Life Cycle Engineering approach to analyse the performance ... · PDF filemeasuring. 89. vi List of figures ... Biobased plastics and their biodegradability [10] ... Table 2.1: Principles

Life Cycle Engineering approach to analyse the

performance of biodegradable injection moulding plastics

Duarte Nuno Fontainhas de Almeida

Dissertação para obtenção do Grau de Mestre em

Engenharia Mecânica

Júri

Presidente: Prof. Rui Manuel dos Santos Oliveira Baptista

Orientador: Prof.ª Elsa Maria Pires Henriques

Vogal: Prof. António José Vilela Pontes

Vogal: Prof. Paulo Miguel Nogueira Peças

Maio de 2011

i

Acknowledgments

I sincerely would like to thank PhD Elsa Henriques for her guidance through all this thesis,

specially on operating results, and for leading me to see more beyond.

I would like to pay respect to Eng. Pedro Teixeira (FAPIL) for his support without which this

study wouldn‟t be possible. Special thanks to Eng. Inês Ribeiro, who was always available to answer

to my doubts about life cycle models and injection moulding process. I also would like to thank Eng.

Ana Pires (FCT – U.Nova of Lisbon) who gave me a lesson about waste treatment management and

waste treatment options.

To my colleagues and friends, specially to Luís Oliveira, José Matos and Tiago Costa, thank

you for all the support.

To my closest family and friends that always stood by me throughout this thesis development

but also during my entire graduation, even when my mood wasn‟t the best, thank you so much.

Finally, i would like to thank to my beautiful lady Rita. Thank you so much. For everything.

ii

Abstract

The use of biodegradable and compostable plastics based on renewable raw materials (R-

BDP) has a rising interest derived from its particular characteristics. Currently, various R-BDPs are

combined to improve some technical requirement of the final products, to open up new applications or

to reduce costs. The specific use of renewable raw materials such as maize, potato, wheat and other

carbohydrate sources as feed stocks for the production of R-BDPs is claimed to give the final products

certain advantages in terms of reduced environmental impact. These may include a reduction in the

use of fossil resources, reduced CO2 emissions and energy content and improved waste disposal

options. To assess the overall impact of the use of such materials, the economical, environmental and

functional performance must be analysed on a life cycle approach.

In this thesis a Life Cycle Engineering (LCE) model is developed to compare the economical,

environmental and technical dimensions of performance for 4 different blends of R-BDPs when

processed through injection moulding technology, following a material cradle-to-grave approach.

Moreover, to understand the claimed advantages of these particular plastics, they are compared to a

well-known plastic of general use, in the case, Polypropylene (PP). The proposed LCE model allows

full comparison of the R-BDPs, supporting informed material selection decisions in a product design

context. The aggregation of the 3 performance dimensions into a ternary decision space supports

materials comparison and the identification of their „„best alternative domains‟‟.

Key-words: Life Cycle Engineering, Life Cycle Cost, Life Cycle Assessment, Functional

Assessment, Biodegradable Plastics, Injection Moulding.

iii

Resumo

A preocupação com a utilização de plásticos biodegradáveis e compostáveis obtidos a partir

de matérias-primas renováveis (R-BDP) tem sido crescente, devido às suas características

particulares. Actualmente, vários R-BDPs são combinados para melhorar determinados requisitos

técnicos dos produtos finais, para diversificar a gama de aplicações ou para reduzir custos.

Alegadamente, a utilização específica de materiais derivados de recursos renováveis tais como milho,

batata, trigo entre outras fontes de hidratos de carbono como matérias-primas para a produção de R-

BDPs, confere aos produtos finais determinadas vantagens em termos da redução do impacto

ambiental. Estas vantagens podem incluir a redução na dependência de fontes fósseis, redução das

emissões de CO2 e de conteúdos energéticos, assim como melhores opções de deposição de

resíduos. Para avaliar o impacto global do uso destes materiais, os desempenhos económico,

ambiental e funcional, devem ser analisados numa perspectiva de ciclo de vida.

Nesta tese é desenvolvido um modelo de Engenharia de Ciclo de Vida (Life Cycle

Engineering - LCE) para comparar o desempenho de 4 misturas diferentes de R-BDPs, processados

pela tecnologia de moldação por injecção, nas dimensões económica, ambiental e funcional,

adoptando uma abordagem cradle-to-grave do material. Além disso e para perceber as alegadas

vantagens destes plásticos em particular sobre os plásticos convencionais, estes são comparados

com um plástico de uso geral e de origem não renovável, no caso, o Polipropileno (PP). O modelo de

LCE proposto permite compreender toda a extensão da comparação dos R-BDPs, contribuindo para

um processo de tomada de decisão informado e sustentado nas actividades de desenvolvimento de

produto. A integração das 3 dimensões de desempenho num espaço de decisão ternário permite a

comparação dos materiais e a identificação dos seus “domínios de seleção”.

Palavras-chave: Engenharia do Ciclo de Vida, Custo do Ciclo de Vida, Avaliação do Ciclo de

Vida, Análise Funcional, Plásticos Biodegradáveis, Moldação por Injecção.

iv

Index

Acknowledgments .........................................................................................................................i

Abstract ........................................................................................................................................ ii

Resumo....................................................................................................................................... iii

Index ........................................................................................................................................... iv

List of figures .............................................................................................................................. vi

List of tables .............................................................................................................................. viii

List of equations .......................................................................................................................... ix

Glossary .......................................................................................................................................x

1. Introduction ........................................................................................................................ 1

2. State of the art of biodegradable plastics and Life Cycle Engineering approach .............. 3

2.1 Pursuit for new materials towards solving environmental issues ...................................... 3

2.1.1 Plastics‟ raw material source, biodegradability and compostability ........................ 6

2.1.2 R-BDPs .................................................................................................................... 8

2.1.3 Environmental advantages of R-BDPs .................................................................. 11

2.1.4 Waste management of R-BDPs ............................................................................ 14

2.1.5 Food Supply: scarcity of agriculture resources ..................................................... 17

2.1.6 Future developments for R-BDPs ......................................................................... 18

2.2 Life Cycle Engineering - LCE .......................................................................................... 19

2.2.1 Life Cycle Cost - LCC ............................................................................................ 21

2.2.2 Life Cycle Assessment - LCA ................................................................................ 22

2.2.3 Functional Assessment – FA ................................................................................. 25

2.2.4 Known applications of the Life Cycle Engineering ................................................ 27

3. Application of the LCE approach to analyse the performance of R-BDPs in injection

moulding process .................................................................................................................................. 28

3.1 Characterization of the previous work ............................................................................. 30

3.1.1 Materials characterization ..................................................................................... 30

3.1.2 Samples ................................................................................................................. 30

3.1.3 Injection moulding process characterization ......................................................... 31

3.2 Purpose of the study ....................................................................................................... 35

3.3 Identification of the plastic materials life cycle stages ..................................................... 36

3.3.1 Raw material acquisition ....................................................................................... 37

3.3.2 Plastics processing ................................................................................................ 37

3.3.3 Plastic parts manufacturing ................................................................................... 37

v

3.3.4 End of life: final disposal options ........................................................................... 37

3.4 Life Cycle Models ............................................................................................................ 40

3.4.1 Life Cycle Cost - LCC ............................................................................................ 40

3.4.2 Life Cycle Assessment - LCA ................................................................................ 57

3.4.3 Functional Assessment - FA ................................................................................. 64

3.5 LCE Model ....................................................................................................................... 69

3.5.1 Global evaluation ................................................................................................... 69

3.5.2 Sensibility analyses ............................................................................................... 71

4. Conclusions ..................................................................................................................... 79

5. Further developments ...................................................................................................... 81

6. References ....................................................................................................................... 82

7. Annex ............................................................................................................................... 87

7.1 PLA production technology ............................................................................................. 87

7.2 Technical data sheets of materials .................................................................................. 89

7.3 Equipment used in the experimental work of injection machines‟ energy consumptions

measuring. 89

vi

List of figures

Figure 2.1: Biobased plastics and their biodegradability [10] .................................................................. 6

Figure 2.2: System boundary for PLA (as produced by Cargill Dow at the Blair, Nebraska facility) [4] .. 9

Figure 2.3: Fossil energy requirement for selected FoPs and PLA. (PC=polycarbonate; HIPS=high

impact polystyrene; GPPS=general purpose polystyrene; LDPE=low density polyethylene; PET

SSP=polyethylene terepthalate, solid state polymerisation (bottle grade); PP=polypropylene; PET

AM=polyethylene terepthalate, amorphous (fibers and film grade); PLA1= polylactide (first

generation); PLA B/WP (polylactide, biomass/ wind power scenario) [4]. .................................... 12

Figure 2.4: Contributions to global climate change for some FoPs and PLA ........................................ 13

Figure 2.5: Survey results - Ranking of the end of life disposal preference for R-BDPs [7] ................. 15

Figure 2.6: Adapted overview of the life cycle engineering model proposed by Ribeiro et al [27]. ....... 20

Figure 2.7: Eco Indicator 99 methodology [27]...................................................................................... 25

Figure 2.8: Functional Assessment Methodology [27] .......................................................................... 26

Figure 3.1: Applied methodology ........................................................................................................... 29

Figure 3.2: Sample for tensile tests (185x21x4 mm) ............................................................................. 31

Figure 3.3: Sample for impact/flexion tests (132x13x6.5 mm) .............................................................. 31

Figure 3.4: Injection equipment used in tests at U. Minho .................................................................... 31

Figure 3.5: Injected samples ................................................................................................................. 32

Figure 3.6: Injected 80/20 sample ......................................................................................................... 32

Figure 3.7: Setup times of injection [min] .............................................................................................. 33

Figure 3.8: Overview of the LCE model ................................................................................................ 35

Figure 3.9: Life cycle stages of generic plastic parts ............................................................................ 36

Figure 3.10: Ideal scenario of plastics disposal (S1) ............................................................................. 38

Figure 3.11: 1st intermediate scenario of plastics disposal (S2) ............................................................ 38

Figure 3.12: 2nd

intermediate scenario of plastics disposal (S3) ........................................................... 38

Figure 3.13: Worst scenario of plastics disposal (S4) ........................................................................... 39

Figure 3.14: LCC model ........................................................................................................................ 40

Figure 3.15: Material consumption for 200,000 units ............................................................................ 41

Figure 3.16: Mould production costs estimated distribution .................................................................. 43

Figure 3.17: Injection machine energy consumption model .................................................................. 44

Figure 3.18: Injection stage costs distribution ....................................................................................... 49

Figure 3.19: Injection stage costs distribution in % ............................................................................... 49

Figure 3.20: Injection cycle time Vs. Injection and Raw material costs for 200,000 units .................... 50

Figure 3.21: Deposition method related costs distribution .................................................................... 54

Figure 3.22: EOL total costs for each scenario of disposal ................................................................... 54

Figure 3.23: LCC costs distribution for 200,000 units ........................................................................... 56

Figure 3.24: LCA Model ......................................................................................................................... 57

Figure 3.25: LCI boundaries .................................................................................................................. 58

Figure 3.26: LCA final results for 200,000 units (EOL scenario S1) ..................................................... 61

vii

Figure 3.27: 10/90's life cycle environmental impacts distribution ........................................................ 61

Figure 3.28: Plastics processing stage environmental impacts evolution with starch content .............. 62

Figure 3.29: LCA final results for all EOL Scenarios and production volume of 200,000 units ............ 63

Figure 3.30: Functional Assessment methodology ............................................................................... 64

Figure 3.31: Plastics classification regarding the functional performance ............................................ 68

Figure 3.32: Global evaluation of the plastics life cycle performance based on cost, environmental and

functional criteria. Weight criteria: A – 90% Econ. Perf., 0% Envir. Perf., 10% Func. Perf.; B –

40% Econ. Perf., 50% Envir. Perf., 10% Func. Perf.; C – 10% Econ. Perf., 10% Envir. Perf., 80%

Func. Perf. ..................................................................................................................................... 70

Figure 3.33: Unitary cost variation with the production volume............................................................. 72

Figure 3.34: Variation of the difference in unitary costs from R-BDPs to PP with increasing production

volume ........................................................................................................................................... 72

Figure 3.35: LCA results for EOL scenario of Landfill ........................................................................... 74

Figure 3.36: LCA results for EOL scenario of Composting R-BDPs and Recycling PP ....................... 74

Figure 3.37: 10/90's life cycle environmental impacts distribution for EOL scenario of Landfill ........... 74

Figure 3.38: 10/90's life cycle environmental impacts distribution for EOL scenario of Composting R-

BDPs and Recycling PP ................................................................................................................ 74

Figure 3.39: Global evaluation of the plastics life cycle performance considering the EOL scenario of

landfill R-BDPs and PP .................................................................................................................. 75

Figure 3.40: Evolution of EI'99 points per part with the surface area for EOL scenario S1 .................. 76

Figure 3.41: Evolution of EI'99 points per part with the surface area for EOL scenario S4 .................. 76

Figure 3.42: Evolution of EI'99 points per part with the surface area for EOL scenario of composting

10/90 and recycling FoPs .............................................................................................................. 78

Figure 3.43: Evolution of EI'99 points per part with the surface area for EOL scenario of Landfill 10/90

and others ...................................................................................................................................... 78

Figure 7.1: PLA manufacturing overview [4] ......................................................................................... 87

viii

List of tables

Table 2.1: Principles and actions concerning waste management [3] .................................................... 5

Table 2.2: Overview of the different types of R-BDPs [8] ........................................................................ 8

Table 2.3: Energy and GHG savings by selected R-BDPs relative to FoPs - cradle-to-grave basis

(after Patel et al, 2003) [7] ............................................................................................................. 11

Table 2.4: Pros and cons of major waste treatment processes [3] ....................................................... 14

Table 2.5: Percentage of various crops worldwide required to switch all U.S. plastics to PLA [20] ..... 17

Table 2.6: Weights for categories and perspectives [24] ...................................................................... 24

Table 3.1: Injection materials properties [Source: manufacturers] ........................................................ 30

Table 3.2: Characteristics of the injection equipment used for the tests at U. Minho ........................... 31

Table 3.3: Injection variables ................................................................................................................. 32

Table 3.4: Injection cycle times [sec] ..................................................................................................... 33

Table 3.5: Injection materials acquisition cost ....................................................................................... 42

Table 3.6: Injection mould variables ...................................................................................................... 42

Table 3.7: Measured parts and mould properties ................................................................................. 46

Table 3.8: Comparison of values for energy consumption using the simple model and the

thermodynamic-empirical model with the experimental data ........................................................ 46

Table 3.9: Injection machine variables .................................................................................................. 47

Table 3.10: Shredder variables ............................................................................................................. 47

Table 3.11: Plastic parts manufacturing stage data .............................................................................. 48

Table 3.12: Injection moulding stage costs for 200,000 units in batches of 25,000 units ..................... 49

Table 3.13: Costs related to deposition methods (as provided by sources) ......................................... 51

Table 3.14: S1 of EOL costs for 200,000 units ..................................................................................... 52




Table 3.18: Life Cycle Cost for 200,000 units ....................................................................................... 55

Table 3.19: Consumptions over materials' life cycle stages.................................................................. 60

Table 3.20: EI'99 unitary impact values ................................................................................................ 60

Table 3.21: EOL environmental impacts assessment for 200,000 units ............................................... 62

Table 3.22: Example of a pairwise comparison from a survey .............................................................. 65

Table 3.23: Functions‟ weights of importance ....................................................................................... 65

Table 3.24: Weights applied to the material properties ......................................................................... 66

Table 3.25: Functional Assessment ...................................................................................................... 67

Table 3.26: Adimensional values of the candidate plastics in the dimensions of analysis ................... 69

Table 3.27: EI‟99 points/kg of 10/90 and selected FoPs for production and EOL stages ..................... 77

Table 7.1: Material properties for the energy model ............................................................................. 89

Table 7.2: Power measuring equipment ................................................................................................ 89

Table 7.3: Technical data of Sandretto 300T injection machine ........................................................... 90

ix

List of equations

Equation 2.1 Absolute importance of material properties ..................................................................... 26

Equation 2.2 Relative importance of material properties ...................................................................... 26

Equation 3.1 Energy costs..................................................................................................................... 44

Equation 3.2 Theoretical energy consumption ...................................................................................... 44

Equation 3.3 Energy consumption estimative using the simple model ................................................. 44

Equation 3.4 Energy consumption estimative in the thermodynamic component of the proposed model

....................................................................................................................................................... 45

Equation 3.5 Energy to melt the plastic ................................................................................................. 45

Equation 3.6 Energy to fill the cavity ..................................................................................................... 45

Equation 3.7 Energy consumption estimative using the proposed model ............................................ 45

Equation 3.8 Machine hour cost [49] ..................................................................................................... 47

Equation 3.9 Shredding process time ................................................................................................... 47

Equation 3.10 Labour Hour Cost [49] .................................................................................................... 48

Equation 3.11 Setup Cost...................................................................................................................... 48

Equation 3.12 EOL Cost ........................................................................................................................ 52

Equation 3.13 Adimensional value of the alternatives (j) in the cost and environment dimensions of

analysis .......................................................................................................................................... 69

Equation 3.14 Adimensional value of the alternatives (j) in the functional dimension of analysis ........ 69

Equation 3.15 Ternary diagram point .................................................................................................... 70

x

Glossary

ABS – Acrylonitile Butadiene Styrene

BDP – Biodegradable plastics

BUW – Biodegradable Urban Wastes

EOL – End of Life

EU – European Union

EN – European Norm

FA – Functional Assessment

FoP – Fossil Origin Plastic

GHG – Greenhouse Gases

LCA – Life Cycle Assessment

LCC – Life Cycle Cost

LCE – Life Cycle Engineering

LCI – Life Cycle Inventory

LCIA – Life Cycle Impact Assessment

MADM – Multiple Attributes Decision-Making

PA - Polyamide

PC - Polycarbonate

PLA – Polylactic Acid

PP – Polypropylene

R-BDP – Biodegradable and compostable plastic derived from renewable raw materials

RRM – Renewable Raw Materials

SAW – Simple Additive Weighting

STA - Starch

SUW – Solid Urban Wastes

USA – United States of America

1

1. Introduction

The increasing environmental awareness of today‟s society has affected most of industrial

processes and products. Plastic, which is one of the most versatile materials in the modern age, is

widely used in many products throughout the world. However, its dramatic production increasing has

focused public attention on a potentially huge environmental pollution problem that could persist for

centuries, because of their extremely low degradability, to the expectable scarcity of landfill sites and

to the growing levels of water and land pollution. Furthermore, as the great majority of plastics are still

derived from fossil fuel resources, their rapid increase will put further pressure on the already limited

non-renewable resources on earth. This new context of an environmentally conscious society has

fostered the development of new solutions for plastics, with allegedly lower environmental impacts.

In fact, plastics derived from renewable raw materials (RRM) and in particular, biodegradable

and compostable plastics derived from RRM (R-BDP) may serve as a promising solution to the

overloaded landfills by diverting part of the volume of plastics to other means of waste management

and, in most of the cases, by preserving non-renewable resources. These materials have been

strongly developed driven by increasing concern in sustainable development, in the desire to reduce

dependence upon finite resources and in changing policies and attitudes in waste management.

However, it‟s crucial to understand the implications of the transition to these “greener” materials.

This thesis aims to compare several types of plastics made from RRM applied to products

manufacturing by the injection moulding process. Moreover, to realize their level of performance they

are compared to a well-known fossil origin plastic (FoP) and commonly used in that technological

process; in the case, Polypropylene (PP). This performance evaluation assesses not only the

environmental aspects, but also the economic and functional aspects, following a cradle-to-grave

approach.

Starch (STA) has been seen as a possible substitute for FoPs as it is both renewable and

biodegradable. However, due to its water sensitivity and low mechanical properties, it‟s not suitable for

many plastic products. One solution developed to overcome these limitations was to combine

plasticized starch with another R-BDP, such as Polylactic Acid (PLA). Following this research area,

this study aims to compare four different types of R-BDPs with different amounts of STA and PLA,

considering a final product produced by injection moulding. The comparison, unlike most studies in the

area regarding only environmental impacts, comprises also a comprehensive economical and

functional performance analyses, within a Life Cycle Engineering (LCE) scope. Hence, it allows having

an integrated view of the advantages and disadvantages of using these new materials regarding

several dimensions of analysis.

The economical dimension analysis was made based on the Life Cycle Cost (LCC)

methodology. A process based cost model was developed, which permits to account all the costs

resulting from a product life cycle. The environmental impacts were evaluated using the Life Cycle

2

Assessment (LCA) methodology, which uses the same data gathered for the economic analysis about

the product‟s life cycle stages, to obtain an eco indication that expresses the environmental behaviour

of materials. The analysis of the functional dimension was based on the decision matrix method, in

which the candidate materials were compared taking into consideration its intrinsic characteristics and

its correlations with the most important characteristics of a plastic part.

Finally, instead of following the traditional approach of analysing the dimensions separately,

the three dimensions of analysis were aggregated in a single analysis framework. The result is a more

comprehensive view of the possible choices. The framework is a ternary diagram, in which the

dimensions of analysis are represented in each axis. With this approach, the difficult task related to

the materialization of the relative importance of the three dimensions into a set of weights is

overcome. The use of ternary diagrams to support decisions has already been applied in other

industrial frameworks. Results from the global evaluation depend on assumptions taken during the

study. Hence, a few sensibility analyses were made in order to assess the relevance of those

assumptions in the global evaluation. These sensibility analyses were possible thanks to the flexibility

of the developed models which permit varying input parameters and rapidly visualize its implications

on the outputs, or final results. Therefore LCE may be an effective tool to compare R-BDPs, since

integrates different dimensions of performance throughout all life cycle stages.

Data concerning the injection moulding process of the plastics in comparison, such as material

properties, injection equipment characteristics, injection parameters and, parts‟ geometry and

properties, was kindly provided by Eng. Pedro Teixeira, who made the injection and mechanical tests

in the scope of his PhD thesis. All other kind of information used to make the analyses (like waste

management practices or waste treatment options costs), because of the lack of sources availability,

required exhausting efforts of research and continuous contacting with enterprises and entities in the

business, to gather it. So, some values necessary to proceed with the analysis were assumed based

in few, yet reliable, sources

This thesis begins by presenting in Chapter 2 the state of the art of R-BDPs and LCE

approach. In Chapter 3, the LCE approach it‟s applied to analyse the performance of R-BDPs in the

plastics injection moulding process. Finally, the conclusions and suggestions to further developments

may be found in Chapters 4 and 5, respectively.

3

2. State of the art of biodegradable plastics and Life Cycle

Engineering approach

As the title suggests, this chapter is divided in two major areas. First the state of the art for

biodegradable plastics is characterized. Secondly, the, Life Cycle Engineering approach used to

analyse the R-BDPs‟ performance in injection moulding is described, as well as its three dimensions of

analysis: Life Cycle Cost as the economical dimension, Life Cycle Assessment as the environmental

dimension and Functional Analysis, as the functional or technical dimension. Being LCE the

philosophy that aggregates these three analyses of performance.

The chapter begins by introducing the driving forces for searching new kinds of plastics in

order to solve or at least alleviate environmental issues and contribute for a more sustainable

development. Existing types of plastics derived from RRM are briefly explained as well as the

differences between them. Also material characteristics such as biodegradability and compostability

are introduced in order to give further comprehension of these phenomena.

Further on, insights of the specific R-BDPs are presented along with comparisons with

conventional FoPs. Moreover, it‟s of relevance to understand the challenges for the arising of these

new plastics in society.

After understanding state of the art of plastics derived from RRM and in particular of R-BDPs,

it‟s introduced the LCE approach and also the methodologies that sustain the approach as a decision

making tool of alternative products or systems in comparison.

2.1 Pursuit for new materials towards solving environmental issues

Most plastics are made out of oil products, and so plastics production has an impact on oil

consumption. The total oil consumption of the world in 2008 was 87.2 million barrels a day. Known oil

reserves total 1.24 trillion barrels, which at the current rate of consumption would last 41 years. 99% of

plastics feedstock comes from oil: Ethylene, Propylene, and Styrene are extracted directly from crude

oil. The amount of oil used to make plastics is 4% of total oil consumption [1]. However, more than 4%

of the world‟s oil production actually is used by plastics since the 4% only accounts for plastic

feedstock and not for heat, energy, and transportation used in making and selling plastics [2].

Considering the massive amount of oil the world uses in a day even 4% is a very large quantity of oil.

The rapid increase in production and consumption of plastics has led to the serious plastic

waste problems, so called „White Pollution‟, and landfill depletion, because of their high volume to

weight ratio and resistance to degradation. Accumulated plastic film residues in soil have caused

significant decrease on its efficiency. Plastic wastes floating on rivers and lakes are increasingly

threatening fishery, navigation, and operation of hydropower plants, irrigation and other public works.

4

Moreover, as most of plastics have fossil fuel origin, their rapid increase will put further pressure on

the already limited non-renewable resources on earth [3].

The use of fossil energy resources is an important global issue. Oil resources are limited and

many experts believe that there will be supply disruptions and possible limitations within the next few

decades [4]. But an even more important problem with the use of fossil energy is the huge

translocation of carbon from the ground into the atmosphere accompanied by emissions of sulphur

and nitrogen oxides as well as all kinds of hydrocarbons and heavy metals [5]. Fossil fuels are also the

dominant global source of anthropogenic1 greenhouse gases (GHG), rising concentrations of which

are widely understood to drive global warming [5], with what a growing majority of the scientific

community believes will lead to an unstable and unpredictable climate. As a result, products and

services providing equivalent or superior function with little or no resulting GHG emissions will enjoy

an increasing global market advantage [4].

Advanced technology in FoPs has brought many benefits to mankind, but its consequences on

waste accumulation and resources depletion make it important to find sustainable plastic substitutes,

especially for short-term packaging and disposable applications [6].

It is expected that the arising of R-BDPs may solve or at least reduce some of the

environmental issues worldwide, promoting a more sustainable future. Some of these problems mainly

include [3] :

a) Increasing pressure on landfills; it is hoped that biodegradable plastics would divert

part of bulky plastic wastes from landfilling. It will also facilitate organic waste

management by eliminating the cost involved in removing the collection bags before

entering compost facilities, since bags made of R-BDPs may also be composted, what

is not true for bags made out of FoPs;

b) Littering of difficult-to-recycle products, for instance foodservice disposables, has led

to enormous environmental and visual pollution, which is of alarming concern

particularly in some emerging economies, such as China, India or Brazil. Recycling of

plastics is not always economically favourable due to the high cost in hauling the

lightweight and high volume plastic waste to the recyclers. Cost and environmental

impacts of cleaning the highly contaminated foodservice products are also significant;

c) Biodegradable plastics derived from renewable sources will contribute to a more

sustainable society by conserving the non-renewable resources, the fossil fuel.

In order to meet these expectations, thus contribute to an environmentally sound waste

management and sustainability, there are some major principles recognized by the international

community to be considered, as follows on Table 2.1:

1 Caused by human activities.

5

Principle Action

Source reduction Minimize the generation of waste in quantity and its potential to cause

pollution by appropriate plant and process designs and cleaner production

Integrated life-cycle Substances and products should be designed and managed such that

minimum environmental impact is caused during their whole life cycle

Integrated pollution Waste management should be based on a strategy which takes into

account the potential for cross media and multi-media synergistic effects

Polluter pays The potential polluter must act to prevent pollution and those who cause

pollution pay for remedying the consequences of that pollution

Standardization Provision of standards for the environmentally sound management of

wastes at all stages of their processing, treatment, disposal and recovery

Public participation

Waste management options should be considered in consultation with the

public, which should have access to information concerning the

management of hazardous wastes

Table 2.1: Principles and actions concerning waste management [3]

Life cycle engineering and in particular LCA, reveals to be a good tool to put this principles into

practice, since it has a broader view over the products entire life cycle and permits to make an

informed decision when it becomes to choose between alternatives.

A recent report made in United Kingdom [7] based on the environmental impact of R-BDPs,

primarily from LCA studies but also from a survey of opinion on R-BDPs among interested parties in

the bioplastics field found that:

Available LCA results usually show that R-BDPs have advantages over FoPs in

several environmental impact categories including typically fossil energy consumption

and global warming potential;

R-BDPs have favourable eco-profiles for many applications due to their relatively low

energy in manufacture, CO2 „neutral‟ status for their agriculture/forestry-based organic

carbon content, renewability and end-of-life value from compost or energy recovery;

Disposal at end of life is a significant phase in the life cycle for capturing

environmental benefit from R-BDPs. Changes in waste management practices should

provide improved disposal options for R-BDPs;

R-BDPs can offer the potential to add value and environmental benefit through the

use of by-products, co-products and wastes from other industries;

Further research is needed on emissions (especially of methane) from R-BDPs in

domestic and municipal composting and on modelling of likely future waste

management practices applicable to R-BDPs. Further development is needed to

establish an appropriate LCA database on R-BDPs;

Certified labelling and Environmental Product Declarations (EPDs) to ISO 14025 offer

good ways for presenting the environmental credentials of R-BDPs to consumers and

businesses.

6

2.1.1 Plastics’ raw material source, biodegradability and compostability

Several articles within the scope of this research use similar but yet different terms to refer to

“green plastics”, leading to misunderstandings and ambiguities. More important than the terms use to

define them, are their origin resource and characteristics. In particular, it‟s important to understand if

the base material has a renewable or non-renewable (fossil) source and if it‟s biodegradable or not.

Plastics made from RRMs can be natural, when directly formed from natural biomass, such as

cellulose; can be synthetic, when made from biomass monomers, such as Polylactic Acid (PLA); or

can be made from synthetic monomers derived from biomass, like Polythene derived from Bioethanol

[8].

Some RRMs based plastics are biodegradable (Biodegradable Plastics - BDPs), meaning that

they can be broken down into CO2 and water by microorganisms under specific environmental

conditions to a defined extent and within a given time [8] [7]. However, others RRMs based plastics

such as Polyethylene will not biodegrade. Therefore plastics may be based on renewable resources

and biodegradable, may be based on renewable resources but not biodegradable or may else be

based on fossil resources and biodegradable [9]. Figure 2.1 gives an overview of different types of

plastics regarding their raw material resource and biodegradability:

Figure 2.1: Biobased plastics and their biodegradability [10]

7

Additionally, some plastics are also compostable. To be designated as compostable, materials

have to biodegrade and disintegrate in a composting system under standard test methods [7]. In the

EU, the criteria for compostability for packaging material are defined in the standard EN 13432. The

criteria used in that standard are linked to the performances of the material regarding biodegradability

and disintegration, the quality of the compost obtained and the absence of any negative effect on the

composting process [8].

The European norm EN 13432 defines the characteristics that a material must own in order to

be claimed as "compostable" and, therefore, recycled through composting of organic solid waste. The

definition of the compostability criteria is very important because materials not compatible with

composting (traditional FoPs, glass, materials contaminated with heavy metals etc.) can decrease the

final quality of compost and make it not suitable for agriculture and, therefore, commercially not

acceptable. This norm is a reference point for the producers, public authorities, composting plant

managers and consumers [11].

According to the EN 13432, the characteristics a compostable material must show are:

Biodegradability, namely the capability of the compostable material to be converted into

CO2 under the action of micro-organisms. This property is measured with a laboratory

standard test method: the EN 14046 (also published as ISO 14855: biodegradability

under controlled composting conditions). In order to show complete biodegradability, a

biodegradation level of at least 90% must be reached in less than 6 months (Note:

measurement errors and biomass production are experimental factors which can make it

difficult to reach 100%: this is why threshold is set at 90% rather than at 100%);

Disintegrability, namely fragmentation and loss of visibility in the final compost (absence

of visual pollution). Measured in a pilot scale composting test (EN 14045). Specimens of

the test material are composted with biowaste for 3 months. The final compost is then

screened with a 2mm sieve. The mass of test material residues with dimensions > 2mm

shall be less than 10% of the original mass (Note: also in this case a 10% tolerance is

allowed, taking into account the typical error found in biological analysis);

Absence of negative effects on the composting process. Verified with the pilot scale

composting test;

Low levels of heavy metals (below given max. values) and absence of negative effects on

the final compost (i.e. reduction of the agronomic value and presence of ecotoxicological

effects on the plant growth). A plant growth test (modified OECD 208) and other physical

chemical analyses are applied on compost where degradation of test material has

happened [11] [12].

Each of these points is needed for the definition of compostability but it is not sufficient alone.

For example, a biodegradable material is not necessarily compostable, because it must also

disintegrate during the composting cycle [11]. On the other hand, a material which breaks during

8

composting into microscopic pieces which are then not fully biodegradable it is also not compostable.

The norm EN 13432 is an harmonised norm i.e. it has been quoted in the Official Journal of the

European Communities, it has been implemented in Europe at national level, and it provides

presumption of conformity with the European Directive 94/62 EC on packaging and packaging waste

[11] [7].

In North America, similar criteria for defining compostability have been established by the

Institute for Standards Research under ASTM D6400-99 Specification for Compostable Plastics [7].

More focus will be given to RRM based, biodegradable and compostable plastics (R-BDPs),

since the plastics selected for the case study (Chapter 3) are composed by different blends of STA

and PLA, both R-BDPs.

2.1.2 R-BDPs

Currently, various R-BDPs are combined to improve the technical performance of the final

products, to open up new applications or to reduce costs. The specific use of RRM such as maize,

potato, wheat and other carbohydrate sources as feedstock for the production of R-BDPs is claimed to

give the final products certain advantages in terms of reduced environmental impact [7]. These may

include a reduction in the use of fossil resources, reduced CO2 emissions and energy content and

improved waste disposal options. Moreover, the key feature of these RRM based plastics is their

biodegradability and compostability, for example when used in packaging applications [7], such as

food or liquid containers, which are usually deposited as urban wastes.

R-BDPs are often used as blends, either with other BDPs or with FoPs [8]. There are available

on the market several different types of R-BDPs, Table 2.2 show some of these plastics, as well as

their manufacturer, their renewable base source and their range of application.

Renewable base source Manufacturer (trade name) Application

Starch-based plastics Novamont (MaterBi) Films, moulding, extrusion

Rodenburg (Solanyl)

Plantic Technologies

Bioplast (Biotec)

Biop

Polyhydroxy-alkanoates (PHA) Kaneka Moulding, films

Metabolix

Telles

PHB Industrial

Polylactic Acid (PLA) NatureWorks (PLA) Films, moulding, fibers

Pyramid Bioplastics

Synbra Technologies

Cellulose derivatives Innovia Films (NatureFlex) Films, moulding

FKuR

Table 2.2: Overview of the different types of R-BDPs [8]

9

Starch - STA

STA may offer a substitute for FoPs as it is renewable, degradable and also compostable.

STA is a carbohydrate that is extracted from various botanical sources (e.g. wheat, maize, potato).

Nevertheless, STA has severe limitations, especially when used in packaging applications, due to its

higher water sensitivity and relatively poor mechanical properties when compared to FoPs. Articles

made from STA swell and deform upon exposure to moisture. One way to overcome these difficulties

and yet maintaining its biodegradability consists of combining plasticized starch with another R-BDP

such as PLA, being itself a derivative of STA [6].

Polylactic Acid - PLA

PLA is at present one of the most promising R-BDPs. It is a versatile new compostable polymer

that is made from 100% renewable resources like corn, sugar beets or rice [4]. PLA is a thermoplastic

made from lactic acid, which is a common organic acid. It‟s transparent and, as some studies have

found [13] [14], PLA has comparable mechanical and physical properties to that of Polyethylene

(PET), Polypropylene (PP) and Polystyrene (PS), which allows it to fulfil different applications [6].

Moreover, PLA can be processed on standard plastics machines, which means that switching a

processing plant from FoPs to PLA is very simple [15].

PLA can be synthesized a number of different ways. One method is direct condensation of the free

acid in solution. Another method is a ring opening polymerization of the ester derivatives of the acid.

This last method requires a zinc or tin catalyst, which requires high temperature and vacuum to

achieve high purity in the polymers [2].

At the present, Cargill Dow Polymers (USA) is the main producer of PLA [4]. Figure 2.2 shows

a simplified flow diagram and system boundary for the production process of PLA pellets.

Figure 2.2: System boundary for PLA (as produced by Cargill Dow at the Blair, Nebraska facility) [4]

10

The flow diagram represents a simplification of the life cycle inventory for PLA production

process, which includes the general inputs and outputs of the system boundary. The analysis permits

to assess the impacts associated to PLA‟s production phases, including corn growing, transportation

of corn to the wet mill, processing of corn into dextrose, conversion of dextrose into lactic acid,

conversion of lactic acid into lactide and finally the polymerization of lactide into polylactide [4].

A further detailed explanation of the various steps involved in the production of the

NatureWorks‟ PLA starting with corn growing and ending with the production of PLA granules is

available in Annex 7.1 of this thesis.

In the near future, Cargill Dow Polymers expects to begin the production of PLA B/WP, which

is the biomass-based process for the next generation of PLA. The „B‟ stands for Biomass and the „WP‟

for Wind power. The process will differ from first generation of PLA in four key ways [4]:

1. Instead of corn-derived dextrose, the primary feedstock is crop residue (stems, straw,

husks, and leaves) from corn or other crops;

2. The cellulose and hemicellulose will be converted into fermentation sugars in a so-called bio

refinery. The remaining lignin-rich fraction will be combusted or gasified to produce steam which will in

turn provide thermal energy for the various conversion processes;

3. The lactic acid production process will be further optimized to increase yield and reduce raw

material use among other improvements;

4. Instead of electricity from the grid, the additional required electricity inputs will be derived

from wind power;

All these improvements and changes will lead to lower fossil fuel and raw material use as well as

lower air emissions, water emissions and solid waste production in the PLA processing operation.

Typical applications

Packaging has been the dominant application area for R-BDPs such as starch and its

derivatives. The relatively high water vapour permeability of starch plastics is useful in applications

such as fog-free packaging of warm foodstuffs [10], but also on meat, fruit, vegetable or yogurt

containers [6].

Starch blends are equally used in applications including biodegradable film for compost bags

for the collection of green waste, shopping bags, strings, tapes, technical films and wrap film; catering

products such as cutlery, cups, plates or food trays have been made of R-BDPs [7] [10], and also in

the textile industry [7].

The agriculture sector is also an important area of starch plastics. Starch blends are used for

agricultural mulch film, plasters, and planting pots (e.g. Mater-Bi and Biolice) [10].

11

Another field where R-BDPs can now compete with non-biodegradable thermoplastics is in

medical industry [7], in which PLA and PLA blends are used to make implants, plates, nails, and

screws for surgery. They are stable and do not biodegrade under standard conditions. The major

limiting factor in the use of PLA is the fact that in its unblended form it softens at 60°C [15].

2.1.3 Environmental advantages of R-BDPs

Plastics may be compared for a wide range of environmental impact categories. This section

focuses in two of the most important categories – fossil energy use and GHG emissions – in order to

illustrate the comparative process and to emphasize key performance benefits of using R-BDPs, and

in particular PLA.

Life Cycle Assessment (LCA) studies results generally show that R-BDPs have advantages

over FoPs in several environmental impact categories (including typically fossil energy consumption

and GHG emissions) but are less favourable or poorer in other categories (typically eutrophication2,

ozone layer depletion and in some cases acidification). This is a common occurrence in LCA

comparisons of different materials. In addition, the different environmental impact categories are

usually not regarded as being of equal weighting in terms of seriousness of effect on the environment

(e.g. global warming is generally regarded as far more important than eutrophication) [7].

On balance, R-BDPs are reported to have favourable eco-profiles [16] for many applications

by reason of their relatively low energy in manufacture, their CO2 „neutral‟ status for

agriculture/forestry-based organic carbon content, and their end-of-life „value‟ in composting or energy

recovery [7]. Data supporting these findings is presented in Table 2.3, in which two different R-BDPs

such as Thermoplastic Starch (TPS) and PLA are compared to a common FoP, like a Low Density

Polyethylene (LDPE). Both energy and GHG reductions clearly support the use of R-BDPs.

Energy savings * GHG savings *

Biodegradable plastic [MJ/kg BDP] [kgCO2 eq./kg BDP]

Thermoplastic Starch (TPS) 51 3.7

TPS plus 60% polycaprolactone 24 1.2

PLA 19 1.0

*max. +/- 15% depending on whether relative to Low Density Polyethylene (LDPE) or Linear Low Density Polyethylene (LLDPE) according to APME data by Boustead (1999/2000)

Table 2.3: Energy and GHG savings by selected R-BDPs relative to FoPs - cradle-to-grave basis (after Patel et al, 2003) [7]

2 Accumulation of large amounts of plant nutrients on water leading to an excessive algae increase,

which can lead to a decrease in dissolved oxygen, causing death and subsequent decomposition of many organisms, decreasing water quality and possibly profound changes in the ecosystem [53].

12

2.1.3.1 Fossil energy use

The graphic shown in Figure 2.3 compares the fossil energy requirements to produce selected

FoPs and PLA. The cross-hashed part of the bars represents the fossil energy used as chemical

feedstock (the fossil resource to build the polymer chain). The solid part of each bar represents the

gross fossil energy use for the fuels and operations supplies used to drive the production processes.

Figure 2.3: Fossil energy requirement for selected FoPs and PLA. (PC=polycarbonate; HIPS=high impact polystyrene; GPPS=general purpose polystyrene; LDPE=low density polyethylene; PET

SSP=polyethylene terepthalate, solid state polymerisation (bottle grade); PP=polypropylene; PET AM=polyethylene terepthalate, amorphous (fibers and film grade); PLA1= polylactide (first generation);

PLA B/WP (polylactide, biomass/ wind power scenario) [4].

Again, the required energy for PLA is under than that required to produce FoPs. Results are

even more evident when comparing is done with next generation of PLA (PLA B/WP).

A key finding of this analysis is that the first generation of PLA uses 20–55% less fossil energy

than the FoPs. When it comes to the future PLA B/WP the use of fossil energy can be reduced up to

90% compared to any of the FoP being replaced. This will also give a significant reduction in fossil

energy related air and water emissions. This comparison represents the potential for environmental

benefits for plastics made from RRM.

2.1.3.2 Global climate change

Global climate change has been identified as perhaps the most important environmental issue

of this century. GHG emissions are not exactly the same as combusted fossil fuel emissions, because

several non-combustion gases can contribute to global climate change. For example, methane (CH4)

is a potent GHG that can emanate from natural gas system leaks, decomposition of biological

materials, and chemical/ industrial processes. However, GHG emissions are closely correlated to

fossil fuel emissions because combustion of fossil fuels is the source of most GHG caused by human

activity [4].

13

Results from a comparison of the contributions to global climate change from a range of FoPs

as well as the two cases of PLA, undertaken by Cargill Dow [4] are shown in Figure 2.4.

Figure 2.4: Contributions to global climate change for some FoPs and PLA

The analysis demonstrates that the PLA1 (first generation of PLA) production process enjoys

a substantial advantage over most plastics, and is comparable to several others. Even more

significant are the greenhouse benefits that derive from the transition to corn residue (lignin fraction)

and reliance on wind energy for the balance of plant energy requirements. The utilization of the lignin

fraction of ligno cellulosic feedstock for process heat generation „„closes the loop‟‟ on carbon related to

energy generation, and in combination with other factors yields a negative GHG impact for PLA pellets

[4].

A most appealing result of the use of agricultural feedstock for the PLA production and most of

the process energy requirement means that customers using PLA can not only use PLA as a material,

but as a component of their GHG reduction strategies. LCA reveals that no FoP can rival the GHG

sink effect of the improved PLA process. Although disposal of products made of PLA – whether by

combustion, composting or other conventional means – results in a return of carbon dioxide to the

atmosphere, this advantage survives. In addition, the fact that PLA can be chemically recycled into

new feedstock with the proper recovery and processing infrastructure offers the unique opportunity to

permanently close the loop on carbon emissions related to the product and to permanently sequester

carbon dioxide into a product that is constantly renewed [4].

According to Murphy [7], the ideal environmentally sustainable product provides equivalent

function as products it replaces and is available at competitive costs. It is made from renewable

resources, can itself be constantly renewed without degradation in quality or performance, and has a

minimum environmental impact. Such a product is made using only substances known to be safe for

both humans and the environment. Ideally the life cycle of the sustainable product is in balance with

the surrounding ecosystem [4]. Thereby, R-BDPs can provide certain advantages fostering the

environmental sustainability of plastic products.

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2.1.4 Waste management of R-BDPs

Though developed as a solution for the waste problem, R-BDPs create new challenges on

waste management with respect to policies and laws, waste management processes and application

of market-based instruments [3].

The pros and cons of major waste treatment processes are listed in Table 2.4:

Process Pros Cons

Recycling

• Reduce amount of wastes for disposal

• Save resources and energy in virgin

production

• Extend product‟s lifetime, conserve

resources

• Not everything economically recyclable

• Recycling consume energy, emit pollutants

• Recycled product inferior in quality, thus only

lower grade application, limited market

Composting

• Reduce load of landfill by digesting

organics

• End products useful for soil amendment

• Need less energy than recycling or

incineration

• Economics still unfavourable

• Risk of odour and pest problem

• No reliable market for end product (compost)

Incineration

• Reduce waist substantially by

volume/weight

• Generate energy

• Reduce burden of landfill

• High capital and operational costs

• Emissions of hazardous substances (dioxin,

etc.)

• More stringent in operation and control

Landfilling

• Final and indispensable disposal of

wastes, residues from recycling,

incineration, etc.

• Relatively easy to build and operate

• Suitable sites become scarce worldwide

• Costs in increasing significantly due to higher

environmental and sanitary requirement

• Leach and gas emissions problems

Table 2.4: Pros and cons of major waste treatment processes [3]

Recycling may be the best final disposal alternative for conventional plastics, regarding the

climate change potential, depletion of natural resources and energy demand, being these

environmental benefits mainly brought by the avoided material production [8]. However, R-BDPs are

thermoset and not thermoplastics as most of FoPs, which turn the mechanical recycling process of

more difficult or non-recyclable in an economically viable way since the method implies shredding and

then melting the plastic so it can be remoulded, during which biodegradable plastics will usually

decompose [3] [2]. Inherently, R-BDPs are not created for mechanical recycling [7]. Furthermore,

mixing of these plastics in the feedstock of recycling will damage the process of mechanical recycling

and the quality of recycled products. For this sake, products made of R-BDPs should be labelled as

such, so that they can be sorted out from recyclables [3].

Composting is the most relevant waste treatment process of R-BDPs. Internationally accepted

definitions and standards for R-BDPs are all based on their compostability so far. The success of R-

BDPs will be decided by the availability of composting/digestion facilities. Experience worldwide

15

reveals the economic viability of composting depending on: source separation and collection of

organic wastes and recovery of non-compostables; the existence of a market or use for the compost

generated. Therefore, the closer the market, the more likely that composting is sustainable [17].

Incineration is not the desired destination of R-BDPs, regardless of being plastics containing

mainly carbon and hydrogen, R-BDPs produce significant amounts of heat, therefore consideration of

heavy metals and persistent organic pollutants generated from incineration is also applicable to R-

BDPs [3].

Accidental entry of R-BDPs, except for its volume, should not cause any problem in a standard

landfill which is designed to be inert with wastes inside degrading very little [3]. However, as

substandard landfill is common in many less developed countries, entry of R-BDPs will increase the

biodegradation already existing by generating more leachate and GHG, such like CO2 and methane,

and thus worsen the contamination of ground and surface water, and environment [18]. Therefore and

as with any material, landfill should be avoided since it represents a loss of useful material and energy

[9].

A study performed in United Kingdom [7], aiming to assess the contribution of bioplastics

towards sustainability, and based on a survey of around 100 questionnaires distributed to selected

networks and groups may clarify the preferences for composting as final disposal option for R-BDPs.

Among other questions, it was asked “What are the preferred methods of disposal of R-BDP

(Landfilling, Incineration, Domestic Composting, Municipal/Industrial composting, Anaerobic Digestion

or Recycling?”. Results are represented in Figure 2.5.

Figure 2.5: Survey results - Ranking of the end of life disposal preference for R-BDPs [7]

The answers showed a clear preference (75%) for composting, either in municipal or domestic

systems, as the favourite disposal route for R-BDPs. In opposition to that, landfilling appears as the

worst final disposal option (100%).

Thus, reduction of landfilling may be one of the key reasons why use of R-BDPs might lead to

greater sustainability.

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2.1.4.1 Source separation and life cycle approach

This section analyses the possible challenges that might be brought about by

commercialization of R-BDPs on commonly practiced waste management technologies. It is taken the

example of composting as it is the most relevant for this kind of plastics.

It has been identified that the reduction of contaminant level is crucial for the success of

composting, which in return provides guarantee for the acceptance of biodegradable materials. There

are various options to get cleaner compost [3]:

1. Reduce or eliminate contaminants in product design so as to facilitate the after-use disposal

and improve the quality of recycled products, such as compost. It calls for life cycle consideration

beyond waste management system to design, production and consumption;

2. Source separation of waste by households and commercial consumers into recyclable

products, compostable products (organic wastes and non-recyclable papers, etc.) and wastes for final

disposal;

3. Sorting at a centralized facility after collection and prior to composting is included in most of

the modern municipal waste composting facilities;

4. To separate contaminants after composting, traditional practice of municipal waste

composting.

Evidence from the experimental trials and operating facilities show that options 1 and 2 have

higher potential to reduce contaminant level than options 3 and 4, thus should be prioritized and

encouraged. It is very expensive to remove contaminants from mixed waste compost in order to meet

the increasingly stringent requirements set by many countries on quality of compost. This is actually

the major reason why industrial scale composting did not succeed in the past. Centralized sorting

before composting becomes increasingly difficult and less effective too with the increase in separation

cost. Moreover, some liquid contaminants, fine dust or paint chips containing heavy metals and/or

toxic chemicals can attach to the otherwise clean organic wastes during collection and storage.

Source separation, on the other hand, provides higher quality of compost with significant lower

contaminant levels than centralized sorting and after-composting screening, as revealed by research

in some European countries and in USA [19]. Source separation of organic wastes can achieve a high

level of diversion potential of wastes from landfill, estimated in the range of 25–50%, which is

comparable to that of centralized sorting [19].

Introduction of life cycle approach is the new trend in the industry of plastics [3]. A truly

environmentally benign product should have minimum adverse impacts on human health and on

environment, not only during its production and use stages, but also in final disposal after being

discarded. An environmental perspective to the production of R-BDPs might include decreasing the

use of toxic chemicals and heavy metals in plastic additives, unwanted by all disposal methods and

17

organic recycling in particular [3]. This should be borne in mind while developing R-BDPs and planning

for new applications.

2.1.5 Food Supply: scarcity of agriculture resources

According to Momani [2], the switch to plastics derived from RRM has the potential to affect

the world‟s food supply in a number of ways. R-BDPs derived from food crops like corn, soy, sugar

cane, and others would directly decrease the amount of those crops that would be available for food.

R-BDPs derived from non-food crops like switch-grass would indirectly affect food production by

competing for land with food crops. R-BDPs derived from agricultural waste or algae would have little

to no impact on the food supply [2]. Given the fact that food shortages exist in many regions of the

world interfering with the world‟s food supply and scarcity of agricultural resources is a major concern.

Being PLA derived from sugars, the production of products based in this material will

consequently compete with the food industry. Sugar can be made from a variety of plants and the total

annual yield of sugar if all corn were used for making sugar would be 318 million metric tons. For

sugarcane it would be 156 million metric tons, for rice it would be 318 million metric tons, and for

potatoes it would be 14 million metric tons. The annual production of plastics in the U.S. totals 52.5

million metric tons. The production of PLA requires 147% the mass of the plastic to be imputed as

sugar. Therefore the sugar requirement if all U.S. plastic production were switched to PLA would be

77.2 million metric tons. This would require about 24.3% of the world‟s supply of rice or corn.

Alternatively, PLA production would consume 49.5% of the world‟s sugar cane or 551% of the world‟s

potato production. The total production of sugar, derived from all crops, in the world is 1.3 billion metric

tons. American production of PLA would consume 5.94% of the entire world‟s sugar production if all

plastics made in the U.S. were replaced by PLA, after Kawamoto [20]. Results are summarized in

Table 2.5. It‟s clear that PLA could not replace all plastics to begin with.

Corn Rice Potato Sugar cane Total sugar

Crop percentage

24.3% 24.3% 551% 49.5% 5.94%

Table 2.5: Percentage of various crops worldwide required to switch all U.S. plastics to PLA [20]

In order to maintain the safety of the food market, it has been suggested to the American

authorities to convert reserve lands, under the Conservation Reserve Program (CRP), into cropland

for plastics derived from RRM. The program, CRP, encourages farmers to set land aside in order to

preserve the soil and natural environment; in 2006, 14 million hectares of farmland were being left

unused as part of the program [21], knowing that each acre of land could produce around 3.63 tons of

corn, it would result that the total amount of corn that could be produced if all the CRP land were put

into used would be 131 million tons annually [22]. Thereby, it would be enough to convert all plastics

production to PLA.

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2.1.6 Future developments for R-BDPs

To close this chapter it should be referred some likely future needs and trends in R-BDPs

manufacture and development in the market:

At the present, R-BDP manufacture is generally small-scale comparing to FoP. It is

likely as scale increases technical improvements and environmental economies of

scale will accrue for R-BDPs [7];

Potential exists to further develop more „durable‟ (but at the same time less

biodegradable) R-BDPs [7];

Further development is needed to continue building wider ranges of technical

performances of R-BDPs [4];

Certified labelling and Environmental Product Declarations offer good ways for

communicating the environmental credentials of R-BDPs to consumers and

businesses [23].

Moreover, the increase on consumers‟ environmentally consciousness towards waste

separation and supporting the costs of R-BDPs‟ products will further implement these particular

plastics in society and contribute for a more sustainable development.

19

2.2 Life Cycle Engineering - LCE

The manufacture of products over time has changed as new targets emerge. Several factors

such as available technology, market needs and society values have dictated this change. Until the

19th century, the manufacture of products was custom and in small volumes, with very limited

technology [24]. From that date until 1913, when Henry Ford revolutionized the factory concept with

the creation of assembly lines and thus, manufacturing engineering with the innovation of mass

production [25], with ultimate goal being low cost and little differentiated production. In the 80s, the

arising of computer-assisted industrial automation and consequently increasing flexibility of production

systems has enabled a wider variety of products. With the increased offer came a higher demand on

quality and it was necessary to limit production to market demand. The globalization of the market in

the 90s forced to increase the competitiveness of enterprises, making the industry increasingly turning

to the market [24].

Nowadays, to meet new market needs, the development of a product cannot be focused only

on the classic approaches, such as technical and economic performances. In recent years,

environmental problems have emerged as one of the most important global concerns. Consequently,

strategies and development methods to promote products as ecological as possible have been

incorporated in product design. In this context, to have a broader view of the product‟s environmental

impacts, an innovative approach which extends to the end of the product‟s useful life and retirement

has been developed, in opposition to the conventional approach, where the product‟s sale is

considered as the final analytical step.

Life Cycle Engineering (LCE) emerged in response to the need to develop life cycles causing

the lowest possible environmental impacts, while still offering economic viability. LCE refers to

„„Engineering activities which include: the application of technological and scientific principles to the

design and manufacture of products, with the goal of protecting the environment and conserving

resources, while encouraging economic progress, keeping in mind the need for sustainability, and at

the same time optimizing the product life cycle and minimizing pollution and waste‟‟ [26]. Therefore,

LCE can be defined as a decision making methodology that considers performance, environmental,

and cost dimensions throughout the duration of a product, guiding design engineers towards informed

decisions. LCE differs from other life cycle approaches in this point; while LCE incorporates these

three dimensions of analysis, Life Cycle Assessment (LCA) only covers environmental aspects, Life

Cycle Cost (LCC) covers the economic aspects and Life Cycle Management (LCM) includes “only”

economic and environmental aspects [27].

Life Cycle Engineering includes not only conventional tools, as technical performance analysis

based on mechanical, electrical, and chemical properties, but also life cycle methodologies based on

process models, to analyse economic performance (LCC) and environmental performance (LCA) [27].

Lately, several researches have published under the umbrella of „„Life Cycle Engineering‟‟.

Three main research branches under the scope of LCE can be identified in the literature: 1) Definition

20

of guidelines and frameworks fostering the application of LCE philosophy in the early design phase of

products, services and social policies; 2) Development of strategies and approaches aiming the

implementation of LCE principles in the product‟s reliability and serviceability design and modelling; 3)

Development of tools and models that apply the LCE principles to compare alternatives during the

product or process design phase [28]. As the third branch is the most related with this work, more

emphasis will be given to it.

There are several published works about the LCE‟s application to different case studies, such

as, in material selection to automotive and injection moulding, technology selection for plastic injection

moulds, construction and computer industry [29] [28] [27], to name only a few, targeting the individual

evaluation of functional, economic and environmental dimensions of products or systems.

Traditionally each dimension of LCE methods is analysed separately and in some studies,

weights are given to each dimension in order to evaluate each alternative with a single value.

However, this is always a controversial step in any type of study dealing with analysis of different

nature. To solve this problem, Ribeiro et al. [27] proposed an LCE model in which the three

dimensions of analysis were aggregated into a single analysis framework. The result is a more

comprehensive view of the possible choices. The framework is a ternary diagram, in which the

dimensions of analysis are represented in each axis. With this approach, the difficult task related to

the materialization of the relative importance of the three dimensions into a set of weights is

overcome. The use of ternary diagrams to support decisions has been applied in industrial frameworks

[30]. Figure 2.6 illustrates the referred analysis model proposed.

Figure 2.6: Adapted overview of the life cycle engineering model proposed by Ribeiro et al [27].

In particular, material selection is an important application area of LCE. As material selection

is part of product design, decisions taken during this stage largely influence the product‟s costs and

environmental impacts for its entire life. As environmental impacts of products are directly influenced

21

by the materials environmental properties, the material selection assumes a strategic importance [31]

[32]. Despite of the lack of specific LCE literature dedicated for the comparison of R-BDPs

performance in injection moulding process, this approach suits perfectly to perform such task, as it

permits to have a global view of R-BDPs life cycle performance in terms of economic, environmental

and functional dimensions of analysis.

In the following sections it will be presented the life cycle methodologies used to perform the

analyses of the three dimensions of LCE‟s approach. That is, Life Cycle Cost (LCC) to analyse the

economic aspects, Life Cycle Assessment (LCA) to account the environmental impacts and finally the

technical/functional analysis.

2.2.1 Life Cycle Cost - LCC

The LCC analysis is a tool that translates the total cost of a product, structure or system over

its useful life. The growing need for LCC models appeared in the 60s, when it was found the impact

that economic decisions made in the early stages of developing a product would have in the future.

The objective of LCC analysis is to identify the economic consequences of a decision [24]. For

example, in choosing a material for a part, the material with lower cost of acquisition may not be the

most economically viable material at the end of the life cycle. The LCC model evaluates the costs of a

product, project or system from development to production and use, maintenance and end of life, thus

allowing an informed and conscious decision.

Life cycle cost generally refers to „„all the costs associated with a product throughout the

product‟s life‟‟ [33]. Its objective is to cover the assessments of costs in all steps of the product‟s life

cycle, including the costs that are not normally expressed in the product market price, such as costs

incurred during the usage and disposal.

LCC methodology includes all the internal and external costs related to the product. Internal

costs are the ones supported by the manufacturing enterprise, while external costs are the costs for

which the enterprise is not responsible. Internal costs can be separated in conventional costs, the

direct costs detouring from production, indirect costs, enterprise‟s general costs attached directly to

the product, and the intangible costs, costs that are several times omitted in accountability due to their

probabilistic nature. The external costs are the costs for which the company is not responsible, for

example the products use costs [34].

In mid-nineties, the International Electrotechnical Commission published the IEC 60300

standard due to the great interest towards the LCC in the maintenance area [35]. This standard gives

guide lines in how to perform cost analysis of a product‟s life cycle. Apart from this standard of LCC

applied to the maintenance of equipments, there isn´t a general procedure to perform LCC analysis as

the costs incurred should vary with the application field [36].

22

Greene and Shaw [37] after reading several models descriptions, concluded that most of the

effort in doing a LCC analysis is done previous to the introduction of data in a computer software.

They described a sequence of general steps that should be taken in most applications:

1. Determine the purpose of the LCC analysis;

2. Define and establish the boundaries of the system;

3. Select/Develop the appropriate model to estimate costs;

4. Collect data and introduce the entry inputs in the model;

5. Evaluate the veracity of the inputs and outputs;

6. Formulate the results of the LCC analysis;

7. Document the LCC analysis;

8. Present and discuss the results of the LCC analysis.

That process should be dynamic and applied to a specific situation, so some of the steps

above may switch places or even be eliminated. The inherent difficulty of LCC concerns the necessity

of collecting a large amount of data, which most of the times isn‟t registered or is hard to find [38].

LCC is essentially an evaluation tool in the sense that it gets on important metrics for choosing

the most cost-effective solution from a series of alternatives [27]. However, the LCC method by itself,

without additional assessments, is not sufficient as an indicator for sustainable practice. Thus it is also

advised to evaluate the product on an environmental basis also with the same life cycle approach,

namely with the LCA [39].

2.2.2 Life Cycle Assessment - LCA

Topics such as sustainable development, fossil and natural resources availability, global

climate change and waste reduction are increasingly dominating political and industrial agendas.

Therefore, the relevance of the environmental performance of processes, products and services in

decision–making is rapidly growing [9].

The life cycle of a product begins with the extraction of raw materials from the earth, followed

by the manufacture, transport and use. This life cycle ends with products final disposal, which may be

recycle, reuse, landfill, incineration, composting, etc. In each phase there are several emissions and

consumption of resources. With a life cycle perspective all the environmental implications must be

addressed. In this context the Life Cycle Assessment (LCA) presents itself as a management tool that

allows the assessment of environmental impact of a product, facility or system during its whole life

cycle.

The first studies similar to LCA were performed during the 70 decade, driven by the oil crisis,

and they were essentially energetic evaluations. With the ending of the crisis in 1975 the motivation for

this kind of studies decayed for a while. In the late 80‟s, the environmental impacts associated with the

natural resources and energy consumption were severely discussed, especially after the acid rain in

23

Europe and USA, and also with the increasing conscience of the greenhouse effect. These two

problems join the growing list of environmental problems due to the wastes deposition. In this context

the general public start to think about the Nature capacity to deal with all the wastes generated, and

the industry began to be pushed to reduce drastically their wastes. The LCA concept was born and it

had been gaining strength since then [36].

Presently, LCA consists of four steps:

1. Definition of the goal and scope of the study – boundaries, functional units and data

collection criteria are established;

2. Life Cycle Inventory stage (LCI) – construction of the product life cycle model with all

environmental inflows and outflows, regarding materials and energetic streams for

each life cycle stage;

3. Life Cycle Impact Assessment (LCIA) – evaluation of the environmental relevance of

all the inflows and outflows. These flows are related to environmental impact

categories, thus a model of characterization in order to estimate the effect on these

flows in the categories is developed, resulting in an index for each category of

environmental impact;

4. Results interpretation – finally, the interpretation of results is performed to evaluate the

entire study, bearing in mind its purpose [27].

The assignment of a ranking of weights to the environmental impact categories is a

controversial issue in this methodology due to their reliance on value judgments and hence

subjectivity. There are several methods available for its allocation within the LCA, the EPS-system, the

method Tellus, the method of eco-scarcity, the Eco Indicator 95 (EI ‟95), or its evolution Eco Indicator

99 (EI ‟99) and other methods of distance to the target value [34]. Thereby, there are several methods

for the LCIA stage that are compatible with the requirements of ISO, but most experts prefer to select

a method already published rather than developing a new one [24].

Notice that LCA is not a method for environmental accounting, as it typically lacks information

on costs [29]. The LCA is used mostly by companies for the successful implementation of an

Environmental Management System, required for their green certification. This certification is done by

the ISO 14000 family, [40] to [41], and nowadays it‟s seen like a competitiveness advantage, providing

new weapons for marketing strategies, by showing the company environmental strengths [36].

The difficulty of the LCA is tracking down all sources of energy or natural resources

consumption, and the emissions generated. To control this difficulty the boundaries of the problem

must be very well defined.

24

2.2.2.1 Eco Indicator 99

Among several other known methods for the LCIA phase, compatible with the ISO

requirements, EI ‟99 is one of the most referred by experts [27] [28]. The indicator assesses the

impacts of emissions on human health and ecosystems. The Ecological Impact (EQ) is represented by

the Potentially Affected Fraction (PAF) or Potentially Disappeared Fraction (PDF) of species, being the

environmental impact given by the Global Warming Potential (GWP), by the Potential Destruction of

the Ozone layer (ODP), etc. The impact on Human Health (HH) is measured by DALY units, which

represent the years of life lost or disabled as a result of the impacts of emissions, and Mega Joule

(MJ) surplus is the measure of Resource (R) depletion. For a given process, emissions are classified

into various categories of impacts and assigned in common units for each category based on impact

factors. The development of these indices was done in their own categories of impact, including land

use and resource scarcity as a category of impact. Modelling of the damage functions were also

developed and cultural theories as tools for dealing with subjectivity were included. This method

considers the analysis of three spheres, namely technosphere, the ecosphere and valuesphere. The

technosphere represents the field of technological processes and systems developed by humans. The

dominance of the ecosphere understands the processes and ecological systems, incorporating the

technosphere. In valuesphere, which means choice of values, three perspectives have been

developed. Depending on the attitude of three human archetypes (individualistic, equalitarian and

hierarchic), it was determined the distribution of weight factors between human health, ecosystems

and resources (Table 2.6). Depending on the perspective chosen, one indicator can be obtained. The

view generally accepted in the scientific community is the hierarchic perspective, being a moderate

perspective [24].

Perspectives

Damage categories Individualistic Equalitarian Hierarchic

Ecosystem 25 50 40

Human Health 55 30 30

Resources 20 20 30

Table 2.6: Weights for categories and perspectives [24]

A general scheme to obtain EI '99 is illustrated in Figure 2.7. This diagram represents the

method to calculate the score of EI‟99 and is divided into three steps: inventory of the inflows and

outflows of the processes in the lifecycle of the product (LCI), damage model of flows and assigning

weights to the three categories (LCIA).

25

Figure 2.7: Eco Indicator 99 methodology [27]

2.2.3 Functional Assessment – FA

Materials selection based on its technical performance, that is, on its properties, is the

classical approach in engineering. Each and every engineering component performs one or more

functions, like bearing load, holding pressure or transferring heat among so many others, being these

taken as material selection conditions [42]. These functions cover from mechanical and electrical

properties to corrosion strength and superficial finishing. In mechanical projects the mechanical

properties tend to gain relevance and there is a wide spectrum of those that can be considered. The

relative importance of these properties is dependent of the component‟s application, being that

different material classes present specific mechanical properties. Appropriate combinations of

properties define the applicability of a certain material for a specific feature. For instance, values of

density and Young‟s Modulus can be used to select light and stiff materials [43].

Within the performance analysis of a product, system or technology, the Functional

Assessment refers to certain factors that contribute to its functional performance and are not included

in the previous dimensions of analysis. In this point resides the difficulty of this analysis, as the

functions to be evaluated this time, must not have been already analysed at the economical neither at

the environmental performance analyses.

The evaluation of the technical performance of a product, tool or other equipment relies on the

know-how of professionals (and users) to choose the relevant technical requirements for the

application. Several decision-making methods can be used on this kind of evaluations, frequently

made on a comparison base, such as graphic theory and matrix approach (GTMA) and fuzzy Multiple

Attribute Decision-Making (MADM) methods, but the expertise of professionals is still crucial for this

type of evaluations [30].

26

An example of a method used to perform the functional analysis in LCE approaches is the one

adopted by Ribeiro et al. [27] for a of material selection study. Figure 2.8 outlines the steps of the

evaluation resulting in a score for each candidate material under evaluation, which is a relative

quantification of the appropriateness of each material for the technical performance of the product.

Figure 2.8: Functional Assessment Methodology [27]

The first step is to identify the product requirements, Ri, and their relative importance, wRi, for

the product performance (requirement weights). Once the ability of a specific material to fulfil the

requirements depends on its properties, it becomes necessary to determine the relevant properties

and correlate them with the requirements. That relation between material properties and requirements

is done through a matrix of indices, W, where each index Wij reflects the contribution of the property Pj

to accomplish the requirement Ri. Most of these indices are zero, meaning that there is no correlation

between the property and the requirement, but the sum of indexes of each line of the W matrix have to

yield the same number, i.e., ∑ ∑ ∑ , which means that the value of X must be

pre-set and distributed through one or several properties correlated with the requirement. The

absolute importance, aPj, of each material property Pj can then be calculated:

Equation 2.1

Finally the material property weight (the relative importance) will be:

Equation 2.2

All the required information to compare the functional or technical performance of a set of

materials is now available. The final step is the construction of a global comparison table in which

27

each material with its quantified properties is quantified against all the others. Since each material

property has its own value and units, the property must be adimensionalized in order to turn possible

to add all the properties. The adimensional properties are then weighted according to the material

property own weight, wPj. Finally, adding the entire weighted adimensional material properties, a

weighted material index, wMIk, is achieved for each material. The potentially “best material” will be the

one with the highest wMI.

2.2.4 Known applications of the Life Cycle Engineering

Life cycle engineering has gained much attention recently due to its significant applications to

various products and systems in industry. A branch of engineering where the LCE methodology is

quite successful is in the automotive design. For example, the LCE was successfully applied in the

automobile fender designs [44]. In this case study, a good choice regarding the material used in the

fender can lower the overall energy consumption during the entire life cycle: production and use. Also

the choice of the best design shouldn‟t consider only the primary energy demand and global warming

potential during its life cycle, since part costs are also a significant factor in this valuation. It concludes

that that the cost factor is a decisive factor when choosing between designs, but the life cycle impact

should also be assessed during the entire life cycle.

Another example of the application of LCE methodology was in technology selection to

manufacture plastic injection moulds for low production volumes [28]. In this study it was compared

two alternative technological processes: a rapid tooling mould made of a spray metal shell backfilled

with resin and aluminium powder (STM mould) and another based on conventionally machined

aluminium (CM mould). The global evaluation based on the three dimension of analysis dictated that

“Considering very low production volumes the STM mould is the „best mould‟ in terms of economic

and environmental aspects, while the CM mould has a better technical performance.” [28]

The requirements for manufacturing operations relatively environmental sustainability have

become more and more stringent every year. As a response to these requirements the manufactures,

around the world have taken several approaches to meet these requirements. As a direct result,

companies on one hand have introduced environmental features at various levels in their product

development processes, in manufacturing operations or in strategic planning, driven either by external

market forces or by internal environmental consciousness. On the other hand, researchers around the

world have developed new tools and techniques that may help the introduction of environmental

features in new products and at the same time reducing costs [36]. Among these techniques the LCE

stands out as an effective tool to be used by the companies since it evaluates not only the functional

requirements but also the environmental implications and costs during the entire life cycle of a

product, system or facility.

28

3. Application of the LCE approach to analyse the

performance of R-BDPs in injection moulding process

This chapter presents the Life Cycle Engineering (LCE) approach used to compare the

performance in injection moulding of selected R-BDPs with a common plastic. The LCE model used

will be explained later on. First the methodology used in this thesis is presented (Figure 3.1).

The R-BDPs in comparison on this study are the same used at a PhD thesis in current

development and some of the information regarding these materials, needed for this work, was kindly

shared by that PhD thesis author, Eng. Pedro Teixeira. So the first task was to investigate about R-

BDPs insights as, characteristics, manufacturing technologies or typical applications. Also the study

on LCE philosophy and in particular its application to material selection was made. Secondly,

characterization of previous work was performed. Here, it was important to gather and understand all

the information about the materials and their properties, about the plastic part into which these

materials were transformed (samples) and about the injection moulding process. Then, and in order to

compare the materials in a life cycle perspective, it became necessary to identify the life cycle stages

for plastic material parts and in particular for R-BDP parts. In particular for the End of Life (EOL) stage,

several possible EOL scenarios were defined based on literature research and experts knowledge.

The fourth step was to collect all the necessary data to introduce in the developing life cycle models

for costs and environmental impacts evaluation. Information regarding to the industrial environment,

such as labour, equipment and facilities was collected in FAPIL, S.A. Data concerning the EOL stage,

such as waste treatment processes‟ costs, was collected from companies in the business. The data

collection task revealed to be very challenging, because of the lack of info related to this specific R-

BDPs and in particular because of the difficult access to data related with waste management

collection and processes. Exhaustive efforts towards gathering the necessary data related to final

disposal options had to be made and involved contacts to experts and companies. Along and in

continuous feedback with data collection, the development of the process based parametric models

for cost and environmental analysis was done.

The next step was to make the functional assessment analysis and integrate it with the

economic and environmental dimensions, thus completing the LCE approach. This approach

permitted to have a global evaluation of the plastics comparison and consequently define the best

domains of application for each material according to different strategies of selection.

One of the advantages of using process based parametric models is their possibility to vary

the inputs, making it possible to understand their sensitivity to different variables. Therefore and after

the initial analysis different considerations of production volume, EOL scenario and part‟s geometry, to

evaluate how the costs and impacts would behave were tested. Finally, the results are presented and

discussed.

29

Figure 3.1: Applied methodology

30

3.1 Characterization of the previous work

In this sub-chapter the work previously made is characterized. The used materials in this case

study are introduced and in particular their characteristics and properties. The injected samples and

the used parameters of the injection moulding process are presented.

3.1.1 Materials characterization

In this case study 4 R-BDP commercial materials were analysed. They are all based on Starch

(STA) blended with Polylactic Acid (PLA) with different proportions. Due to these different amounts of

PLA and STA, materials have distinct properties. The FoP chosen to compare with the R-BDPs was

the Polypropylene (PP). Properties of all the studied materials are shown in Table 3.1

Material Manufacturer Trade name

Composition Density [kg/m

3]

Melting

point [⁰C] MFI

3

[g/10min]

10/90 Cabopol Biomind

C004 10%PLA+90%STA 1200 90 15-30

40/60 Rodenburg

Biopolymers Solanyl

35F 40%PLA+60%STA 1280 140-145 13

80/20 Cabopol Biomind

R006 80%PLA+20%STA 1250 130 20-40

90/10 Biotec Bioplast GS 2189

90%PLA+10%STA 1300 130 20-40

PP Total

Petrochemicals PPH 9020 - 905 165 25

Table 3.1: Injection materials properties [Source: manufacturers]

Note that the blends with greater concentration of PLA have very similar properties and that

PP has considerable higher melting point when comparing to most of the R-BDPs. As it will be seen

further, this fact has implications on injection machine‟s warm up time and on the injection cycle time.

3.1.2 Samples

As stated before in this text, the purpose of this research is to compare the different blends of

R-BDPs applied to plastic parts obtained by injection moulding, so the focus is the material and not the

product. However, the comparison of the materials following a life cycle perspective, demands to

transform the materials into plastic parts, and according to its geometry and dimensions (Figure 3.2

and Figure 3.3), the injected samples into which the blends where injected, may very well be

equivalent to a part made in R-BDP. Typically R-BDPs‟ parts have small dimensions and simple

geometries, like a fork, a knife or even a tooth-brush and thereby similar to those of the samples.

Therefore and further on, the samples will be considered as parts representing a general product

made in R-BDP material and with identical dimensions to the samples. In the scope of Eng. Pedro

Teixeira‟s research, tensile, flexion and impact mechanical tests were made to the materials, which

implied having samples with different geometries. Those mechanical tests are out of this research‟s

3 MFI – Melt Flow Index at 190⁰C/2.16 kg

31

scope. However, the same two samples were considered for this work, as if the two geometries were

two components for a final product.

Figure 3.2: Sample for tensile tests (185x21x4 mm) Figure 3.3: Sample for impact/flexion tests (132x13x6.5 mm)

3.1.3 Injection moulding process characterization

The tests were run and the samples were injected at U. Minho using the equipment shown in

Figure 3.4. Characteristics of that equipment are presented on Table 3.2

Figure 3.4: Injection equipment used in tests at U. Minho

Table 3.2: Characteristics of the injection equipment used for the tests at U. Minho

Several tests were made varying the conditions of injection in order to establish the best

injection parameters that assured acceptable quality of the injected samples. Among the injection

Injection machine - Ferromatik Milacron K85D-S/2F

Installed power 58 kW

Clamp force 85 ton

Temperature controller - PIOVAN TP6

Installed power 6 kW

Max. Temperature 140 ⁰C

32

parameters that permitted to obtain sound parts, it was chosen the ones that minimize the injection

cycle time. Figure 3.5 and Figure 3.6 shows photos from the samples injected at U. Minho:

The cycle time obtained, material input, and final part mass for each sample are presented in

Table 3.3. Despite of the injection machine being equipped with two screws, only one was used, for

that reason, from now on it‟s considered the machine having an installed power of 26 kW instead of 58

kW. This information will be important later on this thesis when accounting the consumed energy on

the injection moulding process.

Material Quality Inj.

Press [bar]

Hold. Press [bar]

Inj. Temp [⁰C]

Warming time [sec]

Cycle time [sec]

Part mass

[g]

Wastes [g/cycle]

Mat. input

[g]

10/90 10%PLA+90%STA 59.50 39.00 100 521.74 48 27.00 0.32 27.32

40/60 40%PLA+60%STA 59.75 38.75 140 730.43 46 28.80 0.35 29.15

80/20 80%PLA+20%STA 60.00 37.71 140 730.43 41 28.13 0.34 28.46

90/10 90%PLA+10%STA 59.50 39.00 140 730.43 41 29.25 0.35 29.60

PP - 30.92 19.92 230 1200.00 29 20.36 0.24 20.61

Table 3.3: Injection variables

For a mould and a part with these characteristics, the warming time to inject PP at 230ºC is

about 20 minutes, thereby for the R-BDPs the warming times are the ones presented in Table 3.3. It‟s

clear that R-BDPs don´t require such higher injection temperature as PP and therefore the necessary

time for the machine to warm up is also lower for these materials. The reason why 40/60, 80/20 and

90/10 present the same warm up time is caused by the three blends having the same recommended

injection temperature.

Because of the defective parts (such as burned parts or excessive burrs) usually arising from

the injection moulding process, it was considered 1.2% of material wastes (according to FAPIL). The

Figure 3.5: Injected samples Figure 3.6: Injected 80/20 sample

33

values for each part‟s mass where calculated based on the mould‟s cavity volume and on each

material‟s density. To obtain the amount of injection material necessary it was added the amount of

wastes per cycle to the part‟s mass.

The setup times of injection will vary according to each material due to its different recommend

injection temperatures and consequently warm up times. Before injection process is done, it‟s is

necessary to prepare the injection mould. This mould preparation implies several operations such as

fitting the mould in the injection machine, cleaning up wastes from previously jobs, lubrication, etc. It´s

assumed that for a mould with these characteristics, this operation takes about 30 minutes to

complete. In Figure 3.7 are shown the setup times for each plastic, which accumulates the mould

preparation time with the warm up time.

Figure 3.7: Setup times of injection [min]

The injection cycle times obtained for each plastic are different depending on the particular

plastic properties‟ (Table 3.1). In particular, Table 3.4 reveals that R-BDPs have greater injection

cycles compared to PP and that greater concentration of STA lead to increased cycle times.

Material Quality Cycle time [sec]

10/90 10%PLA+90%STA 48

40/60 40%PLA+60%STA 46

80/20 80%PLA+20%STA 41

90/10 90%PLA+10%STA 41

PP - 29

Table 3.4: Injection cycle times [sec]

These R-BDPs with high STA content have bigger differences between injection and ejection

temperatures ( , which demand longer time to cool down the part to a safe

temperature of extraction, in order to avoid defective parts, in particular, burned parts. Therefore these

34

materials need longer injection cycles than ones having smaller gaps between injection and ejection

temperatures.

35

3.2 Purpose of the study

The purpose of this analysis is to compare the 4 different R-BDPs with the PP in three

different but complementary dimensions (economical, environmental and functional) following a life

cycle approach. The proposed LCE model allows to fully understanding the comparison of R-BDPs

with a well-known plastic, supporting informed material selection decisions.

The first stage of the LCE model proposed in this study (Figure 3.8) is to define the boundaries

of the problem under analysis and to collect all necessary data for products life cycle stages,

concerning production, in-use and disposal costs, and all emissions and consumptions occurred. This

is a crucial phase for the integrity of the analysis, as data accuracy is the key to obtain reliable results.

Figure 3.8: Overview of the LCE model

The next step is to evaluate individually the product from an economic, environmental and

functional point of view allowing a global comparison. These evaluations use distinctive methods. For

each evaluation a specific process-based model was built, consisting in arithmetical algorithms

embedded into modular spread sheet, to allow systematic data input and results analysis. Economical

and environmental evaluations are performed from a life cycle perspective, using LCC and LCA

respectively. Functional evaluation is performed using a Multiple Attributes Decision- Making (MADM)

method and the Simple Additive Weighting (SAW) method, which allow a logical approach to fuzzy

problems [28].

36

For each material and for each dimension of evaluation (functional, economic, and

environmental) a single indicator is obtained, allowing the direct incorporation of the functional,

economical and environmental performances into a multi-criteria decision problem. The final result is a

global evaluation, presented in a ternary diagram, clearly showing the possible choices according to

the importance given to the three dimensions of analysis. This ternary materials selection diagram

illustrates the „„best materials‟‟ for different criteria weights. In fact the ternary diagrams identify not

only the best materials according to a set of weights attributed to functional, economic, and

environmental dimensions, but also the range of weights of each „„best material‟‟. In addition,

considering that some assumptions had to be taken along the performance analyses of R-BDPs, a few

sensitivity analyses were performed in order to evaluate the influence of such assumptions in the final

result. The utilization of process based models permitted changing variables such as production

volume, End of Life (EOL) scenario or part‟s geometry, extending the knowledge of each material

domain space.

3.3 Identification of the plastic materials life cycle stages

In this section it is presented the life cycle of plastic parts, with all the data and key processes

of each life cycle stage to use on the models of analysis to be developed later on this thesis. Figure

3.9 represents the life cycle of a generic plastic part, divided in 5 main stages, from raw material

acquisition to end of life. Bearing in mind the type of products on which the analyses are based on

(disposable and of brief usage), the use stage will not be analysed since costs and environmental

impacts caused by it can be neglected.

Figure 3.9: Life cycle stages of generic plastic parts

A detailed analysis of the inflows and outflows of each life cycle stage is done along with the

presentation of the developed economical and environmental models.

37

3.3.1 Raw material acquisition

Raw material acquisition is related to the corn growing and harvesting for the case of the R-

BDPs and with the extraction of oil or natural gas for PP.

This stage will obviously differ from the R-BDPs to the FoP as different amounts of energy will

be consumed and different amounts of emissions will be produced.

3.3.2 Plastics processing

Plastics processing stage concerns to the addition of additives to improve materials‟

properties. In the case, PLA is added to improve STA‟s water sensitivity and low mechanical

properties and consequently enriching R-BDP blends.

3.3.3 Plastic parts manufacturing

In this stage it is considered an input flow of energy to manufacture the plastic parts. This

energetic consumption promotes an outflow of emissions. There‟s also a mass stream input which has

its origin in the previous stage of Plastics Processing. There may be also another mass stream input

that comes from the process of plastics recycling, but only in the case of PP parts. As it ‟s explained on

the next section, only PP parts may undergo a plastic recycling process.

All the parts are manufactured by injection moulding process. Apart from the differences on

the amounts of energy and mass necessary to produce each one, the process is the same, as well as

the mould used to perform the manufacturing process.

3.3.4 End of life: final disposal options

As previously said in chapter 2 of this thesis, there are different waste treatment methods

available for plastics at End of Life, being composting the preferred method for R-BDPs and

mechanical recycling for PP, as they seem to be the best alternatives, regarding the climate change

potential, depletion of natural resources and energy demand [8]. Landfill appears as the worst disposal

method for all plastics [3] [7].

In this study 4 different scenarios of disposal were assumed: an ideal scenario, a worst case

scenario and two intermediate scenarios. These different possibilities of disposal were chosen in order

to assess the impacts on costs and on environment that a final disposal option has on the material life

cycle.

38

Scenario 1 (S1): this is an ideal scenario of disposal. It is assumed that selective collection of

Biodegradable Urban Waste (BUW) is available for R-BDP parts and that PP parts are capable of

being mechanically recycled, meaning that the parts are shredded into pellets or granulates and serve

as new raw materials. This corresponds to the usual definition for recycling [8]. It is also assumed R-

BDP parts are properly labelled and that population does the separation of domestic wastes.

Figure 3.10: Ideal scenario of plastics disposal (S1)

Scenario 2 (S2): first option of an intermediate scenario. It‟s assumed that R-BDPs are not

selectively collected; instead, they take the Solid Urban Waste (SUW) path and go to landfill. As in the

previous scenario, PP parts are recycled.

Figure 3.11: 1st

intermediate scenario of plastics disposal (S2)

Scenario 3 (S3): second option for an intermediate scenario. R-BDP parts treated as BUW,

PP parts are treated as SUW, ending up at landfill.

Figure 3.12: 2nd

intermediate scenario of plastics disposal (S3)

39

Scenario 4 (S4): worst case scenario. In this scenario none of the materials are selectively

collected and all end at the landfill.

Figure 3.13: Worst scenario of plastics disposal (S4)

Assuming these 4 options for final disposal, an economical and an environmental analysis will

be made in the next chapter in order to predict the impact on costs and on environment of each end of

life scenario.

40

3.4 Life Cycle Models

In this section the LCC and LCA life cycle models are applied to the selected plastic materials

to obtain the economic and environmental analyses of these materials in a life cycle perspective. The

aim of these analyses is to understand costs and environmental integrated impacts resulting from the

choice of a particular plastic.

3.4.1 Life Cycle Cost - LCC

The global approach of the LCC model to each material‟s life cycle stage is illustrated in

Figure 3.14. At each one of the life cycle stages, the LCC model uses the parameters to perform a

simplified life cycle inventory, considering only the relevant streams, crosses this information with

costs databases and retrieves a total stage cost. Gathering all stages it‟s possible to obtain the entire

life cycle cost.

The LCC model permits to change variables and test different situations to evaluate how these

changes may be reflected on the material‟s life cycle cost. For instance, it‟s possible to try out different

solutions in the manufacturing stage in order to reduce the final cost.

Figure 3.14: LCC model

41

Also note that despite of all parts being injected on the same mould, and so the mould won´t

create changes in the comparison of the materials life cycle costs, it will affect the absolute difference

of each alternative final cost. For that reason it was introduced the mould production cost on the LCC

model just to assess the parts‟ actual cost.

The total cost is divided in 3 main cost categories:

Materials costs: costs associated with materials consumption;

Process costs: costs related to the process, like equipment and labour costs;

Energy costs: cost related with the amount of energy consumed in each processes.

To begin, the LCC model is applied to an annual average production volume of 200,000 units,

distributed in batches of 25,000 units. The reader should note that in this study, a unit equals to the set

of the two samples injected.

3.4.1.1 Materials acquisition cost

The materials in comparison have different densities, so consequently the amounts of required

raw material will vary. Figure 3.15 shows the consumption of each material for the established

production volume.

Figure 3.15: Material consumption for 200,000 units

The costs of raw material acquisition and plastic materials processing stages are accounted

together on the materials‟ market price. Table 3.5 presents the acquisition cost per kilogram of the R-

BDPs and PP used in this study and the materials acquisition costs for the total production.

42

Material Quality Mat. input

[g/part] Consumption

[ton] Unitary cost

[€/kg] Acquisition cost

[€]

10/90 10%PLA+90%STA 27.32 5.46 2.64 14,427.07

40/60 40%PLA+60%STA 29.15 5.83 2.30 13,406.98

80/20 80%PLA+20%STA 28.46 5.69 3.12 17,760.60

90/10 90%PLA+10%STA 29.60 5.92 3.50 20,720.70

PP - 20.61 4.12 1.16 4,796.86

Table 3.5: Injection materials acquisition cost

Results from Table 3.5 show that the R-BDPs with higher concentrations of PLA more

expensive relatively to those with higher concentration of STA. In particular, 90/10 is the most

expensive and 40/60 the less expensive, among R-BDPs. As it was expectable, PP‟s cost is much

more inferior that R-BDPs‟. So it can be said that FoPs lower costs are still a great barrier to the

increasing on the utilization of plastics derived from RRM.

3.4.1.2 Mould production stage costs

As said in the previous chapter, all plastics were injected using the same mould. Still, the

mould‟s cost will be reflected on the part‟s final life cycle cost and for that it becomes important to

introduce the mould‟s variables and its cost distribution.

Table 3.6: Injection mould variables

The variables referred in Table 3.6 are the only information available for the mould production

stage. Nevertheless, regarding the moulds characteristics and the type of production that it is made

for, it is possible to predict the mould production costs distribution based on literature [24] [45].

Figure 3.16 shows that raw materials (Steel) cost is the most significant in the mould‟s total

cost. It‟s also possible to perceive that only 2% of the cost goes for energy spent during mould‟s

production. This cost distribution may also be helpful to account the energy and materials impacts of

the mould production stage.

Material Steel P20 (AISI)

Material Density 7850 kg/m3

Material Cost 3 €/kg

Material Quantity 168 kg

Production Cost 3,500 €

43

Figure 3.16: Mould production costs estimated distribution

3.4.1.3 Plastic parts manufacturing stage costs

This is the life cycle stage where the materials take shape, when the plastic parts are made.

The section is divided in 2 subsections: in the first one the assumptions performed in cost accounting

are presented, as well as the formulas used to determine Energy, Equipment, Labour and Setup

costs. Although this last cost item is a part of the costs associated with Production facilities,

contributing to Labour and Equipment cost items, such it does not appear highlighted in Figure 3.14, it

was decided to analyse it separately from Labour and Equipment costs in order to access the setups‟

contribution to the injection moulding total cost. In the second subsection the manufacturing stage

costs for the production volume of 200,000 units are introduced.

3.4.1.3.1 Assumptions and formulas

To apply the LCC model to the injection process becomes necessary to collect several kinds

of information, such as: Time, Batch, Equipment, and Labour.

Time info: provides data about the required cycle time of injection and about the

equipment setup time;

Batch info: gives data about the number of batches and the production volume of each

one. Therefore, to obtain the total time of the manufacturing stage, the injection cycle

time has to be multiplied by the production volume of the batch and the number of the

batches multiplied by the setup time;

Equipment info: data about the injection equipment (machines and refrigerators) and

shredding machine;

Labour info: information about the kind of operator required and its occupation during

the process.

Following the formulas used and the assumptions made to obtain the injection process costs

are presented.

44

Energy costs

It was considered that all the electric energy used was under a medium voltage contract with

the Endesa Energia, S.A.

Equation 3.1

Where CE is the energy cost of the injection moulding process for the entire production

volume, PrEE is the cost of the electric energy, and Econs is the amount of consumed energy on the

injection moulding process for the entire production volume, given by Equation 3.2 as follows.

Equation 3.2

Where PV is the production volume considered and Ecycle is the amount of energy consumed

by the injection equipment during a cycle of injection. Usual approaches in this subject [28] [29],

estimate the energy consumption using a simple model as expressed in Equation 3.3

Equation 3.3

Where Pnominal is the nominal power of the injection machine and tcycle is the cycle time of

injection. However since only a fraction of the nominal power is used during the injection process,

results from that approach will retrieve higher consumptions than the real ones. Thereby, in this study

it will be used an approach based on an energy model that is expected to retrieve results closer to the

reality. This model is being developed by Inês Ribeiro in her PhD research work. The model,

schematized on Figure 3.17, has two major components: a first one, based on a theoretical

thermodynamic model existing in literature [46] [47], and a second one based on empirical

considerations.

Figure 3.17: Injection machine energy consumption model

45

The thermodynamic component states that the thermodynamic energy required to melt and

inject the material into to mould can be described as Equation 3.4

Equation 3.4

In theory, the energy required to melt the polymer can be obtained through the fundamentals

of thermodynamics, which depends on the crystallinization degree of the polymer (Equation 3.5).

{

(

(

Equation 3.5

Where m is the mass of the injection shot; cp is the specific heat of plastic; Tmelt is the melting

temperature of the plastic and Tambient is the ambient temperature; is the degree of crystallization;

and HF is the heat of fusion for a 100% crystalline polymer.

The energy to fill the mould and runner system occupied by the melt can be obtained by

integrating the instantaneous pressure p at each volume increment V. Although it varies with the wide

array of mould and part geometries, it can be estimated in a simplistic way by multiplying the average

injection pressure ̅ by the volume of polymer injected Vinj (Equation 3.6).

∫ ̅

Equation 3.6

The empirical component of the model proposed by Inês Ribeiro, adds to the thermodynamic

component, regarding the melting and filling the plastic, a second component allocated to the

energetic consumption contributions of the temperature controller and of the machine during the part

cooling. Depending on the part thickness, the cooling time of an injected part is usually the main

element of the total cycle time. Hence, during the cycle time there is a significant time period in which

the machine is basically in idle-like state, with the temperature controller working. Therefore, the

proposed approach to the energy estimation can be expressed as in Equation 3.7.

( ̅

( Equation 3.7

Where is the cooling time, is the machine power during the cooling period,

is the average power consumption of the temperature controller, and is the

efficiency index regarding the machine‟s energetic losses.

46

In order to assess the accuracy of the proposed energy estimation model, it was developed an

investigation work under the scope of Inês Ribeiro PhD research work. The author of this thesis also

participated in data collection and analysis. The experimental procedure consisted in measuring the

energy consumptions of a hydraulic machine – Sandretto 300T –, available at FAPIL S.A., in the

process of injecting different parts with specific geometries and injection parameters. The machine

power consumption was measured for 2.5 hours, from start-up through the idle phase and finally

during part production. The characteristics of the measuring equipment and injection machine are

available in Annex 7.3.

It were analysed three different parts, differing mainly on the surface area, on the thickness

and on being mono or bi-material. Table 3.7 presents the main properties of the parts measured

during its production and also the number of cavities of the mould. Notice that part 1 is bi-material, part

2 is a very thick part compared with the others, requiring a long cycle time in order to cool the part and

finally part 3 has higher surface area.

Parts Part

number Material

Surface area [cm

2]

Thickness [mm]

Number of

cavities

Average injection

pressure [bar]

Cycle time [sec]

Shovel 1a PP 41.4 2

2 20 31.2 1b Rubber 744.3 2

Brush 2 PP 78.0 20 4 20 59.0

Box cover 3 PP 1530.0 2 1 70 19.9

Table 3.7: Measured parts and mould properties

The experimental results were then compared with the values obtained through the

thermodynamic/empirical model (Equation 3.7) and with the simple model (Equation 3.3). According to

the results presented in Table 3.8, the simple model approach is clearly inaccurate. Despite a low

accuracy in the part 3, the proposed thermodynamic/empirical model is incomparable more accurate

than the simple model, therefore it may be a good approach to follow in this case study. Nevertheless,

this model may still be improved during the research works of Inês Ribeiro.

Accuracy

Part Cycle time [sec]

Simple [kJ]

Thermo/emp.[kJ]

Experiment. results [kJ]

Simple Thermo/emp.

∆ [kJ] ∆ [%] ∆ [kJ] ∆ [%]

1 - Shovel 31.2 1659.84 325.67 308.23 1351.61 439% 17.44 6%

2 - Brush 59.0 3138.80 713.41 718.38 2420.42 337% -4.97 -1%

3 - Box cover 19.9 1058.68 319.65 410.82 647.86 158% -91.17 -22%

Table 3.8: Comparison of values for energy consumption using the simple model and the thermodynamic-empirical model with the experimental data

47

Equipment costs

Table 3.9 shows the acquisition cost of the equipment assumed to perform the injection

process, which is the one where the parts were injected at U. Minho. Further on this thesis, it will be

made a sensitivity analysis to assess the impact on costs when choosing different injection equipment.

Reference Installed power [kW] Acquisition cost [€]

Machine - Ferromatik Milacron K85D-S/2F 26 70,000

Temperature controller - PIOVAN TP6 6 10,000

Table 3.9: Injection machine variables

The Equation 3.8 [48] allows calculating the machine hour cost by means of dividing the

annual cost of the machine based on the annual equivalent rental cost of the machine over its lifetime

(residual value of the machine is considered null), by the machines‟ annual working hours.

* ( (

( )+ ( )⁄ Equation 3.8

Where, Cpr is the machine investment, i is the opportunity cost and n is the equipment‟s useful

life. In order to obtain the injection machine cost for the production volume, it‟s necessary to multiply

Cmac by the injection cycle time and for the production volume, affected by the setup times.

For the PP‟s injection process case, it is assumed that the wastes resulting from the injection

process may be shredded and re-enter the cycle as raw material. So the shredded PP is added to the

injection materials cost as a profit (negative cost). On the other hand, the shredding costs related with

labour, machines and energy will increase the injection process costs. Table 3.10 shows the variables

of the shredding machine.

Reference Installed power [kW] Capacity [kg/h] Acquisition cost [€]

PLASMAQ 80 280 25.000

Table 3.10: Shredder variables

The shredding machine hour cost and labour hour cost was calculated using Equation 3.8 and

Equation 3.10, respectively. To determine the shredder machine cost, and the labour cost related with

the shredding process, it becomes necessary to multiply these two factors by the shredding process

time, which is:

Equation 3.9

48

Labour costs

In order to calculate the labour hour cost Equation 3.10 [48] is used:

(

Equation 3.10

Where Mmonthly is the average wage including benefits, Ns is the number of wages per year, Sc

are the social costs, dyear is the number of working days per year and hday is the number of productive

hours per day. To obtain the production volume costs with labour, Cman comes multiplied by the

injection cycle time, by the production volume and by the operator percentage of occupation (Op%).

Setup Costs

The setup costs are obtained using Equation 3.11:

( Equation 3.11

Where Cmac is the injection machine hour cost, Cman is the labour cost per hour and tsetup is the

sum of the times for machine warm up and mould assembly. Considering the annual production of

200,000 units and batches of 25,000 parts per batch, it means that there are 8 setups.

3.4.1.3.2 Data collection

Table 3.11 summarizes the data collected and introduced in the cost model in order to

determine the injection moulding costs.

PV – production volume 200,000 units

Batch 25,000 units

PrEE – electric energy cost 0.07112 €/KWh

n – equipment‟s useful life 8 years

i – opportunity cost 15 %

Mmonthly – average wage 1,056 €

Ns – wages per year 14

Sc – social costs 23 %

dyear – working days per year 250-22=228

hday – productive hours per day 7

Op% – operator percentage of occupation 100%

ε melt, fill – inj. machine efficiency 80%

Pm.cool. – inj. machine power during the cooling period 2,5 kW

Ptemp.controller – temp. controller average power consumption 0.7125 kW

Table 3.11: Plastic parts manufacturing stage data

49

3.4.1.3.3 Injection moulding costs

The costs resulting from the injection moulding stage and for the referred production volume

are shown in Table 3.12.

Costs 10/90 40/60 80/20 90/10 PP

Setup 111.35 € 121.35 € 121.35 € 121.35 € 143.87 €

Labour 30,383.16 € 29,117.19 € 25,952.28 € 25,952.28 € 18,358.48 €

Energy 616.29 € 594.24 € 530.53 € 530.94 € 414.88 €

Equipment 27,166.49 € 26,034.55 € 23,204.71 € 23,204.71 € 16,413.64 €

TOTAL 58,277.28 € 55,867.34 € 49,808.88 € 49,809.28 € 35,330.87 €

Table 3.12: Injection moulding stage costs for 200,000 units in batches of 25,000 units

Results on Table 3.12 show that 10/90 is the material that has the most expensive production

cost, while in opposition, 80/20 and 90/10 present the lower production costs among the R-BDPs. It

may also be seen that PP presents a much lower production cost than R-BDPs. Hence, becomes

necessary to understand the contribution of each injection cost categories on the total injection stage

cost. Figure 3.18 and Figure 3.19 help to understand these cost distributions.

Figure 3.18: Injection stage costs distribution Figure 3.19: Injection stage costs

distribution in %

Despite of varying with the injection material, the injection costs are pretty much equally

distributed for every material, being the cost related with labour the most important with a 5%

difference for the equipment costs. As seen, the setup and energetic costs are practically negligible

when compared with the rest of the cost categories. The reduction on every cost category is evident

with the increase of PLA composition in the R-BDP blends, since R-BDPs blends with higher

composition of PLA have shorter injection cycle times, and for that require less labour and equipment

time of utilization.

50

Equipment costs are directly related with its time of utilization and of course with its investment

cost, but once it was used the same machine on the injection of all materials, becomes of interest to

analyse the machine‟s time with the injection costs. This can be made by relating the injection cycle

time of each plastic with the total injection costs. Figure 3.20 shows this relation.

Figure 3.20: Injection cycle time Vs. Injection and Raw material costs for 200,000 units

It´s now clear that the injection cost is largely influenced by the injection cycle time, since

materials with longer cycle times, present higher costs for this annual production volume. 10/90 has

the longer injection cycle time and because of that is the one with higher production cost.

As said before in this thesis, greater concentrations of STA demand longer injection cycle

times, so the more expensive parts to produce are the ones made of R-BDP materials with higher

amount of STA, although being the cheaper R-BDPs to acquire. The total life cycle cost assessment

will help to understand how these differences will contribute for the final cost of each material. That

evaluation will be performed after the End of Life stage analysis being made.

51

3.4.1.4 End of Life stage analysis

In this chapter the impact on costs for four different scenarios of disposal is assessed.

The costs related to collection methods and waste treatment processes used in the three

different possibilities of disposal (composting, recycling and landfill), as well as the revenues

generated by compost and products of recycling, are shown in the Table 3.13.

Cost [€/ton] Source

Collection

Selective collection of BUW 100 SPV

Selective collection of plastics (Ecopoints) 110 SPV

Undifferentiated collection of SUW 45 IRAR

Processes

Municipal composting 50 LIPOR

Plastics recycling process 300 GrijoTubos S.A.

Landfill fee 30 IRAR

Recycled products

Compost 4

90 LIPOR

Recycled PP 600 Daniel J. Morais S.A.

Table 3.13: Costs related to deposition methods (as provided by sources)

The Urban Wastes collection costs were provided by Sociedade Ponto Verde (SPV) and

Instituto Regulador de Águas e Resíduos (IRAR). Currently in Portugal there are only few entities

performing municipal composting of biodegradable wastes. After intensive research the only cost

value obtained was provided by LIPOR – Serviço Municipalizado de Gestão de Resíduos do Grande

Porto, so the cost presented on the previous table was the one used to continue with the analysis.

Same difficulties occurred to obtain the cost values of the plastic recycling process. Although there are

in Portugal several entities performing this process, most of them were very reluctant when come to

provide a cost value. The assumed value was the one given by GrijoTubos S.A which revealed to be

consistent with other values found on research and also with the selling cost value of recycled PP

given by Daniel J. Morais S.A.

Known the cost values related with the waste treatment, it‟s now possible to determine the

costs of each EOL Scenario for every plastic in comparison. So for the 200,000 parts that are

deposited after usage, the collection costs (selective collection of BUW, undifferentiated collection of

SUW or selective collection of plastics) are added to the waste treatment costs (municipal composting

process, landfill or plastics recycling process) and then the revenues generated from the recycled

products (compost or recycled PP) are subtracted, resulting on the total EOL cost (Equation 3.12).

4 Recommended selling price for LIPOR‟s compost Nutrimais, Hortas e Jardins

52

Equation 3.12

From Table 3.14 to Table 3.17 are presented the results of the EOL costs to each plastic in

comparison at each established scenario of final deposition.

Scenario 1

Table 3.14 shows the costs related with the ideal scenario of disposal (composting R-BDPs

and recycling PP).

Costs 10/90 40/60 80/20 90/10 PP

Collection 540.00 € 576.00 € 562.50 € 585.00 € 447.98 €

Waste treatment 270.00 € 288.00 € 281.25 € 292.50 € 1,221.75 €

Revenues 486.00 € 518.40 € 506.25 € 526.50 € 2,443.50 €

TOTAL 324.00 € 345.60 € 337.50 € 351.00 € -773.78 €

Table 3.14: S1 of EOL costs for 200,000 units

The main differences on costs shown in Table 3.14 rely on the differences of the materials‟

mass and obviously of the different path of disposal for PP. So the differences noted among the R-

BDPs are caused only by the differences on weight. The cost of plastics recycling is much higher than

the cost of municipal composting and that difference is clearly shown on the table. However, despite of

the recycling process being much higher than composting, the revenues generated from the recycled

plastic are also much higher than the ones resulting from the compost. The result is that for this

idealistic scenario, the disposal method for PP generates revenues on the part‟s life cycle cost.

Scenario 2

Table 3.15 presents the costs for the intermediate disposal option, with R-BDPs sent to landfill

and PP to recycling.

Costs 10/90 40/60 80/20 90/10 PP

Collection 243.00 € 259.20 € 253.13 € 263.25 € 447.98 €

Waste treatment 162.00 € 172.80 € 168.75 € 175.50 € 1,221.75 €

Revenues 0.00 € 0.00 € 0.00 € 0.00 € 2,443.50 €

TOTAL 405.00 € 432.00 € 421.88 € 438.75 € -773.78 €


Considering the R-BDPs as SUW, the costs resulting from collection and from landfill are

lower when compared to selective collection and composting process. However, this choice generates

53

no revenues, so the EOL cost of the R-BDPs becomes higher when compared to the ones resulting

from the BUW path.

Scenario 3

Second intermediate disposal option, with R-BDPs sent to composting and PP to landfill.

Costs are presented on Table 3.16.

Costs 10/90 40/60 80/20 90/10 PP

Collection 540.00 € 576.00 € 562.50 € 585.00 € 183.26 €

Waste treatment 270.00 € 288.00 € 281.25 € 292.50 € 122.18 €

Revenues 486.00 € 518.40 € 506.25 € 526.50 € 0.00 €

TOTAL 324.00 € 345.60 € 337.50 € 351.00 € 305.44 €


Data from Table 3.16 shows that collecting and composting R-BDPs costs much more than

collecting and landfilling PP, however because compost does generate revenues while landfill doesn‟t,

the result is that the final EOL costs reveal small differences to all the materials in comparison.

Scenario 4

This is the worst case scenario of disposal, on which it‟s assumed that all the materials in

comparison take the SUW path, ending up on landfill.

Table 3.17 shows the costs resulting from this choice.


The lighter PP parts cause costs of collection and landfilling smaller than those verified for R-

BDPs. Additionally, because there are no revenues generated to any plastics, the result is that PP

presents EOL costs around 40% less than R-BDPs.

EOL stage cost distribution items – collection, waste treatment method and revenues – vary

according to the waste treatment path chosen of composting, landfill or recycling, but are independent

of the disposal scenario. Figure 3.21 represents the cost items distribution for each waste treatment

path. Collection represents the larger part of the costs for the processes of composting and landfill,

Costs 10/90 40/60 80/20 90/10 PP

Collection 243.00 € 259.20 € 253.13 € 263.25 € 183.26 €

Waste treatment 162.00 € 172.80 € 168.75 € 175.50 € 122.18 €

Revenues 0.00 € 0.00 € 0.00 € 0.00 € 0.00 €

TOTAL 405.00 € 432.00 € 421.88 € 438.75 € 305.44 €

54

while for the plastic recycling process it represents only 11% once this last process is much more

expensive than composting or landfilling. The reader should also note the high revenues generated by

the recycled PP (59%). This profitable process is another reason for the still competitiveness of the

FoPs.

Composting Plastic Recycling Landfill

Figure 3.21: Deposition method related costs distribution

Figure 3.22 shows the total EOL costs of each plastic material in the different scenarios of

disposal. It‟s clear that PP is always more economic than R-BDPs whether the disposal option is, in

particular when the choice is recycling (S1 and S2), since its revenues will favour PP in the final LCC.

Concerning R-BDPs‟, composting (S1 and S3) reveals to be a more economic option than landfill (S2

and S4). Additionally, results also reveal that the ideal scenario of disposal (S1) is the preferred for

both types of plastics in terms of economics, in opposition to the worst scenario of landfill R-BDPs and

PP (S4) on which both present the highest costs.

Figure 3.22: EOL total costs for each scenario of disposal

The difference between EOL stage costs and plastic parts manufacturing stage costs is huge,

whatever the scenario chosen and the plastic in comparison. In fact, EOL stage costs are almost

insignificant when compared to manufacturing stage costs. However, the EOL stage must not be

55

undervalued, once the environmental impacts generated by each scenario of disposal haven´t been

accounted yet.

Nevertheless, the LCC analysis will proceed assuming the idealistic EOL scenario (S1), being

the preferred one for R-BDPs and PP, concerning the economics and as expected also concerning the

environment, thus contributing to foster a sustainable life cycle.

3.4.1.5 Economical assessment

To finish the LCC analysis, in this section it‟s presented the integration of all the life cycle

stage costs, considering the annual average production of 200,000 units. Note that because of the

reasons already stated the use stage is not accounted.

Results from Table 3.18 reveal that PP costs less than R-BDPs at all life cycle stages. In

material‟s acquisition stage, 40/60 is the less expensive material to acquire among the R-BDPs.

Although it doesn‟t presenting the less consumption of material, it has the lowest cost per unit of mass.

In the part‟s manufacturing stage – injection moulding – 80/20 and 90/10 have approximately the

same production cost and are the less expensive R-BDPs to produce, mainly due to its shorter

injection cycle time that is reflected on the equipment and labour costs. When it comes to final

disposal, R-BDPs present very similar costs, being 10/90 the most economical, once it requires less

amount of material to deliver the 200,000 parts.

10/90 40/60 80/20 90/10 PP

Materials acquisition

Raw Material 14,427.07 € 13,406.98 € 17,760.60 € 20,720.70 € 4,796.86 €

Recycled material 0.00 € 0.00 € 0.00 € 0.00 € -56.88 €

Sub-total (1) 14,427.07 € 13,406.98 € 17,760.60 € 20,720.70 € 4,739.98 €

Mould production

Mould's cost 3,500.00 €

Injection moulding

Setup 111.35 € 121.35 € 121.35 € 121.35 € 143.87 €

Labour 30,383.16 € 29,117.19 € 25,952.28 € 25,952.28 € 18,358.48 €

Energy 616.29 € 594.24 € 530.53 € 530.94 € 414.88 €

Equipment 27,166.49 € 26,034.55 € 23,204.71 € 23,204.71 € 16,413.64 €

Sub-total (2) 58,277.28 € 55,867.34 € 49,808.88 € 49,809.28 € 35,330.87 €

End of Life

Collection 540.00 € 576.00 € 562.50 € 585.00 € 447.98 €

Deposition method 270.00 € 288.00 € 281.25 € 292.50 € 1,221.75 €

Revenues -486.00 € -518.40 € -506.25 € -526.50 € -2,443.50 €

Sub-total (3) 324.00 € 345.60 € 337.50 € 351.00 € -773.78 €

LCC 76,528 € 73,120 € 71,407 € 74,381 € 42,797 €

Unitary cost 0.38 € 0.37 € 0.36 € 0.37 € 0.21 €

Table 3.18: Life Cycle Cost for 200,000 units

56

In conclusion, the combination of a short cycle time of injection with an average material

acquisition cost points out to 80/20 as the most economical R-BDP. The final costs also reveal that PP

is around 40% more economical than the average of the R-BDPs.

Figure 3.23 helps to understand the materials‟ life cycle costs distribution. As stated before,

the costs related with final deposition are practically insignificant. So becomes even more important so

asses the environmental impacts of the EOL stage. Mould production stage also takes only a minimal

part of the final cost, for this annual production volume. Further sensitivity analysis will permit to

access the evolution of this percentage with the variation on quantity of produced parts.

Figure 3.23: LCC costs distribution for 200,000 units

At this point it is possible to prove the assumption made before in this text that the contribution

of the injection moulding stage to the part‟s life cycle cost is the most relevant on the total life cycle

cost, representing between 66% and 82% of the costs for all candidate plastics. The spending on raw

material has proven to be the second most important cost category, representing between 19% and

28% for R-BDPs and 11% for PP. This difference may be explained by the initial lower cost of raw PP

and by the recovering of material by means of process wastes recycling.

To conclude this economical assessment, as Table 3.18 and Figure 3.23 indicate, 10/90 part

presents the highest cost and 80/20 the lowest, among R-BDPs. It´s also clear that R-BDPs present

much higher costs when compared to PP. From the costs distribution it has been proved that the

injection moulding process represents the most important parcel of the life cycle costs.

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3.4.2 Life Cycle Assessment - LCA

At this stage, a cradle to grave approach to assess the environmental impacts of the several

candidate plastics is performed, using all data previously collected for the injected parts and

considering an annual average production of 200,000 parts. The proposed LCA model used to assess

the environmental impacts of each alternative life cycle is schematized on Figure 3.24.

Figure 3.24: LCA Model

The LCA methodology, earlier explained on this thesis, is composed by two main stages: the

account of the emissions produced and of the resources consumed during the product‟s life cycle

(LCI), and the impact assessment of these emissions and consumptions (LCIA). The Emissions Data

base indicated in Figure 3.24 refers to the emissions produced in two separate ways: emissions

generated on the production of raw materials and emissions generated on the production of each unit

of energy consumed during each process. With all the emissions and resources consumptions

aggregated into the impact categories, these are then weighted following a hierarchic/average (H/A)

perspective, which is a moderate perspective generally accepted by the scientific community,

attributing 40–40–20% of weight to the three considered impact areas, HH–EQ–R, respectively [30].

Afterwards, the scores are weighted into a single value (EI‟99).

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3.4.2.1 LCI

This section presents (Table 3.19) the main consumptions of material and energy at all life

cycle stages. However, before presenting the results, the system‟s boundaries must be introduced

(Figure 3.25) with a few related considerations. System‟s boundaries need to be defined in order to

tracking down all sources of energy or resources consumption and generated emissions for the

production of 200,00 units and, at the same time, to avoid collection of unnecessary data [49].

Figure 3.25: LCI boundaries

Mould material processing

Just like it has been made for the cost analysis, also for the environmental impacts analysis

the mould‟s contribution was taken in account, despite of all the parts been injected on the same

mould. The only available information about the mould‟s material is the material by itself (Steel P20)

and the moulds weight (168 kg). Knowing that the mould is composed not only by cavity and core, but

also by other components (as ejectors and guide pillars), it was assumed that the losses on raw

material recurring from the moulds manufacture are compensated by the other components weight.

So, to perform this analysis it was assumed 168 kg as the moulds raw material amount. This is a high

grade steel, characterized by having an average alloy content of 5% to 15%, composed mainly by

vanadium, chromium, nickel, tungsten, cobalt, and molybdenum. These alloying elements, in particular

nickel, define the environmental impact of the steel [50].

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Mould production

The most common mould productions comprises several processes, from milling, drilling,

fitting to, if necessary, electric discharge machining, which incorporate tools, lubricants, energy,

dielectrics and electrodes [49]. However, reports indicate that the majority of the impacts of mould

production are caused by the energy spent in the processes [24], [49]. So in this study only the

impacts regarding the energy‟s consumption and emissions, spent in the processes will be evaluated.

From the mould production costs distribution is known that 2% of the total cost goes to energy.

Admitting the same electrical energy cost already mentioned (0.07112 €/kWh), it‟s possible to

determine the energy spent on moulds manufacturing.

Plastics processing

To access the impacts of R-BDPs production it is necessary to access the impacts resulting

from the production of its components, STA and PLA. STA‟s production impacts accrue from the corn

consumption and also from the energy spent to extract the starch from the corn [6]. In the case of

PLA‟s production, the impacts accrue also from the consumption of corn, as from electricity and heat

energy, from natural gas, consumed to process the corn into PLA [4]. As far as the PP goes, it are

accounted the impacts generated to generate PP granulates, which is the type of PP usually used on

injection moulding processes.

Therefore, in order to evaluate the environmental impacts generated at this life cycle stage it‟s

necessary to account the amount of material needed for the production of 200,000 parts of each

material. Note that in case of PP, to the initial necessary amount of material it was subtracted the

recycled material re-entering the process from the shredding of plastic waste.

Plastic parts manufacturing – Injection moulding

In injection moulding processes, the majority of the produced environmental impacts accrue

from the energy consumed by the injection machines [49]. So, at this life cycle stage the total energy

consumed by the injection equipment was accounted, for each material‟s production volume.

Parts use

By the reasons already mentioned, the parts use stage generates no environmental impacts

so it won´t be assessed.

Parts End of Life

As referred in section 3.3.4 of this thesis, it was chosen an idealistic scenario (S1) for the

parts‟ EOL. Therefore, at this life cycle, it has to be accounted the impacts resulting from the

transportation of the waste to each specific waste treatment plant, composting for R-BDPs and

mechanical recycling for PP. Transportation impacts are determined assuming road transport with

40% load (European average including return) in 28ton truck for 10km (average distance to treatment

plant) [51]. The impacts from the composting process accrue from the consumption of energy in the

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process, from the fuel consumed by the equipment, from the generated emissions of NH3 and N2O

and from the avoided production of chemical fertilizers [52]. For the mechanical recycling it is

accounted the energy consumption and the emissions generated on the process but also the avoided

virgin material production [8].

Table 3.19 presents the main consumptions at each life cycle stages for the production of

200,000 parts. PP is the one that consumes less material. Among the R-BDPs, 10/90 and 90/10

present the lower and higher material consumption respectively. At the injection moulding stage, the

energetic consumption is directly related with the part cooling time and consequently with the cycle

time. Therefore, as the results from Table 3.19 indicate, the R-BDPs with higher content of STA have

bigger energy consumptions, since their lower melting points require to spend more time cooling the

part to a safe temperature of injection, increasing thereby their cycle time. Among the R-BDPs, 80/20

appears as the plastic that requires less energy to the injection process. Results from Table 3.19 also

refer the amount of material that ends up in waste treatment plant. For the R-BDPs‟ case it concerns

to the accumulation of the amount of material from the parts in EOL with the amount of material

resulting from the injection process wastes that is also sent to waste treatment plants, while for PP‟s

case it only refers to the amount of material from parts in EOL, since the injection wastes are

shredded and reused in the injection process.

Life Cycle Stages Consumptions 10/90 40/60 80/20 90/10 PP

Mould material processing Material [ton] 0.17

Mould production Energy [kJ] 0.27

Plastics processing Material input [ton] 5.47 5.83 5.69 5.92 4.12

PLA [ton] 0.55 2.33 4.55 5.33 -

STA [ton] 4.92 3.50 1.14 0.59 -

Injection moulding Energy [TJ] 31.196 30.080 26.856 26.876 21.001

EOL Material [ton] 5.47 5.83 5.69 5.92 4.07

Table 3.19: Consumptions over materials' life cycle stages

Unitary impacts of material, energy, transport and waste treatment, were retrieved by

Simapro7.2 software and are indicated on Table 3.20. These values will be used in the following LCIA

analysis in order to obtain the impacts for the entire production volume of each plastic.

Eco Indicator 99 points

Mould material Energy

Steel P20 0.1110 pts/kg Medium voltage - PT 0.0123 pts/MJ

Parts materials

PLA 0.3060 pts/kg Waste treatment

STA 0.0629 pts/kg Recycling PP -0.2100 pts/kg

PP 0.3300 pts/kg Composting R-BDPs 0.0046 pts/kg

Transport Landfill PP 0.0596 pts/kg

Road, 40% load 0.0219 pts/tkm Landfill R-BDPs 0.0104 pts/kg

Table 3.20: EI'99 unitary impact values

61

3.4.2.2 LCIA

With the results obtained from the life cycle inventory, the overall impact for the 200,000 units

of each plastic type life cycle was calculated using the EI‟99 methodology. Starting from the mould‟s

material processing and finishing at the parts‟ EOL, each life cycle environmental impacts for all the

plastics in comparison are indicated in Figure 3.26.

Figure 3.26: LCA final results for 200,000 units (EOL scenario S1)

The results show that the life cycle of the FoP, PP, has lower impact on the environment than

the R-BDPs. Despite of registering relatively high impacts on the materials production stage, bigger

than 10/90 and 40/60, the main reason for the PP to have such smaller environmental impacts has to

do with the avoided new material that the recycling of the products in end of life permits and with the

smaller energy consumption during the injection process. Among the R-BDPs, 10/90 is the one that

registers smaller impacts and 90/10 the most environmentally damaging.

The arising impacts from mould production and mould material processing stages are

practically negligible on the overall impacts, while the injection moulding presents moderate impacts.

As expected, plastics processing and injection moulding stages have the strongest environmental

impacts, accounting 53% and 42% respectively, of the 10/90 life cycle impacts (Figure 3.27), being

this the R-BDP where these fractions are smaller.

Figure 3.27: 10/90's life cycle environmental impacts distribution

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At the plastics processing life cycle stage seems important to verify the existing relation

between the presence of STA and the environmental damages resulting from this stage. As Figure

3.28 indicates, the impacts decrease as the percentage of STA increases. That is, the larger is the

presence of the synthetic bioplastic PLA and more damaging the R-BDPs are to the environment.

Hence, at this life cycle stage, 10/90 reveals to be the most environmentally harmful and 90/10 the

least.

Figure 3.28: Plastics processing stage environmental impacts evolution with starch content

The results also show mechanical recycling as being the best alternative of waste treatment,

regarding the environmental preservation. As mechanical recycling avoids the production of new

material, by recovering used material which may be used to process new parts, the composting

process generates compost which may be a substitute for environmentally damaging chemical

fertilizers, but is a process unable to avoid the production of virgin material [8].

Table 3.21: EOL environmental impacts assessment for 200,000 units

LCA analysis clearly shows the influence that the plastics processing stage has on the final

results. Also the EOL waste management practices play an important role in the plastics‟

environmental performance (see Figure 3.29). In a global analysis and for the chosen EOL scenario

(S1), PP has smaller overall environmental impacts, mainly because of the avoided material that the

recycling process permits, but also because of the increasing impacts on materials production caused

by the growing presence of PLA on the R-BDPs composition. The very low presence of PLA on the

10/90 40/60 80/20 90/10 PP

Transport waste 1.197 1.277 1.247 1.297 0.892

Waste treatment process 25.198 26.878 26.248 27.298 -855.225

EI'99 End of Life 26.4 28.2 27.5 28.6 -854.3

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10/90 R-BDP turns it as the only R-BDP able to compete with PP in environmental impacts generated

during the part‟s life cycle.

Results from Figure 3.29 show the influence of the EOL scenario choice in the comparison

between R-BDPs and PP, as the plastics‟ environmental impacts hierarchy significantly changes

according to the EOL practice of recycling or landfill PP, being recycling the process that most favours

PP. Among the R-BDPs, the EOL options of composting and landfill produces small changes in the

overall LCA results.

Figure 3.29: LCA final results for all EOL Scenarios and production volume of 200,000 units

Concluding, it can be said that in a realistic scenario of final disposal (S4), in which all plastics

end at landfill, the majority of the R-BDPs in study present better environmental performance than PP,

while in a scenario of preferred practices (S1), PP present better profile than R-BDPs.

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3.4.3 Functional Assessment - FA

In this section the Functional Assessment of the plastics in comparison is presented. The

analysis, which follows the methodology illustrated in Figure 3.30, considers the most important

functions that must be performed by plastics and also its relative importance. This analysis stands out

from the economic and environmental analysis since this analysis is dedicated to the use stage of the

plastics‟ life cycle. Hence, for this analysis is required to define a specific group of typical applications

for R-BDPs manufactured by injection moulding process.

Figure 3.30: Functional Assessment methodology

Typical applications for R-BDPs made by injection moulding are usually disposable products

for domestic environment utilization. Among several possibilities of that kind of products, it was chosen

a group of 4 different products – including 2 packaging products (a food package and a liquid

container), 1 catering product (cutlery) and, 1 hygiene product (disposable tooth brush) – from which

were identified and selected the functions that must be performed by the plastics in comparison,

enabling to perform the Functional Assessment.

The functions were selected on discussion with users and fellow researchers and

complemented with research. They are:

Lightness – function related to the products‟ weight which will have effect on

transportation and handling;

Strength – function related with the products‟ capacity to resist to impacts and

handling and to do not degrade easily;

Eco-friendliness – this function regards the ability to cause less environmental impacts

but also as a marketing asset to appeal to buyers;

Appearance – this function is related to the visual aspect of the product, which is

always important when it comes to choose between similar products

65

Such functions have different levels of importance for the functional performance of the

products and this effect was modelled through the attribution of an importance weight. This attribution

might not be an easy task, especially if the functions are so unlike. In this case that task relied on the

users‟ expectations of performance for the selected products, which was assessed by means of a

public survey made directly to users. In this survey, based on pairwise comparisons of functions, the

respondents were asked to give a score of importance (0 - as important; 1 – weakly more important; 2

– moderately more important; 3 – strongly more important) to the more important function between a

set of two functions, repeating the process to all the 4 selected products. Table 3.22 shows an

example of a pairwise comparison from the survey related concerning the product Food container. As

seen the relative importance of each function is summed up to give each function score.

Product Food container

Lightness (A) Strength (B) Eco-friendly (C) Appearance (D)

Lightness (A) 0 B2 C3 A3

Strength (B) 0 B2 B3

Eco-friendly (C) 0 C2

Appearance (D) 0

Function score [points] 3 7 5 0

Function score [%] 20% 47% 33% 0%

Table 3.22: Example of a pairwise comparison from a survey

After gathering the information from the survey (in a total of 8 interviews), the ones presenting

results completely out of the verified trend were eliminated. Then with the remaining surveys it was

made an average of the each function‟s relative importance results in each product. Finally, the

relative importance of the functions was obtained from the average of each function considering all 4

products (Table 3.23).

Functions Weight [%]

Lightness 9

Strength 43

Eco-fiendliness 36

Appearance 12

Table 3.23: Functions’ weights of importance

The survey‟s results show that users tend to be more concerned with the Strength and Eco-

friendliness of disposable products rather than Lightness or Appearance.

The ability of a specific material to perform such functions, depends on its properties [27], so

the next step is to correlate each function to one or more properties of the candidate materials. For

each function a total of 15 points were distributed among the material properties, considering their

66

relevance to the function. It‟s assumed that Lightness is obviously greatly influenced by the material

Density but also by its Maximum Strength and Young‟s Modulus with an equal weight distribution

between these two last properties. The capacity to resist loading, given by Maximum Strength is the

property that most contribute for the products‟ Strength, leaving the materials‟ elasticity (Young‟s

Modulus) with the remaining contribution. Biodegradability assumes total influence on the function

Eco-friendliness and Appearance is scored directly.

Based on the functions‟ weights and on the properties scores, each material property

represents its importance to the plastics Functional Assessment. The analysis of Table 3.24 identifies

Maximum Strength and Biodegradability as the most important properties for the plastic products

performance. Hence, the ability of the R-BDPs to be biodegradable it‟s expected to have a major

contribution to the overall functional performance.

Product Functions

Weight [%]

Maximum Strength

[Mpa]

Young's Modulus

[Mpa]

Density [kg/m3]

Biodegradability Appearance

Lightness 9% 4 4 7

Strength 43% 10 5

Eco-friendliness 36% 15

Appearance 12% 15

Sum 100% 4.7 2.5 0.6 5.4 1.8

Weighting (%) - 31.1% 16.7% 4.1% 36.3% 12.0%

Table 3.24: Weights applied to the material properties

To complete all the required information to compare the functional performance of the plastics

in comparison is only missing to collect the values of each property. The values for Maximum Strength

and Young´s Modulus were collected from the flexural tests made to a series of samples (in the scope

of the research being made by Eng. Pedro Teixeira for his PhD thesis and kindly shared by him), in

which the best and worst results were eliminated and the considered value is the average of the

remaining results. Since the chosen material properties have different units, they had to be

adimensionalized in order to be compared. The adimensionalization is done attributing scores in a 10

point scale (1 for the worst material and 10 for the best) to each plastic property value. The evaluation

of Biodegradability is based on the plastics‟ content in PLA and STA. From the time biodegradability

tests already made by Eng. Pedro Teixeira, it‟s known that R-BDPs with higher presence of STA tend

to degrade faster, independently of the environment conditions. So the values were attributed

according to this variable and are already adimensionalized. As for Appearance, it was evaluated by

visual inspection of the injected samples and relies on the author‟s analysis.

Finally the adimensionalized value of each material property was multiplied by its importance

weight and then the overall result to each plastic was obtained by adding all the properties score

(Table 3.25).

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Material properties Weight [%]

10/90 40/60 80/20 90/10 PP

Maximum Strength 31.1% Value [Mpa] 6.17 19.77 34.30 32.21 24.84

Adimensional 1 5 10 9 7

Score 0.3 1.6 3.1 2.8 2.2

Young's Modulus 16.7% Value [Mpa] 409.02 1558.81 2559.98 2491.95 1605.54


Score 0.2 0.8 1.7 1.5 1.0

Density 4.1% Value [kg/m3] 1200 1280 1250 1300 905


Score 0.2 0.1 0.2 0.0 0.4

Biodegradability 36.3% Value - - - - -


Score 3.6 2.5 1.5 1.5 0.4

Appearance 12.0% Value - - - - -


Score 0.1 0.5 0.8 1.1 1.2

TOTAL SCORE

4.4 5.5 7.2 6.9 5.2

Table 3.25: Functional Assessment

Results from Table 3.25 reveal that the very good mechanical properties and Appearance of

the R-BDPs 80/20 and 90/10 significantly contributes to its high scores, being 80/20 the plastic with

the highest score. In opposition, despite of 10/90 presenting the best score for Biodegradability, its

poorer mechanical properties related functions left it with the lowest final score. When compared to R-

BDPs, PP revealed to have average scores in functions related to mechanical properties but its lack of

biodegradability placed it with one of the lowest final scores.

Figure 3.31 shows the final classification of plastics regarding the functional performance in

the use stage of the plastics life cycle.

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Figure 3.31: Plastics classification regarding the functional performance

To conclude the analysis, it can be said that R-BDPs with higher content in PLA have better

functional performance and that globally R-BDPs perform better than PP for the functions required to

disposable products, exception made for 10/90.

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3.5 LCE Model

After having made the three analyses, this section presents the global evaluation of the

selected plastics in study, leading to a decision diagram to support material selection. Furthermore,

some sensibility analyses are also performed in order to increase the domain knowledge of the

decision space.

3.5.1 Global evaluation

With the results obtained from the economic, environmental and functional performance

dimensions, an integrated and global evaluation can be performed. Once the outcome values from the

individual dimensions appear in different units, they were adimensionalized into a 10 point scale to

allow the attribution of importance weights (dimension weights). The adimensional values of each

alternative material, j, in the cost, i=1, and environment, i=2, dimensions of analysis, were obtained by

Equation 3.13

( )

Equation 3.13

Where aij is the adimensional value of the alternative (j) in the dimension of analysis (i) and Aij

is the absolute value of the alternative in the dimension of analysis.

Similarly, the adimensionalized values in the functional dimension (3) were obtained by

Equation 3.14

( )

Equation 3.14

The absolute and adimensional values of each alternative material in the three dimensions of

analysis are shown in Table 3.26:

10/90 40/60 80/20 90/10 PP

LCC Value [€] 76,528 73,120 71,407 74,381 42,797

Adimens. 5.6 5.9 6.0 5.8 10.0

LCA Value [EI‟99 points] 905.3 1350.3 1841.6 2045.5 782.7

Adimens. 8.6 5.8 4.2 3.8 10.0

FA Value [points] 4.4 5.5 7.2 6.9 5.2

Adimens. 6.1 7.6 10.0 9.5 7.1

Table 3.26: Adimensional values of the candidate plastics in the dimensions of analysis

To illustrate the existing possibilities regarding each dimension weights, a ternary diagram was

used (Figure 3.32). Each point on the diagram was determined according to Equation 3.15:

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(∑

)

Equation 3.15

Where j represents the alternative material, aij represents the adimensional values of the

alternative j, in the dimensions of analysis i (with 1-Cost; 2-Environment; 3-Functional), wi the weight in

each dimension of analysis( and P represents the point‟s coordinates.

The diagram illustrates not only the „„best material‟‟ for a particular set of importance weights

but also the domain of weights for each „„best material‟‟. Different combinations of weights might result

in a different „„best material for the application5‟‟ and a slight modification of such weights might deeply

modify this „„best material‟‟. For example, if the strategic goal is the economical aspect, then the

scenario required can be represented by point A, where a high weight is given to the economic

dimension (90%), a low weight is given to the functional dimension (10%) and a null importance is

given to the environmental dimension. For this scenario, the “best material” is PP. On the other hand,

if the strategy follows a more balanced concern between economical and environmental aspects, then

a good scenario could be characterized by point B, where 40% of importance is given to economic,

50% to environment and 10% to functional performance. This scenario is still under PP‟s domain of

“best choice”. Point C illustrates a more extreme strategy oriented towards the functional aspect, with

80% of importance given to functional dimension and the remaining 20% distributed equally between

economic and environmental dimensions. For this scenario, the “best material” is now 80/20.

Figure 3.32: Global evaluation of the plastics life cycle performance based on cost, environmental and functional criteria. Weight criteria: A – 90% Econ. Perf., 0% Envir. Perf., 10% Func. Perf.; B – 40% Econ.

Perf., 50% Envir. Perf., 10% Func. Perf.; C – 10% Econ. Perf., 10% Envir. Perf., 80% Func. Perf.

5 Note that in this case, “application” means a product made in R-BDP, like the ones used to perform the

FA analysis (section 3.4.3).

71

In this case study and according to the analysis, 80/20 and PP are the only two plastics

appearing in the ternary diagram. Therefore, whatever the set of weights chosen those are the

materials to consider for the application. The R-BDP 80/20 points out to a strategy associated to the

functional performance of the material, while PP points out to a strategy more concerned with

economic and environmental costs over the life cycle. As for the other R-BDPs analysed goes, they

revealed a worst performance than the others regarding the assumptions made in this study, since

none of them obtained overall results relatively good enough to exceed 80/20 and PP, whereby they

do not “show up” as alternatives in the final decision diagram.

As referred before in the EOL disposal options (section 3.3.4), the scenario of final disposal

chosen to perform the analyses, is an optimistic scenario, with consumers having good waste disposal

practices. However, these good practices unfortunately do not represent reality. Therefore, a global

evaluation considering a more realistic end of life cycle should be done. That evaluation is presented

along with other sensitivity analyses in section 3.5.2.2.

3.5.2 Sensibility analyses

Several considerations regarding production volume, injection equipment or EOL practices,

were made during the economic, environmental and functional analyses which lead to the decision

space presented on the global evaluation. Some sensibility analyses will now be performed with the

aim of increasing the domain knowledge of that decision space. Moreover, these sensibility analyses

also serve to verify the robustness of the life cycle models.

3.5.2.1 Changing the production volume

One of the advantages of the economic analysis using process based cost models, is to

assess the behaviour on life cycle costs with variations of the production volumes. Keeping the

assumptions made for the previous life cycle cost calculations, like EOL scenario, injection equipment

and labour, and changing only the annual production volume of 200,000 units, it‟s possible to estimate

the evolution of the life cycle cost with the variation on the production volume.

Figure 3.33 shows that PP is the most economical plastic whatever the production volume is,

and that the cost hierarchy among candidate materials remains the same for each production volume.

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Figure 3.33: Unitary cost variation with the production volume

The changing from a low production volume of 2,000 units to a medium production volume of

20,000 units results into a significant life cycle cost per unit reduction, which is verified in all plastics in

study. However the reduction on the final costs tends to stabilize as the production volume continues

to increase. Moreover, Figure 3.33 also suggests that the cost per part differences between PP and R-

BDPs tend to increase as the production volume increases. That fact is shown more clearly on Figure

3.34.

Figure 3.34: Variation of the difference in unitary costs from R-BDPs to PP with increasing production volume

Setting PP‟s part cost as the reference at every production volume, the difference of cost

percentage tend to grow as the production volume increases. This is, for lower production volumes, R-

BDPs present a cost more similar to the PP. This difference increase is caused by the costs related

with the injection moulding process that have an uneven growth, in particular, due to the injection

73

cycle times and required additional setups of each production batch. Note that the costs diversion is

more accentuated for the R-BDPs that require longer cycle times, which are the ones with greater

amounts of STA, like 10/90 and 40/60. That means that only the variable costs, or injection cycle time

dependent costs, are changing with the production volume‟s changing.

From this sensibility analysis to the production volume change, one may conclude that R-

BDPs are always more expensive than the PP whatever the production volume is. However, the cost

differences between R-BDPs and PP tend to reduce as the production falls to low and very low

quantities.

3.5.2.2 Changing EOL scenario – Effects on the environmental

impacts

Consequences on costs due to changing EOL scenarios were already presented at section

3.4.1.4. In this section it‟s intended to assess the consequences of those changes on the

environmental impacts. As seen earlier on the LCIA analysis of section 3.4.2.2, EOL waste

management practices play such an important role on the product‟s LCA. So, becomes of interest to

assess the effects that changing the EOL scenario will produce on the global environmental impacts

for the part‟s life cycle.

Since in the initial analysis it was considered the most optimistic EOL scenario (S1) regarding

consumers behaviour, the opposite scenario is now considered, the worst case scenario (S4), in which

all R-BDPs and PP end up at landfill. The other assumptions regarding the production volume

(200,000 units) and the injection equipment remain the same.

The results (Figure 3.35), attest the importance of final disposal practices. Comparing these

with the previous results (Figure 3.36) it is possible to see that PP appears now much more

environmentally damaging than most of R-BDPs, due to its worse behaviour in landfill. In fact

landfilling PP produces almost 3 times more environmental impacts than recycling. As for the R-BDPs

goes, the hierarchy on impacts remains the same, though landfilling generating more environmental

impacts than composting. Again and as expectable there is a trend of damage increasing with the

presence of PLA in the R-BDPs‟ blends.

74

Being landfill a more environmentally damaging waste management process than composting,

the impacts regarding the EOL represents now more 3% than previously, slightly reducing the

importance of the materials production and injection moulding impacts (Figure 3.37 and Figure 3.38).

Figure 3.37: 10/90's life cycle environmental impacts distribution for EOL scenario of Landfill

Figure 3.38: 10/90's life cycle environmental impacts distribution for EOL scenario of Composting R-BDPs and Recycling PP

It‟s clear with this sensitivity analysis that final disposal practices choices are crucial when

comparing the environmental performance of R-BDPs and FoPs, since it will define which type of

plastics will have a more “environmentally friendlier” behaviour.

The global evaluation, considering the sensitivity analysis performed, led to some changes

(Figure 3.39). When changing the final disposal to landfill, 10/90 appears now as an option for

moderate economic costs and medium to high environmental concerns. 80/20 is still the best choice

whenever the requirements are about high functional performance and the concerns with

environmental impacts are reduced. PP remains as the best option when the aim is all about reducing

costs.

Figure 3.35: LCA results for EOL scenario of Landfill

Figure 3.36: LCA results for EOL scenario of Composting R-BDPs and Recycling PP

75

Figure 3.39: Global evaluation of the plastics life cycle performance considering the EOL scenario of landfill R-BDPs and PP

Regarding today‟s society practices in waste management, this EOL scenario option (S4) is

more realistic than the EOL scenario chosen for the main analysis (S1), on which it was assumed the

best practices of final disposal leading to the preferred EOL waste treatment processes to each

plastics‟ type (composting to R-BDPs and recycling to FoPs). However, this EOL scenario option (S4)

results in a better global performance of R-BDPs, favouring R-BDPs in the comparison to PP, as the

ternary diagram shows (Figure 3.39) that in the decision domain appears now 2 R-BDPs as “best

options". Moreover, R-BDPs have also gained domain space over PP, as PP‟s domain is now much

smaller than it was in the initial diagram (Figure 3.32) resulting from the main analysis, on which was

considered the ideal EOL scenario (S1).

3.5.2.3 Changing part’s geometry

Previous LCA analyses have dictated the importance of materials production impacts on the

overall life cycle. This analysis is concerning about the model‟s sensitivity to changes in the part‟s

geometry and consequently in the amount of material required to produce the part. Note that,

changing the part‟s geometry is different of changing the number of parts injected as it is expected that

the differences on the energy spent during the injection moulding process are not linear and thus

causing changes in the environmental hierarchic ranking of the candidate materials.

The assumptions regarding the injection equipment and energy consumption calculation

remain the same as for the main analysis. In this sensitivity analysis the environmental impacts per

part for all the candidate plastics are evaluated according to the part‟s surface area for the EOL

scenario of composting R-BDPs and recycling PP (S1), as well as for the alternative scenario of

landfill all plastics (S4).

76

Figure 3.40: Evolution of EI'99 points per part with the surface area for EOL scenario S1

In fact, the differences on energy demand are so small that the impacts evolution with the

surface area almost linear. Results show that PP continues the trend of having smaller impacts than

R-BDPs with the surface area increasing, exception made for 10/90 which has very similar impacts to

PP. The environmental impacts hierarchy remains the same independently of the material volume

required and is still directly related to the presence of PLA, although the differences tending to enlarge

as the amount of material increases. Once again the importance of the material related impacts is

verified.

Similar conclusions can be made when changing the EOL scenario to landfill (Figure 3.41). As

registered in the main LCA analysis, PP is more environmentally damaging when sent to landfill than

most of the R-BDPs, despite of the differences tending to increase with the evolution of the part‟s

surface area.

Figure 3.41: Evolution of EI'99 points per part with the surface area for EOL scenario S4

77

So, it can be said that the increase of the part‟s surface area has no effect on the

environmental impacts hierarchic ranking of the candidate plastics whatever the EOL choice is

composting R-BDPs and recycling PP or landfill all, despite of the differences on impacts between

materials tending to enlarge with the required amount of material increasing.

As the previous analysis dictated, independently of the required amount of material, PP comes

favoured in the environmental performance comparison to R-BDPs because of the avoided production

of new material that recycling of thermoplastics delivers and because of the lower energy consumption

spent on the injection moulding process. Meanwhile, PP is known as a preferred plastic for plastics

injection moulding, since its intrinsic properties and processing parameters knowledge are long time

established and applied. So it may be of particular interest to change the FoP in challenge to the RRM

based plastics. In fact, the best R-BDP in the environmental dimension (10/90) is now compared to

other plastics more challenging to inject than the well-known PP. Therefore, for this new comparison it

were chosen 3 other FoP usually used in injection moulding process: Polycarbonate (PC), Polyamide

(PA) and Acrylonitrile Butadiene Styrene (ABS).

The environmental impacts resulting from the production stage of PC, PA and ABS were

calculated based on the energy consumption estimation given by the same thermodynamic theoretical

model referred on section 3.4.1.3.1, while for the EOL stage the environmental impacts were

calculated using each material EI‟99 values obtained from SimaPro; as for 10/90 and PP it were used

the same results previously calculated. Table 3.27 summarizes the values used to perform the

analysis:

EI'99 [pts/kg]

Plastic Production Composting Recycling Landfill

10/90 0.087 0.005 - 0.010

PP 0.330 - -0.210 0.060

PC 0.434 - -0.348 0.051

PA 0.904 - -0.818 0.063

ABS 0.400 - -0.314 0.050

Table 3.27: EI’99 points/kg of 10/90 and selected FoPs for production and EOL stages

Following the same approach of the previous analysis, the comparison is done by first

assuming the EOL scenario option of composting 10/90 and recycling FoPs, and secondly assuming

the EOL scenario option of landfill all plastics.

78

Figure 3.42: Evolution of EI'99 points per part with the surface area for EOL scenario of composting 10/90 and recycling FoPs

Regarding this EOL scenario option, Figure 3.42 shows that the avoidance of producing new

material continues to benefit some FoPs, like PC and ABS, as the surface area increases in favour of

R-BDPs. However, the results also show that even with the avoidance of producing new PA material,

the R-BDP 10/90 presents a better environmental performance than this last material and, the R-BDP

is even better when the amount of required material is bigger. Another important aspect of the results

from Figure 3.42 is related with PP‟s performance with the surface area. For low surface areas PP has

a better performance caused by its shorter injection cycle time and consequently less energy spent

during the injection process. As the surface area increases the amount of material also increases, so

the material‟s influence is higher in the environmental impact, once the impacts‟ component related to

the energy to melt the material has more influence than the component related with the cycle time.

Considering now the landfill option (Figure 3.43), the R-BDP presents much better

environmental profile than all the FoPs in comparison. Also, the differences tend to enlarge as the

part‟s surface area increases. Moreover, PP is actually the FoP from the ones chosen to perform this

sensibility analysis, with environmental impacts more closely to the R-BDP, confirming the assumption

made before, that this conventional plastic in particular is a very good challenger to test the

environmental life cycle behaviour of R-BDPs.

Figure 3.43: Evolution of EI'99 points per part with the surface area for EOL scenario of Landfill 10/90 and others

79

4. Conclusions

This research focused on comparing the performance in plastic injection moulding of

Biodegradable and Compostable Plastics based on Renewable Raw Materials (R-BDPs) with different

compositions regarding the amount of Starch (STA) and Polylactic acid (PLA). Most studies analyse

these materials in terms of environmental impacts, as R-BDP‟s are seen as possible Fossil Origin

based Plastics (FoPs) substitutes. However, nowadays decisions are multi-attribute, based also on

economical and technical performances. Additionally, a decision based only on price or environmental

differential between materials is not enough. In an industrial context, materials are used to

manufacture a part or a product and different materials mean different operating conditions or even

different processes during production. Moreover, materials may even imply changes in design in order

to meet technical requirements. In fact, this study enhances the need to go beyond material properties

and to analyse the whole product life cycle. And as previously stated, the life cycle evaluation of a

product using different materials is not sufficient by only looking at environmental impacts, being

necessary to evaluate the materials in terms of life cycle cost and technical performance.

In this thesis four different R-BDP‟s are analysed, differing in the amount of PLA and STA.

Whilst STA means lower environmental impacts to produce, PLA performs better during injection

moulding, leading to lower cycle time and consequently, higher productivity. The four R-BDPs are also

compared to a common FoP, in the case Polypropylene (PP), to evaluate the positioning of these

materials relatively to the conventional plastics.

Based on a Life Cycle Engineering (LCE) approach, the results obtained from the Life Cycle

Cost (LCC) and Life Cycle Assessment (LCA) methodologies, integrated with the Functional

Assessment (FA) analysis, allowed to perform a global evaluation of the materials in comparison. The

global evaluation consisting of a decision ternary diagram integrating all dimensions of analysis

enables to choose the “best material” according to the decision-makers strategies. Meaning that,

depending on the importance given to each analysed dimension, it‟s possible to select the material

that best suits the goals of selection.

Overall results shown that PP outcomes R-BDPs not only in the economic dimension but also

in the environmental dimension, in which dimension the R-BDPs were expected to perform better. In

fact, R-BDPs with higher content of STA, blend with 10% PLA and 90% STA (10/90) and blend with

40% PLA and 60% STA (40/60), proved to produce lower impacts than PP on their material

processing stage, but the final disposal option of recycling PP, in opposition to composting R-BDPs,

and consequently the avoided production of new material that recycling permits, favoured the FoP.

Therefore, the importance of life cycle analyses was verified. Nevertheless, the R-BDP material blend

with 80% PLA and 20% STA, (80/20), “shows up” in the decision diagram as the best choice when the

selection is done concerning functional/technical aspects.

80

Through the research it was assumed some considerations that may vary in a real situation or

in future conditions. In order to predict those variations and expand the knowledge domain of the

decision space, a few sensitivity analyses were ran. As these analyses demonstrated, the changing of

only one parameter value may change the entire evaluation and, consequently leading to different

choices. Therefore, it‟s crucial to perform a careful data collection in order to avoid wrong choices

based on false assumptions. In particular when adopting a more realistic End of Life (EOL) scenario,

with R-BDPs and PP going to landfill, R-BDPs revealed to be better choices than PP regarding the

environmental aspects, as the R-BDP blend with 10% PLA and 90% STA, (10/90), appeared then as

the “best material”. The material composed of 80% PLA and 20% STA, (80/20), remained as a good

choice in terms of functional requirements and as expected PP maintained the better scores regarding

economical strategies; contributing for that, its lower acquisition costs.

The utilization of the LCE approach allowed a global comparison and confirmed to be an

adequate philosophy to compare and select materials. Moreover, the possibility of making sensitivity

analyses has proven the robustness and flexibility of the process based models.

Finally, it‟s now possible to answer the questions made initially on the introduction and to

understand the real advantages of the materials labelled as eco-friendly. It has been proven that the

substantially higher economical costs of R-BDPs do not always compensate the environmental

advantages that they promote, being these directly correlated to waste management practices and

ultimately with consumers environmental consciousness. The yet higher manufacturing costs do not

permit the R-BDPs to compete for now with conventional plastics. Nevertheless, R-BDPs revealed to

be possible substitutes for conventional plastics in terms of functional/technical requirements.

81

5. Further developments

In this section a few suggestions to further developments in the area are made. Concerning

future researches in the comparison of R-BDPs performance through injection moulding process,

suggestions are:

A more accurate and detailed measuring of energetic and material consumptions

arising from the injection moulding process, will allow to obtain more realistic results of

the economic and environmental costs from the materials injection stage;

The access to better and more precise data regarding waste management collection

and treatment will permit to obtain more accurate results to the impacts on costs and

environment related to the life cycle stage of final disposal;

Despite the accuracy of the analysis made for the samples, in future it‟s

recommended to perform a study with a specific product in mind, to which decisions

will need to be taken earlier on the design stages to fulfil the product‟s desired

functions. Moreover, from the knowledge of the material‟s practical application will

accrue a more informed and detailed functional assessment analysis.

Regarding R-BDPs technology, also some suggestions are made:

The expected transition from the actual PLA‟s production technology to the next

generation of PLA, based on biomass and wind power and the consequent reduction

on environmental impacts will favour the substitution of conventional plastics, given

the importance of the impacts resulting from this life cycle stage;

An improved knowledge on the technology related to the manufacture of this type of

plastics, namely regarding the injection parameters, will certainly increase the

productivity as well as reducing the production costs.

82

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87

7. Annex

7.1 PLA production technology

PLA‟s production system used by Cargill Dow Polymers:

Figure 7.1: PLA manufacturing overview [4]

Today, the PLA life cycle starts with corn. All free energy consumed by biological systems

arises from solar energy that is trapped by the process of photosynthesis. The basic equation of

photosynthesis is:

→ (

In this equation, (CH2O) represents carbohydrate, primarily sucrose and starch. So, all the

carbon, hydrogen and oxygen in the starch molecule as well as in the final polylactide molecule have

their origin in water and carbon dioxide. After harvesting, the corn is transported to a corn wet mill

where the starch is separated from the other components of the corn kernel (proteins, fats, fibers, ash

and water) and converted via enzymatic hydrolysis into dextrose. Cargill Dow ferments dextrose into

lactic acid at near neutral pH. Via acidulation and a series of purification steps the lactate salt

fermentation broth is then purified to yield lactic acid. The first generation of PLA will be produced from

88

the annually renewable resource corn, the cheapest, starch - rich and most widely available raw

material in the USA. In other parts of the world, locally available crops such as rice, sugar beets,

sugarcane, wheat and sweet potatoes can be used as a starch/sugar feedstock.

There are two major routes to produce polylactic acid from the lactic acid monomer: direct

condensation polymerization of lactic acid and ring-opening polymerization through the lactide

intermediate. The first route involves the removal of water by condensation and the use of solvent

under high vacuum and temperature. With this route only low-to-intermediate molecular-weight

polymers can be produced, mainly because of the presence of water and impurities. Other

disadvantages of this route are the relatively large reactor required, and the need for evaporation,

recovery of the solvent and increased colour and racemization. Mitsui Chemicals developed a new

process based on direct polycondensation of l-lactic acid to enable the production of high molecular

weight PLA without the use of an organic solvent [4].

Cargill Dow uses the second route: ring-opening polymerization through the lactide

intermediate. In the first step of the process water is removed under mild conditions (and without the

use of a solvent) to produce a low molecular weight pre-polymer. This pre-polymer is then catalytically

depolymerised to form a cyclic intermediate dimer, referred to as lactide which is then purified to

polymer grade using distillation. The purified lactide is polymerized in a solvent free ring-opening

polymerization and processed into polylactide pellets. By controlling the purity of the lactide it is

possible to produce a wide range of molecular weights.

89

7.2 Technical data sheets of materials

Table 7.1: Material properties for the energy model

7.3 Equipment used in the experimental work of injection machines’

energy consumptions measuring.

Manufacturer Chauvin Arnaux Model Qualistar CA8334B Source FAPIL S.A.

Table 7.2: Power measuring equipment

Plastic Cost [€/kg]

Density [kg/m3]

Pressure [bar]

Pressure [kg/m2]

Cp [J/kgK]

Tmelt Tamb Cristalinization

degree

Heat of fusion [kJ/kg]

10/90 2.64 1200 39.00 397,683 510 100 23 11.70% 87.92

40/60 2.30 1280 38.75 395,133 510 140 23 11.70% 87.92

80/20 3.12 1250 37.71 384,572 510 140 23 11.70% 87.92

90/10 3.50 1300 39.00 397,683 510 140 23 11.70% 87.92

PP 1.16 905 19.92 203,090 2000 230 23 39.00% 100.50

PC 1.87 1070 20.00 203,940 1400 280 23 0% 180

PA 2.75 1470 20.00 203,940 1600 275 23 60% 130

ABS 1.87 1060 20.00 203,940 1500 180 23 0% -

90

Manufacturer Sandretto

Model SN 300T

Clamping unit kN 3000

Screw Diameter mm 55

Screw Length L/D 20

Calculated Shot Volume cm3 659

Pressure on Material bar 1968

Pressure on Material with regenerative bar 1640

Max injection capacity cm3/s 245

Max injection capacity with regenerative cm3/s 294

Plasticizing rate (HDPE) g/s 41

Plasticizing rate (PS) g/s 52

Max screw speed Min-1

254

Max hydraulic motor torque Nm 1660

Hydraulic motor power kW 37

Heating Zones (+ nozzle) n 4 + 1

Total Heating Power kW 16,2

Mould Clamping Force kN 3000

Mould Opening Force kN 429

Min/Max. mould thickness mm 230 - 730

Clamping stroke mm 660

Platen size (H x V) mm 980 x 980

Tie-bars space (H x V) mm 665 x 665

Tie-bars diameter mm 120

Ejection force kN 59.6

Ejector stroke mm 250

Hydraulic circuit pressure Bar 195

Oil capacity l 465

H2O requirement (at 15oC) for oil cooling m3/h 0.27

Electric motor power kW 37

Total installed power kW 53.2

Total net weight Kg 17800

Table 7.3: Technical data of Sandretto 300T injection machine

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