CONTENTS · Tapioca starch production is recognised as one of the most important agro-industries to the Thai economy. Tapioca starch is extracted from the root of the cassava plant,

CONTENTS

INTRODUCTION

CHAPTER 1 NATIVE STARCH INDUSTRY IN THAILAND 1-1

1.1 BACKGROUND INFORMATION 1-1 1.2 MANAGEMENT OF ENVIRONMENTAL IMPACTS FROM

NATIVE STARCH INDUSTRY 1-5 1.3 BUSINESS PERSPECTIVES IN NATIVE STARCH INDUSTRY

IN THAILAND 1-7

CHAPTER 2 NATIVE STARCH PRODUCTION PROCESS

& MATERIAL FLOWS 2-1

2.1 NATIVE STARCH PRODUCTION PROCESS 2-1 2.2 MATERIAL FLOW 2-6

CHAPTER 3 INTRODUCTION TO MIS APPLICATION 3-1

3.1 BACKGROUND 3-1 3.2 OBJECTIVES OF MIS APPLICATION 3-1 3.3 BENEFITS OF MIS APPLICATION 3-2 3.4 MIS PRINCIPLES 3-2

CHAPTER 4 APPLYING MIS PROCESS TO NATIVE STARCH

INDUSTRY 4-1

4.1 PRODUCTION PROCESS MODEL 4-1 4.2 DATA COLLECTION AND CONSOLIDATION 4-2 4.3 DATA PROCESSING 4-18 4.4 INFORMATION REPORTING & ANALYSIS 4-24

LIST OF TABLES

Table 1.1a Plantation Area, Production, Yield, Farm Price and

Farm Value of Tapioca in Thailand (1996-2005) 1-1 Table 1.1b Plantation Area of Tapioca in Each Province (2002 – 2005) 1-1 Table 1.1c Native Starch Factories in Thailand 1-3 Table 1.2a Examples of Eco-efficiency Improvement 1-5 Table 3.4a Suggested Tools for MIS Implementation with

their Pros and Cons 3-14 Table 4.2a Proposed Data Collection Scheme for Material

Preparation Section (Section#1) of

Native Starch Production 4-6 Table 4.2b Proposed Data Collection Scheme for Extraction and

Drying Section (Section#2) of Native Starch Production 4-9 Table 4.2c Proposed Data Collection Scheme for Wastewater

Treatment and Biogas System Section (Section#3)

of Native Starch Production 4-12 Table 4.2d Proposed Data Collection Scheme for Utility Section

(Section# 4) of Native Starch Production 4-15 Table 4.3a Management Information derived from

Data Processing 4-19 Table 4.4a Summary of Management Information 4-27

LIST OF FIGURES

Figure 1.1a Native Starch Factory Distribution 1-3 Figure 1.1b Location of Native Starch Factories in Thailand 1-4 Figure 2.1a Standard Native Starch Production Process 2-2 Figure 2.2a Material Flow of Native Starch 2-7 Figure 2.2b Material Flow of Water 2-8 Figure 2.2c Material Flow of Energy 2-9 Figure 3.4a General MIS Information Flow Diagram 3-8 Figure 3.4b Examples of Tools Used for MIS Process 3-13 Figure 4.1a Production Process Model for Native Starch Industry 4-4 Figure 4.2a Locations of Data Collection in Material Preparation (Section#1) 4-5 Figure 4.2b Locations of Data Collection in Extraction and

Drying Section (Section#2) 4-8 Figure 4.2c Locations of Data Collection in Wastewater Treatment

and Biogas System Section (Section#3) 4-11 Figure 4.2d Location of Data Collection in Utility Section (Section#4) 4-14

LIST OF ABBREVIATIONS

°Bè Beaumè

BOD Biological Oxygen Demand

°C Degree Celsius

COD Chemical Oxygen Demand

DIW Department of Industrial Works

ERP Enterprise Resource Planning

FTR Fresh Tapioca Root

GTZ German Technical Cooperation

GUI Graphical User Interface

ICT Information & Communication Technology

IPPCS Integrated Pollution Prevention and Control Strategy

IT Information Technology

KPI Key Performance Indicator

LAN Local Area Network

MIS Management Information Systems

MRP Manufacturing Resource Planning

MS Access Microsoft Access

MS Excel Microsoft Excel

NOx Oxide of Nitrogen

PEA Provincial Electricity Authority

PC Personal Computer

Department of Industrial Works MIS Guideline for Eco-efficiency Improvement

INTRODUCTION

The Department of Industrial Works (DIW) is implementing the project on

Management Information Systems (MIS) for Industrial Pollution Prevention

and Control Project, supported by German Technical Cooperation (GTZ).

Main objectives of the MIS Project are to establish environmental information

database at the DIW, to introduce an MIS for improving eco-efficiency of

selected industries, to make consultancy services available to industries

locally, and to establish public information centre on industrial pollution.

As part of the MIS Project, ERM-Siam has been commissioned to undertake

a study on “Elaboration of User Requirements and Capacity Assessment of

Palm Oil and Native Starch Industries”. The study results provide necessary

inputs for the design and development of MIS for enhancing competitiveness

and eco-efficiency for these two industries. One element of the study tasks by

ERM-Siam is to establish MIS guideline for improving eco-efficiency for palm

oil and native starch industries.

Scope of this guideline addresses the application of MIS for eco-efficiency

improvement for native starch industry. The principal objectives of this

guideline are:

• To allow management representatives of native starch factories to realise

the importance, principles and benefits of using MIS for improving

eco-efficiency and enhancing business competitiveness;

• To encourage native starch factories for collecting and analysing

eco-efficiency data, and making use of information to aide decision-

making of the management; and

• To provide introductory guidance for applying MIS for improving

eco-efficiency in native starch industry.

Contents of this MIS guideline comprise background information on native

starch industry in Thailand, standard production process and material flows,

MIS introduction, MIS principles and MIS application for native starch

industry.

Aim of the guideline is to support the development and implementation of

a meaningful MIS for improving environmental performance and

eco-efficiency in native starch industry.

For further information, please feel free to contact the Bureau of Water

Technology and Industrial Pollution Management of the Department of

Industrial Works, Ministry of Industry.

Chapter 1

Native Starch Industry

in Thailand


1-1

1 NATIVE STARCH INDUSTRY IN THAILAND

1.1 BACKGROUND INFORMATION

Tapioca starch production is recognised as one of the most important agro-

industries to the Thai economy. Tapioca starch is extracted from the root of

the cassava plant, which has an ability to grow in low-nutrient soils where

other crops do not grow well. Also, the cassava plant can tolerate drought.

Cassava roots can be stored in the ground for up to 24 months, and some

varieties for up to 36 months, thus harvest may be delayed until market,

processing, or other conditions are favourable.

Total area of tapioca plantation in Thailand as of 2005 was about 6.52 million

Rai, allowing the production of about 16.94 million tonnes of tapioca starch

(See Table 1.1a). The largest area of tapioca plantation in Thailand is in

Northeast of Thailand. The provinces with highest plantation areas are

Nakhon Ratchasima, Chaiyaphum, and Kalasin (See Table 1.1b).

Table 1.1a Plantation Area, Production, Yield, Farm Price and Farm Value of Tapioca in

Thailand (1996-2005)

Year Planted

Area (rais)

Harvested

Area (rais)

Production

(tonnes)

Yield per

Rai (kg)

Farm Price

(Baht per kg)

Farm Value

(Million

Baht)

1996 7,885,000 7,676,000 17,388,000 2,265 0.98 17,040

1997 7,907,000 7,690,000 18,084,000 2,352 0.71 12,839

1998 6,694,000 6,527,000 15,591,000 2,388 1.26 19,644

1999 7,200,000 6,659,000 16,507,000 2,479 0.91 15,021

2000 7,406,000 7,068000 19,064,000 2,697 0.63 12,010

2001 6,918,000 6,558,000 18,396,000 2,805 0.69 12,693

2002 6,224,000 6,176,000 16,868,000 2,731 1.05 17,712

2003 6,435,000 6,386,000 19,718,000 3,087 0.93 18,337

2004 6,757,000 6,608,000 21,440,000 3,244 0.80 17,152

2005 6,524,000 6,162,000 16,938,000 2,749 1.31 22,189

Source: Agricultural Economics Office, Ministry of Agriculture and Cooperatives, 2005 * 1 Rai = 1,600 Square metres

Table 1.1b Plantation Area of Tapioca in Each Province (2002 – 2005)

Region Plantation Area (Rai)

Tapioca Plantation

Location 2002 2003 2004 2005

Northeast Nakhon Ratchasima 1,320,722 1,353,734 1,396789 1,470,924

Chaiyaphum 358,051 388,228 417,591 348,,674

Kalasin 289,332 297,284 304,080 295,524

Khon Kaen 237,698 245,904 271,652 190,700

Buriram 173,076 179,305 183,123 194,149

Loey 129,807 142,203 171,667 132,955

Roi Ed 122,221 130,281 134,849 104,102

Udonthani 120,099 130,858 140,129 145,740

Mahasarakham 104,311 118,875 125,930 111,055

Mukdahan 85,233 90,352 92,671 102,953


1-2

Region Plantation Area (Rai)

Tapioca Plantation

Location 2002 2003 2004 2005

Ubon Ratchathani 70,954 75,067 79,803 68,765

Sakon Nakhon 63,529 65,093 70,498 66,689

Nongkhai 55,180 58,958 65,787 44,417

Sri Saket 43,566 47,711 51,379 53,344

Surin 42,381 43,137 45,981 36,757

Yasothorn 39,711 41,699 42,383 43,634

Nhongbualamphoo 36,121 38,629 51,481 38,566

Amnaj Chareon 31,289 30,558 34,619 31,411

Nakhon Phanom 16,465 16,570 18,649 12,270

East Chacheonsao 362,537 365,636 366,332 314,540

Chonburi 297,705 303,117 312,969 275,620

Chanthaburi 229,813 229,779 238,937 223,213

Rayong 209,628 215,918 213,540 227,046

Trad 7,212 4,128 3,676 -

Central Srakaew 339,090 345,873 362,728 356,914

Kanchanaburi 202,548 209,472 230,613 248,796

Uthaithani 150,217 161,622 171,827 179,084

Prachinburi 107,569 112,499 117,917 147,909

Ratchaburi 92,717 99,213 102,829 90,805

Chainath 63,571 66,498 74,394 68,993

Lopburi 55,956 63,328 78,108 89,828

Suphanburi 17,963 23,578 27,141 26,181

Saraburi 8,277 9,439 10,682 20,304

Petchburi 3,811 4,373 4,685 3,204

North Kampangpetch 348,648 323,531 330,985 371,145

Pisanuloke 185,341 186,705 183,599 147,337

Nakhon Sawan 146,614 154,807 164,506 188,277

Petchabul 22,695 25,253 26,884 21,482

Chiangrai 16,190 18,108 19,013 4,596

Uttaradith 4,798 5,181 5,553 11,102

Pichit 4,108 4,544 3,312 3,507

Nan 4,082 4,336 4,410 5,985

Prae 998 1,062 1,230 1,515

Tak 853 1,113 1,119 1,894

Sukhothai 560 622 624 823

Payao 383 434 460 538

Lampang 234 283 280 630

Source: Agricultural Economics Office, Ministry of Agriculture and Cooperatives, 2005

Tapioca starch industry in Thailand covers three types of production,

which are:

• Native starch production;

• Modified starch production; and

• Starch derivatives production.

According to the Information and Communication Technology Bureau of the

Department of Industrial Works, there are 85 native starch factories or 80% of

total tapioca starch factories. Northeast of Thailand has the highest number of

native starch factories (46%) followed by East (33%), Central (14%) and North

(7%) regions, respectively (See Table 1.1c and Figure 1.1a). Native starch

factories are typically located within the same areas as tapioca plantation, as

shown in Figure 1.1b.


1-3

The details of general information of native starch factories are provided in

Table 1.1c.

Table 1.1c Native Starch Factories in Thailand

Region Factory Location Number of Factory

Northeast Nakhon Ratchasima 20

Kalasin 8

Chaiyaphum 3

Khon Kaen 2

Mahasarakham 2

Udonthani 2

Roy Ed 1

Loey 1

East Rayong 11

Chonburi 10

Chachoensao 4

Chanthaburi 3

Central Uthaithani 2

Srakaew 2

Nakhon Pathom 1

Samutprakarn 1

Samutsakhorn 1

Kanchanaburi 1

Prachinburi 1

Ratchaburi 1

Lopburi 1

Saraburi 1

North Kampangpetch 5

Uttharadith 1

Total 85

Source: Information and Communication Technology Bureau, DIW (2005)

Figure 1.1a Native Starch Factory Distribution

East33%

Central14%

North7%

Northeast46%


1-4

Figure 1.1b Location of Native Starch Factories in Thailand

Source: Information and Communication Technology Bureau, DIW (2005)

Over 19 Factories

Nakhon Ratchasima

10 - 19 Factories

Rayong

Chonburi

1 –9 Factories

Kalasin

Chaiyaphum

Khon Kaen

Samutprakarn

Mahasarakham

Samutsakhorn

Udonthani

Kanchanaburi

Roy Ed

Prachinburi

Loey Ratchaburi

Chachoensao

Lopburi

Chanthaburi

Saraburi

Uthaithani

Kampangpetch

Uttharadith

Sakaew

Nakhon Pathom


1-5

1.2 MANAGEMENT OF ENVIRONMENTAL IMPACTS FROM NATIVE

STARCH INDUSTRY

Native starch production is characterised by its generation of substantial

amount of by-products. In regard to the manufacturing of tapioca starch,

associated environmental impacts occur due to material preparation through

washing, peeling, and starch extraction. Typically, a ton of starch production

generates approximately 10 to 20 cubic metres of wastewater with high

organic loading (BOD load ≅ 55 - 200 kg, COD ≅ 130 - 400 kg, SS ≅ 40 - 140 kg,

total Phosphorus ≅ 0.2 - 0.6 kg and total Nitrogen ≅ 3 - 10 kg). Solid wastes,

i.e. peel, tails, stalks and pulp, are also are generated from the production

process.

Good environmental management is necessary to ensure sustainability of

the native starch industry. To achieve reduced environmental impacts from

native starch production, the environmental management practice has to be

integrated in the production process management system and include efficient

use of natural resources.

1.2.1 Considerations for Improvements of Production Process

Losses in the production process can be avoided by, for example controlling

the performance of refiner and pulper during starch refining and pulp

pressing to minimise starch loss in process wastewater and pulp, respectively.

Using inefficient types of equipment, insufficient machinery and plan

maintenance (incl. leakages/spillages) are major sources of starch loss in

the native starch factories. This can be improved by the introduction of

preventive maintenance schemes ensuring that all equipment and machinery

is in good condition at all times.

Some examples of achieving improved eco-efficiency through various

processing steps are shown in Table 1.2a.

Table 1.2a Examples of Eco-efficiency Improvement

Processing

Step

Detailed

Step

Prevention and Control Results

Overall

Production

Process

Production

period

• Native starch production in average < 1 hour

• Minimise retention time by avoiding intermediate storage

• Implement continuous processing

•

• Minimising loss

of starch by

biological attack

Cleaning and batch production

• Control effective emptying reactors, tanks, pumps and pipes

• Avoid excessive rests of product in the system at the end of batch and before cleansing

• Avoiding starch

loss


1-6

Processing

Step

Detailed

Step

Prevention and Control Results

Product

quality

control

• Install closed processes to

avoid contamination of product

• Separate fruit water (which

promotes these reactions due to

its substrate content)

• Control the preparation and

usage of sulphur solution

• Cool warm end products

without condensation of

humidity on tank walls,

containers, pipes, etc

• Apply most hygienic process

conditions referring microbes

and avoiding easy degradable

substrate

• Preventing

enzymatic/

microbial attack

to the starch

during

processing

Raw Material Handling

- • Chop very large roots in half before processing to ensure correct peeling operation

• Process FTR in the delivered order to the factory

• Store FTR in bunkers, under roof and not on plan concrete floors

• Easy to extract

and provide

better quality

native starch

• Avoiding loss of

starch by aging of

the roots

• Avoiding loss of

starch by

increased

biological attack

to sun-warmed/

heated raw

material

Extraction/

Refining

- • Optimise disintegration of

roots (install and maintain high

quality rasper blades)

• Optimise and control counter-

current flow

• Prolong the equipment life

span by controlling the

efficiency of separation of sand

from roots (cyclone) and pulp

and all parts (magnetic

separator) before refining stage

• Maintain and control the

separating equipment

(checking, cleaning, repairing

sieves, cyclones, centrifuges)

• Maximising the

starch yield from

raw material

Drying and

Cooling

- • Maintain and control cyclones

filters and scrubbers; and

• Control the automatic air

regulator of the dryer.

• Ensuring

efficient starch

recovery during

drying and

cooling

Source: Environmental Management Guideline for Native Starch Industry (1997)

1.2.2 Utilisation of Native Starch By-products and Residues

Transforming the waste offers the possibility of creating marketable value-

added products. It is an incentive for managing waste streams. This strategy

can relieve some of the financial burden incurred by waste treatment, and


1-7

simultaneously reduce pollution burden to the environment. Typically, in

native starch production, solid residues consist of sand, tails, stalks, peel, and

pulp. Liquid residue is wastewater generated from native starch production.

Generated sand is typically disposed onto the cultivate land or is disposed

offsite. Tails and stalks can be sold and used as organic fertiliser and soil

conditioner, as it maintains humidity of the soil.

Peel and pulp are generally sold to animal feed mills or to local farmers as

these materials can be utilised as media for mushroom cultivation.

In addition, the peel and pulp can be used as organic fertiliser and soil

conditioner as they help to maintain the humidity of the soil.

Details of the integrated environmental management approach in native

starch production including the “Integrated Pollution Prevention and Control

Strategy” (IPPCS) are provided in the Environmental Management Guideline for

Native Starch Industry – Department of Industrial Works (1997).

1.3 BUSINESS PERSPECTIVES IN NATIVE STARCH INDUSTRY IN

THAILAND

Thailand is recognised as the largest exporter of tapioca starch in the world (1).

Annual production capacity has increased from originally hundreds of

thousand to three million tonnes, and is expected to reach four million tonnes

in the near future. The export volume has reached one million and eight

hundred thousand tonnes per year. The significant export markets of

Thailand are China, Taiwan, Japan, Malaysia, Singapore, Philippines and

Indonesia. Some countries in Latin America also showed more interest in

tapioca starch from Thailand.

Over the past decades, the number of starch factories has increased to respond to

customers’ demands, and consequently native starch industry is becoming more

competitive. To stay competitive, native starch factories are required to assure

product quality, to offer competitive product pricing, as well as to be productive.

In recent years several governmental agencies has provided supports to native

starch industry to relief this pressure; for instance, thru an active technical and

financial promotion of biogas system application, and introduction of cleaner

technologies.

1.3.1 Introduction of Biogas System

A biogas system has been recently introduced to most native starch factories,

as its application is proven to be economically viable. Process wastewater

from the starch production process is used as input to a system to generate

biogases mainly methane. Biogases are then used as fuel to burner generating

(1) http://www.thaitapiocastarch.org [Accessed on 25th November 2005]


1-8

hot air, which is used for starch drying process. By using a biogas system,

consumption of bunker oil decreases, and wastewater loads to the existing

wastewater treatment plant also declines. The application of biogas system

can contribute in significant cost savings to the factory and help conserve

the natural resources.

1.3.2 Eco-efficiency Improvement

Eco-efficiency improvement is one of the industry initiatives that can help

native starch industry to stay competitive. Factories can gain benefits from

eco-efficiency improvement concerning profitability, cost reduction, better

management of environmental risks and liability, and meeting requirements

by customers and government agencies. However, at present most native

starch factories pay more attention to management of raw material and

product than eco-efficiency improvement, as the importance and benefits of

data collection and analysis for eco-efficiency improvement has not much

been realised by the industry

Chapter 2

Native Starch Production

Process & Material Flows


2-1

2 NATIVE STARCH PRODUCTION PROCESS &

MATERIAL FLOWS

2.1 NATIVE STARCH PRODUCTION PROCESS

The principle of native starch production process consists of extraction of

starch from root cell using water as an extractor (which finally is separated

and/or evaporated); and utilisation of high-speed centrifugal separator or

other appropriate equipment to separate protein and other matters from

starch. Starch quality is dependent upon extraction of high purity starch.

A schematic flow diagram of the standard native starch production process is

shown in Figure 2.1a. The details of the production process are described in

following sections.

2.1.1 Reception and Storage of Tapioca Root

Tapioca roots are weighted and tested for starch content using the buoyancy

principle (under water weight). The test of root is conducted to assess

the starch content and estimate the price. The roots are normally processed

within 24 hours to avoid loss of starch content due to fast enzymatic and

microbiological attack.

2.1.2 Preparation of Tapioca Root

Dry Sand Removal

Tapioca roots enter the dry sand removal drum to remove sand, soil and outer

peel. The residue from this process is solely solid. The generated amount

depends on the conditions of weather and location. Typically, average

residue is 20 kg/ton of root. In practice, the dry sand removal process does

not completely eliminate all stalks and tails. Therefore, average amount 10 kg

of stalks and tails per ton of root are being removed at starch factory.

These residues are typically disposed offsite.

Peeling and Washing

Tapioca roots are conveyed through belts or lifters from the sand removal

drum to peeling and washing units. In the peeling process, fast rotating

propeller elevator segregates peels and other contaminants (i.e. residual sands,

stones and metals) from the roots. Water spray cleans roots. The removed

peels consist of the outer skin or corky layer. The peels are generally sold to

animal feed mills or sold as media for mushroom cultivation.


2-2

Figure 2.1a Standard Native Starch Production Process

Dry Sand Removal

Washing and Peeling

Chopping

Grinding

Fruit Water Separation (Decanter)

Starch Extraction

Starch Refining

Starch Dewatering

Starch Drying

Cooling and Bagging

Grid Chamber

Pulp Press

Biogas Plant

Wastewater Treatment Plant

Burner

Generator

Fresh Tapioca Root

Tails and Stalks

PeelWash Wastewater

Wet Sand

Fruit Water

Pulp

Sulphur Solution

Process Wastewater

Electricity (To be Used in

Production Process)

Bunker Oil

Emission

Hot Air

Native Starch

Biogas

Effluent

Pre-treated Wastewater

Biogas

Sulphur

Fresh Water

Fresh Water

Fresh Water

Recycled Water

Dry Sand

Sand

Sludge


2-3

2.1.3 Degrading (Root Disintegration)

Chopping and Grinding

Clean roots are passed onto the chopper through a chain conveyor or a rasp

bucket conveyor. At this stage, the roots are cut into small pieces of

approximately 1-2 inches to aid energy saving in the next stage of processing.

The chopped roots are then processed in a root rasper, in which the roots are

grinded into fine particles (mash of pulp, starch, fruit water etc.). Thus

chopping and grinding process help form a basis of starch extraction, in which

tuber cells are opened to release the starch granules and to obtain a high

starch yield.

Also, at this stage cyanic acid is dissolved along with fruit water from the

roots. The mechanical equipment therefore has to be made from high-grade

stainless steel to avoid formation of ferrocyanides (bluish colour formation in

starch).

Fruit Water Separation by Decanter (Optional)

After grinding, fruit water is separated from starch and pump using decanter

(this process is optional to the starch production). The tapioca root has water

content of around 60 to 70 % by weight. This liquid phase is called “fruit

water”. The fruit water contains water-soluble substances such as salts

(potassium), compounds of nitrogen and phosphorous, sugars etc.

Microorganisms and its enzymes degrade these substances in fruit water

resulting into new substances such as alcohols, organic acids.

These biochemical reactions exert a negative influence on the product quality

if these substances are not separated from starch and pulp.

To avoid generations of undesirable substances such as organic acids and

alcohols, some factories use decanter centrifuges to initially separate fruit

water from starch and pulp. The fruit water is partly separated, depending on

the type of equipment in use. Additional water is added at this stage to dilute

the fruit water.

2.1.4 Starch Extraction

In the extraction stage, the starch is separated from the cellulose (fibres/pulp)

in multi-stage extractors. The multi-stage extractors consist of three to four

extracting units directly connected to each other without any intermediate

tanks. The extractors are made of rotating centrifugal sieve cones with 60 to

80 mesh sieves in the first coarse extraction stage; and a 90-mesh filter cloth in

the subsequent fine extraction stage. The extractor units are entirely built with

stainless steel.

The starch pulp slurry is fed into a conical rotating screen, where jets of wash

water are sprayed onto the pulp to separate the starch and fibres.


2-4

The washing is undertaken in counter-current. This wash water is taken from

the effluent of the starch-refining section.

Sulphur solution is added in this stage to inhibit microbiological reaction, and

consequently to prevent formation of lactic acid.

The washed fibres (pulp) leaving the last unit of extractor contain 90 to 95 % of

water and a low-starch content. The pulps are then dewatered by pressing

and are left dried on concrete floor. Dry pulps are to be further sold to animal

feed mills or used as media for mushroom cultivation.

The crude starch milk leaving the fine screen has a concentration of about 3

Beaumè (°Bè) (54 kg dry starch per m³), consisting of soluble contaminations,

such as proteins, fatty material, sugars (rests of fruit water), and insoluble

contamination such as small cellulose particles from the rasping operation

(rests of pulp). This portion of insoluble contamination will be removed

during the subsequent refining stage.

2.1.5 Starch Refining

The processing of tapioca roots has to be completed within the shortest

possible time to avoid reduction of starch quality and content due to fast

enzymatic and chemical reaction. A continuous refining system without

detention tanks is normally used at this stage, where the refining of the starch

is carried out for a few minutes via separation, washing and concentration.

The pulp containing starch is pumped through a safety strainer and a sand

cyclone in order to protect the subsequent aggregates and the product quality.

Thereafter the slurry enters the separation equipment arranged as centrifuges

or hydrocyclones.

Most factories use separators for starch refining. To ensure a high quality

starch, separators in series are installed. The heavy phase leaving the

separators is the starch with the concentration around 20 to 22 ° Bè, whereas

the light phase is the resulting wastewater.

The concentrated starch then goes to the next step “drying process", and

the wastewater typically enters the wastewater treatment plant. In certain

factories where a biogas system is installed, this wastewater goes to the biogas

system.

2.1.6 Starch Dewatering, Drying, Cooling and Bagging

The refined starch slurry is dewatered and then continuously fed to the dryer

through screw transporters. The dryer is a pneumatic flash dryer, in which

the evaporation takes place by the exposure of the moist material to 200°C hot

air. Drying is completed in a very short time to ensure that no grains are


2-5

formed and that degrading or modifying of the starch does not taking place.

The hot starch is separated by cyclones.

It is crucial to cool starch immediately after being dried, thus the flash dryer is

equipped with special cooling cyclones. The hot cyclones and the cooling

cyclones shall be designed to allow drying efficiency of 99.95%. An automatic

air regulator keeps the moisture content of the final starch within the limit

about 12 to13 %.

Then, the starch is bagged for further distribution, whereas the exhausts from

the dryer and cooler enters a starch recovery unit before the exhausts are

emitted to the atmosphere.

2.1.7 Utilities

The main utility system for native starch factories includes water treatment

plant, burner, generator, wastewater treatment plant, and biogas system

where applicable.

Water Treatment Plant

Water is utilised in various sub-processes of native starch production

(i.e. washing and peeling, starch extraction, and starch refining). Raw water is

treated in a water treatment plant for coagulating and chlorination prior to use

in such sub-processes.

Burner

Burner is used to generate hot air. Hot air serves as one of the main energy

sources for native starch production process. In normal operation,

a considerable amount of bunker oil is used as burner fuel. However, bunker

oil can be substituted by biogas generated from biogas system, which is being

applied at some of the native starch factories.

Wastewater Management

Wastewater generated from native starch factory contains high organic

contents, therefore, can be used as liquid fertiliser. However, level of organic

content should be pre-adjusted to attain a suitable fertilising condition,

through addition of wastewater treatment.

To assure the quality of wastewater effluents meeting the industrial effluent

standard, further treatment of process wastewater is required. Environmental

Management Guideline for Native Starch Industry (1997) has provided a review of

suitable wastewater treatment technologies for native starch industry,

including primary wastewater treatment, secondary wastewater treatment

and nitrogen removal.


2-6

Biogas System

Due to high organic loading of wastewater generated from native starch

production, therefore it is possible to apply anaerobic digestion technologies

to recover and convert organic wastewater into biogas. In the past, the most

widely adopted wastewater treatment plant was pond treatment system,

which comprised of anaerobic ponds, facultative pond, and polishing pond.

Biogas generated from anaerobic ponds was neither captured nor utilised.

In recent years, a biogas system has been introduced to starch industry in

order to reduce the energy cost and also minimise the impact on water

pollution. Typically, native starch production generates wastewater with

the COD content of approximately 20,000-25,000 mg/l. Therefore, one (1) m3

of native starch wastewater could produce 8-10 m3 of biogas at 80% efficiency

of biogas system. Approximately, one (1) m3 of biogas may substitute

approximately 0.6 litre of bunker oil.

2.2 MATERIAL FLOW

Performance of the native starch production process can be determined by

considering the materials flows of production process. The materials include

inputs to the process (i.e. raw materials and energy) and outputs from

the process (i.e. products, wastes and emissions). A concept of material flows

is employed to identify, quantify and improve characteristics of products,

technical processes and eco-efficiency. Through this concept, analysis of

inventory based on balancing of material and energy flows, and balance

evaluation are applied.

Assessment of production performance is made possible by material flows.

Thus material flow incorporates itself as a key decisive making factor in

production process. An example of how material flow is inclusive in decision-

making includes decision on response plans or tasks to be employed in order

to improve or solve any particular problems of production process.

In a typical native starch factory, key materials influencing the eco-efficiency

performance are native starch, water, and energy. These key materials can

reflect the causes of under-performing production. Material flows associated

with native starch, water and energy are shown in Figure 2.2a - 2.2c.


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Figure 2.2a Material Flow of Native Starch

Thru native starch production since entering fresh tapioca root (FTR) into

production process, losses of starch occur in various sub-processes. Losses are

via discarded peel, pulp, dryer exhaust and wastewater stream. According to

Environmental Management Guideline for Native Starch Industry (1997), starch

loss during production process is approximately 40 kg/ton of native starch

produced.

Dry Sand Removal

Washing and Peeling

Chopping

Grinding


Starch Extraction

Starch Refining

Starch Dewatering

Starch Drying

Cooling and Bagging

Grid Chamber

Pulp Press

Fresh Tapioca Root

Recovered Starch

Starch Loss with Process Wastewater

Starch Losswith Pulp

Starch Loss with Peel

Starch Loss with Air Emission

Native Starch & Recovery

Department of Industrial Works MIS Guideline for Eco-efficiency Improvement2-

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Figure 2.2b Material Flow of Water

Fresh water is pre-treated by passing through water treatment plant.

Fresh water is mainly used in washing, peeling, and starch refining stages,

and also is partly used to produce sulphur solution for starch extraction

process. Used water from pulp press and refining stage is recycled and

supplied to other stages as present in above figure and finally leaving as

effluent from the wastewater treatment plant.

Efflu

ent


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Figure 2.2c Material Flow of Energy

Remark

Extraction and drying processes are the sections that consume the highest electricity.

Electricity is used as the main energy source for all sections in native starch

production process. Extraction and drying processes consume the highest

electricity, compared with the other sections. Only where a biogas system is

available and used for electricity generation, the utility section is able to self

*


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generates the electricity, which can be supplied into the production process

and wastewater treatment system.

To improve eco-efficiency, materials flows need to be established and

employed in order to understand the inputs and outputs of the production

process. The result is the identification of improvement opportunities within

the process. The material balancing flows function as pointer of where the

data should be collected and behave as balancing evaluation of material

inventory. For instance, through material balancing flow, starch loss within

the production process could be identified including where the loss is

occurring.

However, data and information on eco-efficiency in native starch industry

are currently limited. At present, actual information on material balance of

water and energy usage is rarely available. As a consequence, most

information regarding eco-efficiency are not fully utilised by management

to aid decision-making.

Theoretically, analysis of material inventory and balance could be

successfully undertaken, when eco-efficiency data have been continuously

collected. Therefore, the development of data collection, verification,

evaluation and information reporting is of particular concern, and is

a starting point for management information process to support decision-

making.

In this Guideline, Management Information System (MIS) is introduced for

improving eco-efficiency in native starch production. The following sections

of the Guideline will describe MIS concept, principles and how MIS could be

applied to native starch production.

Chapter 3

Introduction to

MIS Application


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3 INTRODUCTION TO MIS APPLICATION

3.1 BACKGROUND

Management Information System (MIS) is defined as a system or process that

manages the collection, analysis and presentation of information to assist

decision-making and to enhance business competitiveness. MIS is typically

used as a tool by management to assess and monitor business performance

and to help compare or identify possible business alternatives, i.e.

introduction of new activities and process modification in industries.

Basic functions of MIS are to systematically capture data from operations; to

analyse data and transform into meaningful information; and to report and

make use of information such as monitoring performance and improving any

given process or activities.

3.2 OBJECTIVES OF MIS APPLICATION

Since businesses have to face higher competition, Information Technology (IT)

has proven to be a crucial part of business decision making to obtain a leading

edge. Moreover, IT is also applied to other parts of the business such as

marketing, human resources, production process and eco-efficiency.

Specific objectives of MIS application depend on individual organisation’s

strategy. In this guideline, the main objective of MIS application in native

starch industry is to improve eco-efficiency and competitiveness.

A number of internal and external drivers encourage organisations to focus on

eco-efficiency practices.

These internal drivers include:

• Cost reduction;

• Increasing quality of products and services;

• Increasing innovations and employee motivation;

• Responsibility to community;

• Profitability;

• Managing environmental risks and liability; and

• Maintaining or increasing market share.

External drivers include:

• Customer demands for more “environmental-friendly” products;

• Competitive advantage by setting the trend or following market leader;

• Shareholders demanding accountability and transparency;

• Thai government regulations;


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• Public pressure for cleaner production; and

• Government regulations and directives where products are exported to

overseas such as European Countries;

Market globalisation has influenced companies to greatly improve the quality

and environmental soundness of products and services they provide while at

the same time to produce goods at the lowest possible cost. In such a context,

eco-efficiency improvement by promoting the creation of products while

optimising resource use and reducing wastes and pollution, can answer

the increasing business needs together with enhancing the business

competitiveness.

In this perspective, the introduction of MIS can provide valuable support for

successful decision-making at the management level in native starch industry.

With such a tool, eco-efficiency improvement can be achieved while at

the same time, competitiveness can be enhanced.

3.3 BENEFITS OF MIS APPLICATION

It is important to understand how MIS technology can support decision-

making and help to improve business competitiveness. However MIS can also

lead to a number of practical benefits for improving eco-efficiency.

These benefits include:

• Encouraging native starch industry to collect, analyse and transform

eco-efficiency data into meaningful information for the management in

a timely and systematic manner supporting order to support their

decision-making;

• Allowing the management of native starch factories to identify gaps for

improvement, to monitoring performance (either for their own internal

benchmarking or industry benchmarking), and also to compare various

alternatives such as process modification and installation;

• Increasing native starch productivity and maximising return on

investment;

• Cost reduction measures (and increasing revenue) through more efficient

use of materials, resources and energy;

• Reducing risks and liabilities with appropriate environmental

management planning and avoiding the use of toxic substances;

• Enhancing brand image through efforts on marketing and communication;

and

• Improving environmental performance and reducing toxic emissions by

reusing and recycling unused materials

3.4 MIS PRINCIPLES

Basic requirements for MIS application and implementation are categorised

into three (3) main elements comprising “People”, “Implementation Process”,


3-3

and “Tools” (hardware and software). Principles and relationship between

these elements are elaborated in this section.

3.4.1 People

The most important element in MIS is the people involved since all objectives

and benefits will be addressed by understanding personnel who will also

oversee MIS process, information and tools.

An MIS operation comprises of several tasks; therefore, it is necessary to

group such tasks, based on relevance, and assign roles and responsibilities to

fulfil them. By doing so will not only clearly define roles and responsibilities

to perform MIS processes but also assist plant owners to be able to select and

recruit suitable personnel.

It should be noted that the amount of MIS personnel is based on plant owner

consideration. Typical roles and responsibilities in MIS implementation are

described as follows.

Roles, Responsibilities and Qualifications:

In general, there are three (3) levels of roles and responsibilities for personnel

involved in MIS implementation, comprising management role, supervision

role, and operation role.

Management Role

Every successful MIS requires management support and involvement.

Without management, all data collection and analysis for decision making will

not be meaningful. The main role of management is to bind MIS and other

operation together to implement the decision made from MIS reports and/or

decision-making process. Also, management needs to take an active role in

facilitating the followings:

• Use and interpret information from MIS reports for decision-making;

• Align MIS strategy and policy with business strategy;

• Guide MIS supervisors on objectives and benefits of implementing an MIS;

• Provide and manage MIS budget and personnel;

• Communicate the importance of MIS to all employees including

MIS personnel and all other department personnel; and

• Provide support in further development and improvement of MIS in

the future.

Supervision Role

Personnel in charge of MIS supervision can be someone who posses an overall

understanding on how to reach the objectives and realise the benefits, while

manage and supervise MIS operation. Thus MIS supervisor is not necessarily

Information & Communication (ICT) trained or certified personnel.


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Typically, the supervision role is undertaken by a plant manager, production

manager, or dedicated MIS supervisor. However, it will be beneficial if MIS

supervisor is comfortable with computer technology.

Supervision roles and responsibilities include:

• Oversee all MIS processes, information and tools, are implemented in

a correct and good manner with clear understanding of realising the

objectives and benefits;

• Introduce the MIS procedures and its objectives to MIS operation

personnel;

• Analyse data and create useful information;

• Report information findings and recommendations to management for

decision making; and

• Organise maintenance, troubleshoot, and upgrade all MIS hardware and

software (optional).

Operation Role

Operation role can be assigned to any plant staff, who is involved in any

particular process that needs data collection. Typically, the plant personnel

taking the operational role come from different departments such as

production staff and laboratory staff. Understanding that data collection and

MIS procedure implementation are different tasks from regular operation

tasks, selecting personnel for this role requires those who understand and able

to perform MIS tasks with comprehension and care.

At the plant floor, implementing MIS procedures are secondary to operational

tasks unless acquire dedicated MIS personnel. MIS supervisors need to make

sure that MIS operation personnel are trustworthy and honest to their

responsibilities. Otherwise, MIS procedures and data collected will be skewed

and not present actual findings, which will lead to poor analysis, poor

reporting and poor decision making. Above all, it will not assist in realising

the objectives and benefits set out to implement MIS in the first place; hence,

careful selection and monitoring of MIS operation personnel is vital.

Operational roles and responsibilities include:

• Implement MIS procedures and tasks at any particular process required;

• Collect and enter data into provided system (i.e., software) accurately and

honestly; and

• Organise maintenance and troubleshoot, and upgrade all MIS hardware

and software (optional);

It should be noted that dedicated MIS team/personnel is recommended to

supervise, monitor and implement MIS procedures, tasks and tools.

Nevertheless, this would depend on the plant owner insights, budget and

operations.


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3.4.2 MIS Implementation Process

People, as described in the previous section (Section 3.4.1), will need to adopt

MIS processes and understand the information flow to implement MIS, and

successfully meet its objectives and benefits. A methodology for applying

an MIS needs to be selected for MIS implementation.

Every industry is different and so are their processes, information flow and

methodology. Conversely, the MIS processes could be applied to the native

starch industry. This section describes typical MIS processes, information

flow and methodologies for applying an MIS.

Typical MIS Processes

Preparation Stage

At this stage, people roles need to be assigned, tools need to be selected and

acquired; processes will need to be set and communicated to relevant

personnel and departments. Training is often required for personnel of

related process. Management shall take on the role in identifying the needs

for MIS implementation, setting the strategy, objectives, and the foundation

and its cooperation between internal departments and management, which in

turn determines the achievement of MIS commencement.

Personnel involved: Management, MIS, and Related Department Heads

Data Collection and Consolidation

Data collection and consolidation is a crucial process as it gathers actual data

from plant level. In most cases, this process is undertaken by existing plant

staff and not specifically dedicated MIS personnel; therefore, training and

reminders are often provided. To ensure the quality of data, a data audit

process shall be conducted from time to time.

After collection, data need to be consolidated and stored such as entering data

into software(1) to be systematically structured for further analysis.

This process is sensitive and is regarded as the most human error process in

MIS. Entering incorrect data, into the system would lead to poor analysis.

To prevent human error, data verification process based on each plant’s MIS

policy may need to be implemented. See section “ Software-enabled method”.

Personnel involved: MIS Supervisor and Assigned Operator

(1) Software-enabled method


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Data Cleansing & Verification or Data Auditing

This process is optional depending on each plant’s MIS policy. This process

varies from industry to industry but is required for financial application

processing such as credit card or loan. For native starch industry, it varies

from plant to plant whether data collection and consolidation is adequate and

reliable. If not, MIS supervisors will need to allocate additional resources to

verify data collected. Consequently, this process will not be emphasized in

this guideline.

Data Processing

Processing of entered data will create sets of information that will allow

management to support decision-making. Each set of information will then be

compared and analysed to measure each production processes’ efficiency,

illustrated by key performance indicators (KPI), creating plant and industry

benchmarks. Data processing is generally carried out by software.

This process is viewed as the most vital process in MIS processes since data

processing will provide key information such as how efficient each process is,

how each data collected can help improve efficiencies, and how to initially

adjust each process for better throughput according to data analysis.

Personnel involved: MIS Supervisor and Management

Information Reporting and Analysis

Following analysis, set of information will need to be arranged in

a presentable format for reporting. The purpose is to formalise sets of

information in a simple visual format so that high-level executives or

management can easily review it.

In regards to time constraint on management to review the information, it is

critical to standardise reports so that management has little-to-no learning

curve understanding the information. MIS needs to design this displaying

information process into formatted reports while incorporating minimum

time usage as possible; automate such process will be ideal. Recent researches

indicate that significant MIS time and resources are allocated to report

creation rather than necessary processes.

Since different management require different information based on their

interests; therefore, MIS reports should be designed to provide necessary

information for decision-making in the viewpoint of their interests.

Decision-making

This process is mainly management’s responsibility. MIS takes a supportive

role. Undeniably, this process is the pinnacle of MIS processes as it

summarises all MIS effort and allows MIS to make recommendations to

management based on analysed information.


3-7

Despite the outcome, implementing management’s decision is an assigned

departments’ responsibility which may need MIS support to fulfil such

implementation.

Information Flow

Relationship between MIS process and MIS roles and responsibilities is

summarised and shown by a typical information flow diagram in

Figure 3.4a as follows.

Methodologies

To capture and enter data through analyse and present information, all MIS

processes need to apply a methodology to centralise and store such data while

enable the information flow. Methodologies can be categorised as such:

Manual Method

This is the most labour intensive approach to carry out any process.

It requires involved personnel to utilise basic tools such as paper forms and

a calculator to perform process’ tasks. Filing of gathered or even analysed

information is at the heart of each method. The manual method requires

paper-based filing (storing) as actual working documents while act as back-up

copies at the same time.

This manual method requires the most resources when compare to the next

two methods but may present the most cost-effective approach due to low

investment in tools and low maintenance. However, this method presents

frequent human errors.

Unavoidably, as information technology becomes more sophisticated and

more economical, businesses grow to rely heavily on them; hence, the need of

continuity plan is becoming more important. It has been proven time and

time again, that when unforeseeable event occurs, technology cannot aid the

continuity of business processes. Although primitive technology-wise, this

method became the standard continuity process for MIS practice.


3-8

Figure 3.4a General MIS Information Flow Diagram

Data collection

& consolidation

Decision

making

Data calculation

Data

verification

Information

reporting &

analysis

Data storage

MIS Operation

MIS Supervisor

Management

Production Control

Process Modification


3-9

Software-enabled Method

This method requires an interaction with software on a personal computer

(PC). A minimum set of a PC is at the base of this method.

As discussed in the section “Data Collection and Consolidation”, to

systematically structure entered data, the software interface (screen) is

extremely important. This part in software design is called Graphical User

Interface or GUI. GUI is not only formatting fields on a computer screen but it

is a psychological behaviour pattern that is interpreted into a screen layout so

that users can understand how to use it at best.

Decent GUI allows users to engage and interact with data whether entering,

formatting, calculating or so on with a low learning curve. However, good

GUI design also depends on the software functionality. If it serves simple and

straightforward functions such as data entry, it shall be designed to

accommodate the sequence of data to be entered for such industry specific

process.

No matter how well designed-software GUI is, error occurs at the interaction

of human and PC since human performs data input. In addition, data

auditing and process monitoring are viable options to assure better data

quality and lower human errors.

Calculation and analysis including other MIS processes except decision-

making can adopt software usage in two approaches: “file-based” and

“purchase”.

File-based is where MIS personnel create or adopt file associated to each MIS

processes and deploy them on role usage basis. For instance, data entry at

extraction process may have one PC with a file to enter data for such

particular processes involved. This approach, although widely practice,

presents problems of storage, analysis and reporting since data are scattered

in files on multiple PCs. To solve this problem, MIS can customise

productivity software such as Microsoft Excel and Access to service the

information flow. Such approach is an in-house software design, which

requires time, tools (network, cable wiring, database, server and so forth) and

resources and is not standard but highly customised to that particular

business. Consideration to take this approach depends on MIS know-how

and skill.

A viable and standard alternative is to use purchased software, which is

created by reputable companies who have deep knowledge in industry

processes. Supporting information flow for a native starch plant may require

software that interconnects from each production process to process.

This particular type of software is called Manufacturing Resource Planning or

MRP. MRP is industry standard software but needs to be customised to fit

each plant’s production process, financial and accounting, and required


3-10

information in other departments. It may be costly, but it is proven to be

the most productive tool to enable efficiency boosting.

Automated Method

A sophisticated approach, which entails investments beyond computer

hardware and software, requires control over each process using hardware

and electronics that are able to capture data, alert on out-of-setting events and

interconnect to a computer network. This method is generally controlled via

a network of electronic controls and computers. Details of this method vary

highly from process to process; therefore, will not be discussed in this

guideline.

3.4.3 Tools

This section introduces MIS tools from paper-based to sophisticated tool, and

their attributes to consider its suitability to adopt.

Paper, Pencil/Pen and Calculator

Paper, pencil/pen and calculator are the most basic tools for any business

operation, and also the fundamental tools for MIS. No matter how

sophisticated MIS implementation can be, these tools would always be

required in business, as they are extremely familiar to any level of business

operation and are mostly adopted. Thus, application of these basic tools in

MIS process is straightforward. The advantage of these tools is that they

require almost no explanation in usage. The manual methodology requires

these sets of tools as mentioned previously for business continuity planning

and support.

For MIS, these tools can be applied specifically to data collection and

calculation processes. Unavoidably, as manual it is, prone to errors it

becomes. Repetition and verification of each process may be required to

guarantee its correctness.

Personal Computer (PC) and Productivity Software

In the late 1970s and early 1980s the personal computer (PC) has made its way

into every business. The reason is because it can support several tasks in one

machine lending a lot of equipment obsolete such as the typewriter.

However, it is the software inside the PC that makes all the difference.

Software are computer programs designed to serve specific tasks. The most

widely adopted next to operating system (programs to make PC function) is

productivity software such as Microsoft Office.

In a package of productivity software combines a word processor,

spreadsheet, presentation, communication, small database version of software

for users to work on.


3-11

The success of Microsoft Office made the standard productivity tools

synonymous with its brand name such as Microsoft Word, Microsoft Excel,

Microsoft PowerPoint, Microsoft Outlook and Microsoft Access respectively.

These software normally substitute any manual process due to its ease of use,

functionalities, and versatility; hence, it is standard for any business operation

to deploy PCs with productive software as it can serve any business.

File Cabinet and Database

The common purpose of these two is storage of data; the difference is in its

form. A file cabinet files paper-based documents, but database files digital

information in a digitally structured file cabinet.

A database is crucial to store data for data input such as entering data for data

collection and data output such as displaying data consolidation to perform

calculation or even as a report. Database is an electronic centralised place for

data storage. Normally the access of data is from many PCs; therefore,

a database is usually placed in a server on a network of PCs to access.

Before or after storing data electronically, the actual paper is used for writing

down data collection from any production process to print outs of data forms

to perform calculation or reports. All need a physical location to store, which

is the file cabinet.

File cabinets act as a backup location for database’s data printouts whether in

forms of raw data, data tables or reports. File cabinets are proven inadequate

to serve data input and output like databases. Hence, in business practice,

both coexist due to dependability. Procedures to guarantee the safety of

business data are also critically required; backup procedures are commonly

adopted.

Server and Local Area Network (LAN)

A server is a regular PC but dedicated as a public PC to allow other PCs to

access information on it such as a database.

A Local Area Network (LAN) comprises of multiple PCs, servers and network

equipment (i.e., hub, router, switch, etc.) to enable communication with other

PCs. The purpose of communication is to exchange information whether

being email, documents, data, and any forms of electronic information.

There are two (2) types of networks, which are wired/cable and wireless.

Wired/Cable Network

Wired/Cable network will use a physical network cable to physically connect

each PC. The advantage of using cable is that data transmission is reliable,

fast and cost-effective.


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Wireless Network

Wireless Network will use radio emission as media to carry the data over the

air between each PC. The advantage of wireless is the flexibility of location if

within radio emission reach, but it will sacrifice speed. When compare similar

size of networks, wireless networks are more expensive than wired.

MRP and ERP

MRP stands for Manufacturing Resource Planning; similarly ERP stands for

Enterprise Resource Planning. Both are software designed to connect

business processes and facilitate information flow using PCs, servers, and

network.

Each industry has its own specific MRP/ERP as processes are different.

For a given industry, MRP/ERP attempts to consolidate most processes by

using MIS. Currently, the average business that implements MRP/ERP can

bind 20% of the overall operation. This is due to the complexity of each

department and the interconnectivity to facilitate information flow.

Each department has its own sets of processes, which can create a complex

flow of information within the department. Implementing MRP/ERP requires

the management to to emphasize to all departments for cooperation. Over the

past two decades, Key Performance Indicator seems to be the driving force for

department cooperation.

Figure 3.4b illustrates different tools at each MIS process in accordance with

information flow.

A misconception of tools is to select, acquire and utilise the most advanced or

up-to-dated hardware and software when, functionality-wise, a moderate set

of computer hardware and software can perform such tasks adequately.

Adopting overqualified tools always irrationally causes increase in MIS

budget.

It should be noted that tools are to facilitate people to carry MIS processes and

information flow; understanding the methodologies, nonetheless, is more

essential than selecting and acquiring tools. The reason being that with such

understanding, MIS can better select and apply suitable tools that support

process requirements.

Table 3.4a addresses suggested tools for different methodologies (Manual,

Software-enabled and Automated) associated with MIS processes.


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Figure 3.4b Examples of Tools Used for MIS Process

Data

verification

Data calculation

Decision making

Data storage

Information

reporting & analysis

Production Control

Process Modification

Management

MIS Supervisor

MIS Operation

Data collection & consolidation


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Table 3.4a Suggested Tools for MIS Implementation with their Pros and Cons

Methodologies MIS

Process Manual Software-enabled Automated

Data

Collection

Pen/paper form Pen/paper form Pen/paper form

Data Entry Pen/paper form Excel/Access Packaged

software/MRP

Combination of

hardware and

software to

control

production

process

equipment

Data

Calculation

Form/calculator Excel/Access Packaged

software/MRP

Analytical

software or

business

intelligence

Information

Analysis &

Reporting

Paper report Access/paper report Packaged software/

paper report

Automated

report creation

and distribution

Pros/ Cons Most basic/ low-to-

no investment

Widely adopted/

low investment

Currently best

practice/significant

investment

Highly effective/

high investment

Hard evidence

data/ high error rate

Ease of access to

MIS/Decentralised

data & storage

Ease of use and

access to all roles

with centralised

data storage/

customised on

Accurate data/

sensitive system

Labour intensive Computer literate

personnel required

Training required to

use software

Free up

resources/ rely

on solution

vendor

As shown in Table 3.4a above, a wide range of tools can be adopted

depending on the methodology selected. However, in the real practice, a mix

of methodologies is applied.

Whether noting down data on a piece of paper then enter into a database form

or key-in collected data into a software on the plant floor and printout to store

in a file cabinet, a mixture of tools are often used based on each plant’s

operation, familiarity and budget. Therefore, a pre-defined set of tools is often

mistaken.

In summary, each methodology (Manual, Software-enabled or Automated)

will evidently require different types of hardware. For example, Software-

enabled, file-based method, requires MIS personnel to design program

productivity software such as Microsoft Excel and Access, to create forms

(in MS Access), to interface with data entry formula sheets (in MS Excel) to

calculate such data and so forth.

Whereas, the automated method requires more complex and sophisticated PC

to communicate and enable the automation of data capturing via other

hardware such as steam gauge censor. This method minimally requires

a local area network (LAN) to facilitate the information flow.


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In conclusion, plant owners can select a methodology with comprehension

while being empowered with tool knowledge to be able to select suitable

software and hardware accordingly.

Chapter 4

Applying MIS Process

to Native Starch Industry


4-1

4 APPLYING MIS PROCESS TO NATIVE STARCH

INDUSTRY

This section describes how an MIS process is applied to native starch industry

in order to improve eco-efficiency. A production process model that facilitates

the MIS application for native starch industry is hereby addressed. Also, the

MIS process for typical native starch industry starting from data collection and

consolidation, data processing and to information reporting, is described.

4.1 PRODUCTION PROCESS MODEL

In order to facilitate data collection as part of the MIS process for improving

eco-efficiency, there is the need for establishing a representative “Production

Process Model” for a typical native starch factory. As a consequence, a typical

production process of native starch factory (shown in Figure 2.1a) can be

arranged or sub-divided into four (4) sections comprising: Material

Preparation Process; Extraction and Drying Process; Wastewater & Biogas;

and Utility.

4.1.1 Material Preparation (Section 1)

Material preparation section involves mainly with the conversion process of

tapioca root to crude starch milk by the following production steps:

• Dry Sand Removal;

• Washing and Peeling;

• Chopping; and

• Grinding.

4.1.2 Extraction and Drying Process (Section 2)

Once crude starch milk comes out from grinding step, it will enter to the

extraction and drying process part. The main task of this section is to extract

the tapioca starch and to improve the physical property of native starch.

This section comprises following main equipment:

• Fruit water separation using decanter - this depends on individual factories;

• Starch extraction;

• Starch refining;

• Starch dewatering;

• Starch drying; and

• Cooling and bagging.

This section also produces significant amount of wastewater and pulp.

Resulting wastewater goes to either wastewater treatment plant or biogas


4-2

system (depending on the availability of biogas system), whereas pulp can be

sold as raw material for animal feed mills.

4.1.3 Wastewater Treatment and Biogas System (Section 3)

This section mainly deals with the wastewater coming out from washing and

peeling, fruit water separation and starch dewatering steps in pre-production

process and other production stages. Biogas system is also included in this

section. Wastewater from fruit water separation and starch refining are used

as input to the system to generate biogases mainly methane which are used as

fuel for hot air burner.

4.1.4 Utility (Section 4)

Electricity, hot air and fresh water are used to support the native starch

production process. This section comprises water treatment unit, hot air

burner and electricity generator where applicable.

A representative “Production Process Model“ for MIS application for

improving eco-efficiency in native starch industry is shown in Figure 4.1a.

4.2 DATA COLLECTION AND CONSOLIDATION

In order to apply MIS, a set of data will continuously need to be acquired for

further usage. The first step as described in MIS principal process will be the

data collection and entry of each section in MIS production process model

(Figure 4.2a–4.2d). After collecting of data from each section, MIS will need to

consolidate all data into one centralised place whether on paper or in

a computerised format such as an excel file or a database. This is to help

facilitate the information flow for further processes.

As a result of a baseline study, users’ requirement identification and capacity

assessment of representatives of native starch factories, a set of proposed data

to be collected has been established based on their current data collection,

analysis and information usage, and their needs for applying MIS to enhance

business competitiveness and eco-efficiency. Table 4.2a–4.2e illustrate

the proposed data collection scheme for each simplified production process

model/ section of native starch industry.

The data collection scheme addresses proposed data, measurement unit,

priority of data collection, objectives, collection frequency, responsibility, and

measurement methods. It should be noted that the proposed data set has been

prioritised into “Priority 1” and “Priority 2” based on the main purpose of

enhancing the native starch factories to implement a meaningful MIS.

Criteria for data prioritisation are given below:

• Priority 1 – Data that are directly related to native starch productivity and

the use of main raw materials as well as the management of value-added


4-3

unused materials where economically viable to native starch factories.

In addition, environmental data required to be reported to the government

are also included (Examples of data include the use of fresh tapioca root,

the use of water, electricity and effluent quality); and

• Priority 2 – Data that are indirectly related to productivity of the native

starch factories including pollution outputs from the production process,

and also those data that play a key role in the production process however

are hardly or costly measured at present (Examples of data include

saleable peel and pulp and burner stack emissions).

“Priority 1” data are the minimum data requirements for applying meaningful

MIS for increasing business competitiveness and enhancing eco-efficiency for

a typical native starch factory. In addition, these data will be further

processed into information or performance indicators to allow the

management to use and make decisions.

A set of management information is addressed in Table 4.4a of this Guideline.

Locations of data to be collected are illustrated in Figure 4.2a-4.2d.

The collecting locations addressed in Figure 4.2a-4.2d are indicated by

code consisting of a letter with numbering.

Abbreviations of these numerical codes are provided as follows:

• P = Products and By-products (Valuable Unused Materials)

• S = Sales

• L = Efficiency and Losses

• C = Purchases

• I = Input Materials

• E = Energy and Fuel

• W = Waste and Emissions

Whereas, “Priority 2” data are optional data requirements that are useful and

help business competitiveness and eco-efficiency however these data are

considered as the second priority for the native starch factories (with less

concern than “Priority 1” data). Thus, these data will not be transformed to

the information or performance indicators in this Guideline (but these data

could be additionally included according to the specific needs of individual

native starch factory).

In general, the collected data are first stored in a database and processed in

MIS software, and then key performance indicators (KPI) are created and

these information are reported to management for decision-making.


4-4

Figure 4.1a Production Process Model for Native Starch Industry

Recycled W

ater

Fresh W

ater

MATERIAL PREPARATION

EXTRACTION AND DRYING PROCESS

UTILITY

TREATMENT SYSTEM


4-5

Figure 4.2a Locations of Data Collection in Material Preparation (Section#1)

MATERIAL PREPARATION


4-6

Table 4.2a Proposed Data Collection Scheme for Material Preparation Section (Section#1) of Native Starch Production

No Data Unit Priority* Objectives Collection

Frequency

Responsibility Measurement Methods

C1 Total Expense of Fresh

Tapioca Roots (FTR) being

Purchased

Baht 1 To monitor the expense of FTR purchased and to

estimate and plan native starch production

Daily Purchasing N/A

I1 Total Amount of Fresh

Tapioca Roots (FTR) being

Purchased

Ton 1 To monitor the amount of FTR purchased and to

estimate and plan native starch production

Daily Purchasing Weighing, i.e. the use of

weigh bridge

C2 Unit Cost of FTR

(Highest starch content)

Baht/Ton 1 To monitor the highest unit cost of FTR purchased

onsite and this data reflects the quality of FTR

being purchased (ideally good quality)


C3 Unit Cost of FTR

(Lowest starch content)

Baht/Ton 1 To monitor the lowest unit cost of FTR purchased

onsite and this data reflects the quality of FTR

being purchased (ideally poor quality)


C8 Code of FTR Provider N/A 2 To record the source of purchased FTR Daily Purchasing N/A

C14 Starch Concentration of FTR % 1 To calculate the purchasing price of FTR Daily Purchasing Weighing (Buoyancy

Principle)/ Analytical

Standard Method

I2 Use of Fresh Tapioca Root

(FTR)

Ton 1 To monitor the actual amount of FTR being used

in production process and to estimate and plan

native starch production

Daily Production Estimation based on I1

W1 Generation of Sand Ton 2 To monitor the amount of sand generated. This

data can be further used to determine the typical

ratio of sand and fresh tapioca root

Monthly Production Weighing, i.e. the use of

weigh bridge

P1 Generation of Tails and Stalks Ton 2 To monitor the amount of tails and stalks

generated. This data can be used further to

determine the typical ratio of tails and stalks of

tapioca root.

Monthly Production Weighing, i.e. the use of

weigh bridge


4-7


Frequency


P2 Generation of Peel Ton 1 To monitor the amount of peel generated. This

data can be further used to track the utilisation of

peel as by-product

Monthly Production Monthly estimation

based on representative

weighing of peel

S1 Amount of Peel being Sold Ton 1 To help evaluate the efficiency of peel utilisation

and estimate this value-added by-product

Monthly Purchasing Weighing/ Scale

S2 Unit Market Price of Peel Baht/Ton 1 To help calculate the revenue from selling peel to

external parties or customers

Monthly Purchasing/ Sale N/A

W2 Amount of Peel being

Disposed Offsite

Ton 2 To estimate the amount of peel being disposed

offsite or used by plantation


I3 Recycle Water Consumption m3 2 To monitor the total volume of water recycled

within production process

Daily Production Standard Flow Meter

W3 Generation of Wash

Wastewater

m3 1 To monitor the total volume of wash wastewater

generated from material preparation section

Daily Production Standard Flow Meter or

Estimation by Sampling

L1 Starch Content in Wash

Wastewater

% 2 To trace the percentage of starch content

contaminates wash wastewater

Daily QA Lab Analytical Standard

Method

I4 Fresh Water Consumption for

Material Preparation

m3 1 To monitor the volume of fresh water required in

material preparation


E1 Electricity Consumption for


kWh 2 To monitor the electricity consumption for

material preparation

Daily Utility Electricity Meter

Remarks

* - Priority of data collection is classified into two levels “1” as minimum data requirements and “2” as optional data requirements, based on the criteria mentioned earlier.


4-8

Figure 4.2b Locations of Data Collection in Extraction and Drying Section (Section#2)


Starch Extraction

Starch Refining

Starch Dewatering

Starch Drying

Pulp Press

Fruit Water

Pulp

Sulphurous Acid

Recovered Starch

Process Wastewater

Hot Air from Burner

Fresh W

ater

Native Starch

Recycled Water

Sold Disposed

Sulphur

Starch Loss & Recovery

Fresh Water

Fresh Water

Recycled Water

E2

I7

L2

L4

L3 P3

P4

EXTRACTION AND DRYING PROCESS

W5

W6

W4

Cooling and Bagging

Fresh Waterfrom Water Treatment

From Material PreparationTo Material Preparation

To Biogas Plant

I6

S3

L8L7

S7


4-9

Table 4.2b Proposed Data Collection Scheme for Extraction and Drying Section (Section#2) of Native Starch Production


Frequency

Responsibility Measurement

Methods

I5 Installed Capacity of the

Factory

Ton-FTR 1 To realise the maximum capacity of native starch

production

Monthly Production N/A

W4 Generation of Fruit Water m3 1 To monitor the volume of fruit water generated

within production process. This data reflects the

volume of waste water entering biogas system


or Estimation by

Sampling

L2 Starch Content in Fruit Water % 2 To trace the percentage of starch content

contaminated in fruit water

Daily Production/ QA

Lab

Analytical Standard

Method

I6 Fresh Water Consumption for

Extraction Process

m3 1 To monitor the volume of fresh water required in

this section


P3 Generation of Pulp Ton 1 To monitor the amount of pulp generated. This

data can be used further to track the utilisation of

pulp as by-product

Monthly Production Monthly estimation

based on

representative

weighing of pulp

S3 Amount of Pulp being Sold Ton 1 To help evaluate the efficiency of pulp utilisation

and estimate this value-added by-product


S4 Unit Market Price of Pulp Baht/Ton 1 To help calculate the revenue from selling pulp to

external parties or customers

Monthly Purchasing/ Sale N/A

W5 Amount of Pulp being

Disposed Offsite

Ton 2 To estimate the volume of pulp being disposed

offsite


L3 Starch Content in Pulp % 1 To trace the percentage of starch content

contaminated in pulp

Daily QA Lab Analytical Standard

Method

I7 Sulphur Consumption kg 2 To monitor the total amount of sulphur required

in production process

Daily Production/

Purchasing

Weighing/ Scale

W6 Generation of Process

Wastewater

m3 1 To monitor the process wastewater generated

from extraction and drying section


or Estimation by

Sampling

L4 Starch Content in Process

Wastewater

% 1 To trace the percentage of starch content

contaminates process wastewater

Daily Production/ QA

Lab

Analytical Standard

Method


4-10


Frequency

Responsibility Measurement

Methods

P4 Native Starch Production Ton 1 To monitor the production of native starch Daily Production/

Accounting

Weighing/Scale

P5 Production Operating Hour Hour 1 To realise the actual operating hours of native

starch production

Daily Production N/A

S5 Unit Market Price of Native

Starch

Baht/Ton 1 To realise the daily unit market price of native

starch. This data reflects to the total revenue of

native starch being sold

Daily Accounting N/A

S7 Amount of Sold Native Starch Ton 1 To monitor the amount of native starch being sold Daily Accounting Weighing/Scale


Extraction and Drying Process


extraction and drying process


L7 Average Starch Concentration

at 1st Separator

Beaumè 1 To monitor the starch concentration at 1st separator Daily Production Analytical Standard

Method

L8 Average Starch Concentration

at 2nd Separator

Beaumè 1 To monitor the starch concentration at 2nd

separator

Daily Production Analytical Standard

Method

Remarks



4-11

Figure 4.2c Locations of Data Collection in Wastewater Treatment and Biogas System Section (Section#3)


4-12

Table 4.2c Proposed Data Collection Scheme for Wastewater Treatment and Biogas System Section (Section#3) of Native Starch Production


Frequency


W7 Total Generation of

Wastewater

m3 1 To monitor the total wastewater generated from

all production processes. This data is reported to

DIW according to regulation

Daily Production Standard Flow Meter or

Estimation by Sampling

or Calculation

W8 Influent Wash Wastewater

Characteristics (BOD) prior to

being sent to the wastewater

treatment system

mg/l 1 To provide information on influent quality (BOD)

and help the estimation of wastewater loading

prior to entering the treatment system, in order to

allow the in-charge operator to properly control

and maintain the treatment efficiency

Monthly QA Lab Analytical Standard

Method

W18 Influent Wash Wastewater

Characteristics (COD) prior to

being sent to the wastewater

treatment system

mg/l 1 To provide information on influent quality (COD)


prior to entering the treatment system, in order to


and maintain the treatment efficiency


Method

W9 Treated Wastewater

Characteristics (BOD) at the

final pond of the treatment

system

mg/l 1 To provide information on compliance status of

treated effluent (BOD)


Method

W15 Treated Wastewater

Characteristics (COD) at the

final pond of the treatment

system

mg/l 1 To provide information on compliance status of

treated effluent (COD)


Method

W10 Influent Wastewater

Characteristics (BOD) prior to

being sent to Biogas System

mg/l 1 To provide information on influent quality (BOD)


prior to entering the biogas system, in order to


and maintain the biogas system efficiency

Weekly QA Lab Analytical Standard

Method


4-13


Frequency


W16 Influent Wastewater

Characteristics (COD) prior to

being sent to Biogas System

mg/l 1 To provide information on influent quality (COD)


prior to entering the biogas system, in order to


and maintain the biogas system efficiency


Method

W11 Effluent Wastewater

Characteristics (BOD) after

treated by Biogas System

mg/l 1 To provide information on effluent quality (BOD)

from biogas system. This data can be used to

monitor biogas system efficiency


Method

W17 Effluent Wastewater

Characteristics (COD) after

treated by Biogas System

mg/l 1 To provide information on effluent quality (COD)


monitor biogas system efficiency


Method

E3 Biogas Generation from

Biogas System

m3 1 To monitor the volume of biogas generated from

biogas system and this data can be used to

indicate the efficiency of biogas system and the

quality of wastewater entering the biogas system

Daily Utility Standard Flow Meter

W12 Generation of Wastewater

Sludge

Ton 2 To help the management and offsite disposal of

wastewater sludge from the treatment system

Annually Utility Weighing/ Scale

I8 Chemical Usage for

Wastewater Treatment

kg 1 To monitor the use of chemicals for wastewater

treatment and to report to Department of

Industrial Works

Monthly Utility Weighting/ Scale


Wastewater Treatment Plant


wastewater treatment and to report to

Department of Industrial Works


E11 Biogas Tank Volume m3 1 To realise the maximum volume of biogas tank

for receiving wastewater from native starch

production. This data is used for calculating KPI

“organic loading of biogas system”

(see Table 4.3a)”

Annually Utility N/A

Remarks



4-14

Figure 4.2d Location of Data Collection in Utility Section (Section#4)

UTILITY


4-15

Table 4.2d Proposed Data Collection Scheme for Utility Section (Section# 4) of Native Starch Production


Frequency


E5 Generation of Electricity from

Biogas system

kWh 1 To monitor the amount of electricity generated


indicate the efficiency of electricity generation

from the biogas system


E6 Total Electricity

Consumption

kWh 1 To monitor the total electricity consumption Daily Utility Electricity Meter

E7 Electricity Consumption from

Utility Sector

kWh 2 To monitor the electricity consumption from the

hot air generator


E8 Bunker Oil Consumption for

Hot Air Generator

Litre 1 To monitor the bunker oil consumption from the

hot air generator


E9 Biomass Consumption for

Hot Air Generator

Ton 1 To monitor the biomass consumption from the hot

air generator

Monthly Utility Monthly estimation

based on representative

weighing of biomass

E10 Biogas Consumption for Hot

Air Generator

m3 1 To monitor the volume of biogas consumption

from hot air generator


W13 Burner Stack Emission

Characteristic (Particle)

mg/l 2 To provide information on air emission quality

(Particle) releasing from burner stack


Method

W14 Burner Stack Emission

Characteristic (NOx)

mg/l 2 To provide information on air emission quality

(NOx) releasing from burner stack


Method

C4 Expense on Purchased Fresh

Water

Baht 1 To monitor the operating cost arising from the

purchased fresh water

Monthly Purchasing N/A

C10 Average Cost of Purchased

Fresh Water

Baht/ m3 1 To monitor the average operating cost arising from

the purchased fresh water


C5 Expense on the Purchased

Bunker Oil


purchased bunker oil for burner



Bunker Oil

Baht/Litre 1 To monitor the average operating cost arising from

the purchased bunker oil for burner



4-16


Frequency



Biomass


purchased biomass for burner



Biomass

Baht/Ton 1 To monitor the average operating cost arising from

the purchased biomass for burner



Electricity from the PEA


purchased electricity from the PEA



Electricity from PEA

Baht/kWh 1 To monitor the average operating cost arising from

the purchased electricity from the PEA



Sulphur

Baht/kg 1 To monitor the average operating cost arising from

the purchased sulphur


Remarks



4-17

Table 4.2e Proposed Data Collection Scheme for Internal Control Values


Frequency


L5 Expected Starch Content in

Pulp

% 1 To benchmark performance of pulper and to

improve or correct production performance. This

data is also used as internal control value for

calculating KPI “starch loss and value of starch

losses at pulper” (see Table 4.3a)

Annually Production

Manager

Production manager

responses for setting this

internal control value

L6 Expected Starch Content in

Process Wastewater

% 1 To benchmark performance of refiner and to

improve or correct production performance. This

data is also used as internal control value for

calculating KPI “starch loss and value of starch

losses at refiner” (see Table 4.3a)

Annually Production

Manager

Production manager

responses for setting this

internal control value


4-18

4.3 DATA PROCESSING

In order to enhance business advantage and eco-efficiency of the native starch

factory, “Priority 1” data listed in the previous section are required to be

processed and transformed into information or key performance indicators

using MIS software that can allow the management of native starch factories

to use such information for their own analysis and making decision.

Table 4.3a illustrates these management information (or key performance

indicators), data calculation formula, and their definitions, whereas Table 4.4a

in the next section suggests on whom the management information are

reported to, and also the reporting frequency.


4-19

Table 4.3a Management Information derived from Data Processing

No Key Performance

Indicator

Reference

Timeframe

Calculation Formula Unit Description

Material Preparation (Section#1)

MAT1 Average Unit Cost of

Acquired Fresh Tapioca

Roots (FTR)

Daily [Total Expense of FTR Purchased / Total

Amount of FTR Purchased] [C1 / I1] Baht/Ton-

FTR

The total cost of FTR bought in each buy

depends on the quality of FTR (high or low

starch content). Average unit cost of acquired

FTR represents the overall quality of FTR

being bought as a whole in each day.

MAT2 FTR Quality Index Daily [(Average Unit Cost of Acquired FTR – The

Lowest Unit Cost of FTR) / (The Highest

Unit Cost of FTR – The Lowest Unit Cost of

FTR)] X 100

[(MAT1 – C3)/

(C2 - C3)] X 100

% FTR quality index represents the utilisation of

good and consistent quality FTR for native

starch production. The more percentage of the

index is, the better quality (also consistency) of

the FTR is purchased for the production.

MAT 3 Fresh Water

Consumption for


Daily,

Monthly

[Fresh Water Used / FTR Used] [I4 / I2] m3-Water/

Ton-FTR

The ratio of water consumed per the amount

of FTR indicates the utilisation of fresh water

in material preparation process

MAT4 Generation of Peel Monthly [Peel Generated / FTR Used]X 100 [P2 / ∑MI2] X 100 % The ratio of peel generated per the amount of

FTR indicates the generation rate of peel and

efficiency of peeling process.

MAT5 Share of Peel Sold Monthly [Peel Sold / Peel Generated] X 100 [S1 / P2] X 100 % Peel is typically used for plantation such as

mushroom cultivation. The amount of saleable

peel represents the utilisation of peel as value-

added by-product.

MAT6 Value of Peel Sold Monthly [Peel Sold X Unit Market Price of Peel] [S1 X S2] Baht The amount of money in Baht that is generated

from peel being sold to external parties or

customers.


4-20

No Key Performance

Indicator

Reference

Timeframe


Extraction and Drying Process (Section#2)

EDP1 Fresh Water

Consumption for

Extraction Process

Daily,

Monthly

[Fresh Water Used for Extraction and

Drying Process/ FTR Used]

[I6 / I2] m3-Water/

Ton-FTR

The ratio of fresh water consumed per the

amount of FTR indicates the utilisation of fresh

water in native starch extraction process.

EDP2 Share of Pulp Sold Monthly [Pulp Sold / Pulp Generated] X 100 [S3 / P3] X 100 % Pulp is typically used for producing animal

food. The amount of saleable pulp represents

the utilisation of peel as value-added by-

product.

EDP3 Value of Pulp Sold Monthly [Pulp Sold X Unit Market Price of Pulp] [S3 X S4] Baht The amount of money in Baht that is generated

from pulp being sold to external parties or

customers.

EDP4 Starch Loss at Pulper (1) Daily,

Monthly

[1 – ((Expected Starch Content in Pulp -

Starch Content in Pulp) / Expected Starch

Content in Pulp)]

[1 - ((L5 - L3) / L5)] % This indicator indicates the percentage of

starch loss or gain at the pulper, which also

indirectly represents the efficiency of pulper.

This loss can contribute to the reduction in

starch yield.

EDP5 Value of Starch Losses at

Pulper (1)

Monthly [(Starch Content in Pulp - Expected Starch

Content in Pulp) X Pulp Generated X Unit

Market Price of Native Starch / 100]

[(L3 – L5) X P3 X S5 /

100]

Baht The amount of money in Baht that is lost or

gained based on the content of starch in pulp.

EDP6 Generation of Process

Wastewater

Daily,

Monthly

[Process Wastewater Generated / FTR

Used]

[W6 / I2] m3 / Ton –

FTR

Process wastewater generation represents the

amount of wastewater occurred during starch

refining process. Process wastewater usually

contains starch content, therefore, the starch

content in process wastewater reflects to how

much starch loss from this production line.

EDP7 Starch Loss at Refiner (1) Daily,

Monthly

[1 – ((Expected Starch Content in Process

Wastewater - Starch Content in Process

Wastewater / Expected Starch Content in

Process Wastewater)]

[1 - ((L6 – L4) / L6)] % This indicator indicates the percentage of

starch loss or gain at the refiner, which also

indirectly represents the efficiency of refiner.

This indicator is an important performance

indicator in the native starch factory.


4-21

No Key Performance

Indicator

Reference

Timeframe


EDP8 Value of Starch Losses at

Refiner (1)

Monthly [(Starch Content in Process Wastewater -

Expected Starch Content in Process

Wastewater) X Process Wastewater

Generated X Unit Market Price of Native

Starch / 100]

[(L4 – L6) X W6 X S5 /

100]

Baht The amount of money in Baht compared with

fresh tapioca roots used indicates the

losses/gained in the comparable unit, and this

value can be further used as the benchmarking

figure.

EDP9 Native Starch Yield Daily [Native Starch Produced / FTR Used] X

100

[P4 / I2] x 100 % Native starch produced from the process

indicates the overall native starch yield and is

an important performance indicator in the

native starch industry.

EDP10 Value of Native Starch

Yield

Daily [(Native Starch Produced X Unit Market

Price of Native Starch) / FTR Used]

[(P4 X S5) / I2] Baht/ Ton –

FTR

The amount of money in Baht that is generated

from native starch being produced.

EDP11 Capacity Utilisation Monthly [Native Starch Produced / Installed

Capacity] X 100

[∑MP4 / I5] X 100 % This indicator demonstrates the actual

production capacity. The higher percentage of

capacity utilisation is, the more utilisation of

installed machine.

EDP12 Value Added From FTR

to Starch

Daily [(Unit Market Price of Native Starch X

Native Starch Production) / (FTR Used X

Average Unit Cost of Acquired FTR)]

[(S5 X P4) /(I2 X

MAT1)]

Time This figure indicates the time of value added

from FTR to starch. Operating cost is not

taken into account for this figure.

Wastewater Treatment and Biogas System (Section#3)

WBS1 Generation of Total

Wastewater (Influent to

the treatment plant)

Daily,

Monthly

[Total Wastewater Generated / FTR Used] [W7/ I2] m3 / Ton –

FTR

Environmental impact from starch industry is

mainly from wastewater generated in the

production process and its associated pollution

load. This value therefore indicates the need

for wastewater treatment and reflects overall

water utilisation efficiency.


4-22

No Key Performance

Indicator

Reference

Timeframe


WBS2 Total Wastewater

Treatment Plant

Efficiency

Monthly [(Influent Characteristics - Effluent

Characteristics) / Influent Characteristics]

X 100

{[(W8 X ∑MW3) + (W10

X (∑MW4 + ∑MW6)) /

(∑MW3 + ∑MW4 +

∑MW6)] - W9 / [(W8 X

∑MW3) + (W10 X (∑M

W4 + ∑MW6)) /(∑MW3

+ ∑MW4 + ∑MW6]} X

100

% This indicator represents the treatment

efficiency of wastewater treatment plant.

WBS3 Organic Loading of

Biogas System

Weekly [(Influent Characteristics X (Fruit Water

Generated + Process Wastewater

Generated)) / Biogas Tank Volume] X

1,000

[(W10 X (W4+W6))

/ E11] x 1,000

kg/ m3 of

Biogas Tank

Volume /

Day

Organic loading of biogas system indicates

how much organic load fed in to the system

and represents whether organic loading

feeding to the system is over the design value.

WBS4 COD Removal by Biogas

System

Weekly [(Influent Characteristics of Biogas System

- Effluent Characteristics of Biogas System)

/ Influent Characteristics of Biogas

System] X 100

[(W10 – W11) / W10] X

100

% This indicator represents the COD removal

efficiency of the biogas system.

WBS5 Generation of Biogas Daily,

Monthly

[Biogas Generated / Influents to Biogas

System]

[E3 / (W4 + W6)] m3 Biogas /

m3

Wastewater

Biogas generation indicated how much biogas

is generated by wastewater per unit. This

value can represent the biogas system

efficiency.

WBS6 Generation of Electricity

from Biogas System

Daily,

Monthly

[Electricity Generated / Biogas Generated] [E5 /E3] kWh/ m3 The ratio of the amount of electricity generated

from biogas system per biogas volume

indicates efficiency of electricity generation

from the system.

Utility (Section#4)

UTL1 Total Electricity

Consumption

Daily,

Monthly

[Total Electricity Consumption / FTR

Used]

[E6 / I2] kWh/ Ton –

FTR

Total electricity consumption of the whole

process comes from various sources. Total

consumption reflects average electricity

required for all production process.


4-23

No Key Performance

Indicator

Reference

Timeframe


UTL2 Total Fresh Water

Consumption

Daily,

Monthly

[Total Fresh Water Consumption / FTR

Used]

[(I4 + I6) / I2] m3/ Ton–FTR Total water consumption of the whole process

comes from various sources. Total

consumption reflects average water required

for all production process.

UTL3 Total Bunker Oil

Consumption

Daily,

Monthly

[Total Bunker Oil Consumption / FTR

Used]

[E8 / I2] Litre/ Ton–

FTR

Bunker oil is an important input. Total

consumption reflects average bunker oil


UTL4 Total Biomass

Consumption

Monthly [Total Biomass Consumption / FTR Used] [E9 / ∑MI2] Ton/ Ton–

FTR

Biomass is an important input. Total

consumption reflects average biomass


UTL5 Biogas Consumption Daily,

Monthly

[Biogas Consumption / FTR Used] [E10 / I2] m3/ Ton–FTR Total biogas consumption of the whole process

comes from various sources. Total

consumption reflects average biogas required

for all production process. It can also reflect

the percentage of biogas being used.

Remarks (1) - The amount of starch losses/gained depends on internal control value of individual native starch factory. (2) – Daily estimated values of such indicators are calculated by using the related key performance indicator values from previous month (PM)


4-24

4.4 INFORMATION REPORTING & ANALYSIS

Minimum data requirements or “Priority 1” data need to be processed into key

performance indicators that can assist the management of native starch in usage

and making decisions upon. Apart from the defined key performance indicators,

some of “Priority 1” data also provide valuable indicators to the management such

as daily use of fresh tapioca roots, daily production of products, unit costs and

prices of those materials, as well as data that are required to be reported to the

Department of Industrial Works (ie, treated wastewater and usage of chemical and

electricity for wastewater treatment).

Information in various aspects can become important to different groups of people

in the organisation. Typical interested management personnel in the native starch

factories are factory owner, factory manager/production manager and utility

manager. Management personnel of the native starch factories may require

different information.

Typical reporting contents for each management personnel are addressed below

(It should be noted that the needs of information by these personnel have been

established base on the interviews with management representatives of selected

native starch factories).

Owner

• Native Starch Yield

• Value of Native Starch Yield

• Value Added From FTR to Starch

• Native Starch Production

• Unit Market Price of Native Starch

• Amount of Sold Native Starch

• Average Unit Cost of Acquired Fresh Tapioca Root

• Fresh Tapioca Root Quality Index

• Use of Fresh Tapioca Root

• Total Expense of Fresh Tapioca Root Purchased

• Value of Starch Losses at Pulper and Refiner

• Capacity Utilisation

• Production Operating Hour

• Share of Peel and Pulp Sold

• Value of Peel and Pulp Sold

• Starch Loss at Pulper and Refiner

• Treated Wastewater Characteristics (BOD) at the final pond of

the treatment system

• Treated Wastewater Characteristics (COD) at the final pond of


• Generation of Biogas

• Generation of Electricity from Biogas System

• Biogas Consumption of Whole Production Process

• Total Consumptions of Electricity, Water, Bunker Oil and Biomass

• Expenses on Purchased Fresh Water, Bunker Oil, Biomass and Electricity


4-25

• Average Cost of Purchased Fresh Water, Bunker Oil, Biomass, Electricity and

Sulphur

• Legal Compliance regarding Treated Wastewater

Factory Manager/ Production Manager

• Native Starch Yield

• Value of Native Starch Yield

• Value Added From FTR to Starch

• Native Starch Production

• Unit Market Price of Native Starch

• Amount of Sold Native Starch




• Fresh Tapioca Root Quality Index

• Starch Concentration of FTR

• Used of Fresh Tapioca Root

• Average Starch Concentration at 1st Separator

• Average Starch Concentration at 2nd Separator

• Fresh Water Consumption for Material Preparation and Extraction Process

• Generation of Peel

• Share of Peel and Pulp Sold

• Value of Peel and Pulp Sold

• Value of Starch Losses at Pulper and Refiner

• Generation of Process Wastewater and Total Wastewater

(Influent to the treatment plant)

• Starch Loss at Pulper and Refiner

• Total Wastewater Treatment Plant Efficiency

• COD Removal by Biogas System


• Generation of Electricity from Biogas System






• Electricity Consumption for Wastewater Treatment Plant




Sulphur


Utility Manager

• Used of Fresh Tapioca Root





4-26

• Total Wastewater Treatment Plant Efficiency

• COD Removal by Biogas System

• Influent Wash Wastewater Characteristics (BOD) prior to being sent to the

wastewater treatment plant

• Influent Wash Wastewater Characteristics (COD) prior to being sent to the

wastewater treatment plant


the treatment plant



• Organic Loading of Biogas System

• Generation of Process Wastewater and Total Wastewater

(Influent to the treatment plant)


• Generation of Electricity form Biogas System

• Fresh Water Consumption for Material Preparation and Extraction Process


• Electricity Consumption for Wastewater Treatment Plant

• Chemical Usage for Wastewater Treatment




Sulphur


A set of the above-mentioned information and reporting frequency to various

interested personnel or management is summarised in Table 4.4a.


4-27

Table 4.4a Summary of Management Information

No Management Information Unit Owner Factory /

Production

Manager

Utility

Manager

Description

Material Preparation (Section#1)

MAT1 Average Unit Cost of Acquired Fresh

Tapioca Roots (FTR)

Baht/Ton-FTR Daily Daily Daily The total cost of FTR bought in each buy depends on the quality of

FTR (high or low starch content). Average unit cost of acquired FTR

represents the overall quality of FTR being bought as a whole in

each day.

MAT 2 FTR Quality Index % Daily Daily - FTR quality index represents the utilisation of good and consistent

quality FTR for native starch production. The more percentage of

the index is, the better quality (also consistency) of the FTR is

purchased for the production.

I2 Used of Fresh Tapioca Root (FTR) Ton Daily Daily Daily This indicator represents the actual amount of FTR being used in

production process and can estimate and plan for native starch

production in case FTR is stored.

MAT3 Fresh Water Consumption for Material

Preparation

m3-Water/

Ton-FTR

- Monthly Daily The ratio of water consumed per the amount of FTR indicates the

utilisation of fresh water in material preparation process

MAT4 Generation of Peel % - Monthly - The ratio of peel generated per the amount of FTR indicates the

generation rate of peel and efficiency of peeling process.

MAT5 Share of Peel Sold % Monthly Monthly - Peel is typically used for plantation such as mushroom cultivation.

The amount of saleable peel represents the utilisation of peel as

value-added by-product.

MAT6 Value of Peel Sold Baht Monthly Monthly - The amount of money in Baht that is generated from peel being sold

to external parties or customers.

C1 Total Expense of Fresh Tapioca Roots

(FTR) Purchased

Baht Daily - - This data indicates the expense of FTR being purchased and can be

used to estimate and plan for native starch production.

C14 Starch Concentration of FTR % - Daily - This data indicates the quality and price of purchased FTR.


4-28


Production

Manager

Utility

Manager

Description

Extraction and Drying Process (Section#2)

EDP1 Fresh Water Consumption for Extraction

Process

m3-Water/

Ton-FTR

- Monthly Daily The ratio of fresh water consumed per the amount of FTR indicates

the utilisation of fresh water in native starch extraction process.

EDP2 Share of Pulp Sold % Monthly Monthly - Pulp is typically used for producing animal food. The amount of

saleable pulp represents the utilisation of peel as value-added by-

product.

EDP3 Value of Pulp Sold Baht Monthly Monthly - The amount of money in Baht that is generated from pulp being

sold to external parties or customers.

EDP4 Starch Loss at Pulper (1) % Monthly Daily - This indicator indicates the percentage of starch loss or gain at the

pulper, which also indirectly represents the efficiency of pulper.

This loss can contribute to the reduction in starch yield.

EDP5 Value of Starch Losses at Pulper (1) Baht Monthly Monthly - The amount of money in Baht that is lost or gained based on the

content of starch in pulp.

EDP6 Generation of Process Wastewater m3 / Ton –

FTR

- Monthly Daily Process wastewater generation represents the amount of wastewater

occurred during starch refining process. Process wastewater

usually contains starch content, therefore, the starch content in

process wastewater reflects to how much starch loss from this

production line.

EDP7 Starch Loss at Refiner (1) % Monthly Daily - This indicator indicates the percentage of starch loss or gain at the

refiner, which also indirectly represents the efficiency of refiner.

This indicator is an important performance indicator in the native

starch factory.

EDP8 Value of Starch Losses at Refiner (1) Baht Monthly Monthly - The amount of money in Baht compared with fresh tapioca roots

used indicates the losses/gained in the comparable unit, and this

value can be further used as the benchmarking figure.

EDP9 Native Starch Yield % Daily Daily - Native starch produced from the process indicates the overall native

starch yield and is an important performance indicator in the native

starch industry.


4-29


Production

Manager

Utility

Manager

Description

EDP10 Value of Native Starch Yield Baht/Ton –

FTR

Daily Daily - The amount of money in Baht that is generated from native starch

being produced.

EDP11 Capacity Utilisation % Monthly Monthly Monthly This indicator demonstrates the actual production capacity. The

higher percentage of capacity utilisation is, the more utilisation of

installed machine.

EDP12 Value Added From FTR to Starch % Daily Daily - This figure indicates the value added from FTR to starch. Operating

cost is not taken into account for this figure.

P4 Native Starch Production Ton Daily Daily - This data represents the daily production of native starch.

P5 Production Operating Hour Hour Daily Daily Daily Production operating hour indicates the actual time spent on native

starch production.

S5 Unit Market Price of Native Starch Baht/Ton Daily Daily - This data represents the daily unit market price of native starch. It

can reflect to the total revenue of native starch being sold.

S7 Amount of Sold Native Starch Ton Daily Daily - Actual amount of sold native starch gives an indication to the

management on the actual amount of native starch being sold daily.

L7 Average Starch Concentration at 1st

Separator

Beaumè - Daily - Starch concentration at separator gives an indication of the native

starch production performance.

L8 Average Starch Concentration at 2nd

Separator

Beaumè - Daily - Starch concentration at separator gives an indication of the native

starch production performance.

Wastewater Treatment and Biogas System (Section#3)

WBS1 Generation of Total Wastewater (Influent

to the treatment plant)

m3 / Ton –

FTR

- Monthly Daily Environmental impact from starch industry is mainly from

wastewater generated in the production process and its associated

pollution load. This value therefore indicates the need for

wastewater treatment and reflects overall water utilisation

efficiency.

WBS2 Total Wastewater Treatment Plant

Efficiency

% - Monthly Monthly This indicator represents the treatment efficiency of wastewater

treatment plant.


4-30


Production

Manager

Utility

Manager

Description

WBS3 Organic Loading of Biogas System kg/ m3 of

Biogas Tank

Volume

- - Weekly Organic loading of biogas system indicates how much organic load

fed in to the system and represents whether organic loading feeding

to the system is over the design value.

WBS4 COD Removal by Biogas System % - Weekly Weekly This indicator represents the COD removal efficiency of the biogas

system.

WBS5 Generation of Biogas m3 Biogas / m3

Wastewater

Monthly Monthly Daily Biogas generation indicated how much biogas is generated by

wastewater per unit. This value can represent the biogas system

efficiency.

WBS6 Generation of Electricity from Biogas

System

kWh/ m3 Monthly Monthly Daily The ratio of the amount of electricity generated from biogas system

per biogas volume indicates efficiency of electricity generation from

the system.

W8 Influent Wash Wastewater Characteristics

(BOD) prior to being sent to the

wastewater treatment system

mg/l - - Monthly Influent characteristics of wastewater provides information on

influent quality and help the estimation of wastewater loading prior

to entering the treatment system, in order to allow the in-charge

operator to properly control and maintain the treatment efficiency.

W18 Influent Wash Wastewater Characteristics

(COD) prior to being sent to the

wastewater treatment system

mg/l - - Monthly Influent characteristics of wastewater provides information on

influent quality and help the estimation of wastewater loading prior

to entering the treatment system, in order to allow the in-charge

operator to properly control and maintain the treatment efficiency.

W9 Treated Wastewater Characteristics (BOD)

at the final pond of the treatment system

mg/l Monthly Monthly Monthly This data provides information on compliance status (BOD) of

treated effluent.

W15 Treated Wastewater Characteristics (COD)

at the final pond of the treatment system

mg/l Monthly Monthly Monthly This data provides information on compliance status (COD) of

treated effluent.

I8 Chemical Usage for Wastewater Treatment kg - - Monthy To monitor the use of chemicals for wastewater treatment and to

report to Department of Industrial Works.

E4 Electricity Consumption for Wastewater

Treatment Plant

kWh - Monthly Monthly This data can be used to monitor the electricity consumption for

wastewater treatment and to report to Department of Industrial

Works.


4-31


Production

Manager

Utility

Manager

Description

Utility (Section#4)

UTL1 Total Electricity Consumption kWh/ Ton –

FTR

Monthly Daily Daily Total electricity consumption of the whole process comes from

various sources. Total consumption reflects average electricity


UTL2 Total Water Consumption m3/ Ton–FTR Monthly Daily Daily Total water consumption of the whole process comes from various

sources. Total consumption reflects average water required for all

production process.

UTL3 Total Bunker Oil Consumption Litre/ Ton–

FTR

Monthly Daily Daily Bunker oil is an important input. Total consumption reflects

average bunker oil required for all production process.

UTL4 Total Biomass Consumption Ton/ Ton–FTR Monthly Monthly Monthly Biomass is an important input. Total consumption reflects average

biomass required for all production process.

UTL5 Biogas Consumption for Whole Production

Process

m3/ Ton–FTR Monthly Daily Daily Total biogas consumption of the whole process comes from various

sources. Total consumption reflects average biogas required for all

production process. It can also reflect the percentage of biogas

being used.

C4 Expense on Purchased Fresh Water Baht Monthly Monthly Monthly This data indicates an operating cost arising from the purchased

freshwater.

C10 Average Cost of Purchased Fresh Water Baht/ m3 Monthly Monthly Monthly This data indicates an average operating cost arising from the

purchased freshwater.

C5 Expense on the Purchased Bunker Oil Baht Monthly Monthly Monthly This data indicates an operating cost arising from the purchased

bunker oil for burner.

C11 Average Cost of Purchased Bunker Oil Baht/ Litre Monthly Monthly Monthly This data indicates an average operating cost arising from the

purchased bunker oil for burner.

C6 Expense on the Purchased Biomass Baht Monthly Monthly Monthly This data indicates an operating cost arising from the purchased

biomass for burner.

C12 Average Cost of Purchased Biomass Baht/ Ton Monthly Monthly Monthly This data indicates an average operating cost arising from the

purchased biomass for burner.

C7 Expense on the Purchased Electricity from

the PEA

Baht Monthly Monthly Monthly This data indicates an operating cost arising from the purchased

electricity from the PEA.


4-32


Production

Manager

Utility

Manager

Description

C9 Average Cost of Purchased Electricity from

the PEA

Baht/ kWh Monthly Monthly Monthly This data indicates an average operating cost arising from the

purchased electricity from the PEA.

C13 Average Cost of Purchased Sulphur Baht/ kg Monthly Monthly Monthly This data indicates an average operating cost arising from the

purchased sulphur.

Remarks (1) - The amount of starch losses/gained depends on internal control value of individual native starch factory.

References

REFERENCES

Agricultural Economic Office, Ministry of Agriculture (2005) 2004 Agricultural

Statistics of Thailand http://www.oae.go.th/statistic/yearbook47/ [Accessed

on 25 October 2005]

Cecelja, Franjo (2001) Manufacturing Information and Data Systems, First Edition :

Analysis, Design and Practice (Manufacturing Engineering Series)

Department of Industrial Works (DIW) and German Gesellschaft für

Technische Zusammenarbeit (GTZ) GmbH (1997) Environmental Management

Guideline for Native Starch Industry

Information and Communication Technology Bureau, Dapartmentof

Industrial Works (2005) Industrial Database http://sql.diw.go.th/result1.asp

[Accessed on 25 October 2005]

Laudon, Kenneth C. (2005) Management Information Systems : Managing the

Digital Firm (9th Edition), Prentice Hall

Schwalbe, Kathy (2005) Information Technology Project Management, Fourth

Edition

General Information of Native Starch

Factories from DIW’s Database

Name list of Native Starch Factories

�� ก� (HP)

1 �� ก�� 99/9 �.2 �.� !�"�ก-$�%&'�! �.(�!��(�) .�*��*+! �.ก�,� �� 71110 - - 2 �� /%0!�� 1� �&�2� ��ก�� 236 �.4 ก�.107 �./�!�&�� .+�!6�(� .�*��*+! �.ก�,� �� 71110 0-3464-7718-9 1,396.54 3 �� %��ก�: (1994) ��ก�� 1 �.7 �.�� ก�=�� >�:-��$� >�: �.� !ก�?! .�@! �.ก�=�� >�: 46000 0-4381-3059 2,574.66 4 �� ) / (��:�/ �:��( (A� /( �:) ��ก�� 41 �.�� : (ก�.24) �. �� : .�@! �.ก�=�� >�: 46000 0-4381-2061 6,544.66 5 �� B2�C �ก��ก�� ก�� 39 �.ก�=�� >�:-��$� >: �.D&�� .�@! �.ก�=�� >�: 46000 0-273-3612-3 3,847.00 6 �� A��: ��:� ��ก�� 19 �.8 �.�� : �.�2 �! .�@! �.ก�=�� >�: 46120 - - 7 �� ! �/%0!�� ก�� 45 ��/�* E��2� �.�� : �.&*�*� . �!�(�� .ก�=�� >�: 46000 0-4381-3020 5029.7 8 �� A� +� ��ก�� (�� ) ��$�ก�=�� >�: 136 �.12 �. ��( .�*�� .ก�=�� >�: 46190 0-4387-7087 5611.54 9 �� /%0!�� ก�=�� >�: ��ก�� 188 �.1 �.��F� -ก�G� �� H: �.��! .�?+ IJE! �.ก�=�� >�: 46240 0-4386-9243 6,685.70 10 �� /%0!�� F� ��ก�� 99 �.10 �?� E�� .��F� -ก�G� �� H: �.��! .�?+ IJE! �.ก�=�� >�:

46240 0-4382-3711-5 7,459.50

11 �� /ก* ��, ��ก�� (��$� 2) 199 �.1 �.�(!��&�H: .�(!$(�! �.ก��/2!2�� 62120 0-5570-1252 10,381.00 12 �� .1�.� /%0!�� ก�� ก�� 199 �.7 �./� � .$�H�+�(�ก�� .ก��/2!2�� 62130 0-5577-9166-8 6,426.10 13 �?�!��? �*+ ��ก�� > +�C :2@�I( 1169/1 �.1 �.�(ก�� .$�H�+�(�ก�� .ก��/2!2�� 62140 - - 14 �� A ��ก�� (A� +�) 771 �.1 �.2�(� >� �.�(ก�� .$�H�+�(�ก�� .ก��/2!2��

62140 0-577-1241-2 3,515.29

15 �� ,��$/%0!�� (2005) ��ก�� 188 �.7 �.2�(� >� ก�.374 �.2��D& ก�)! .�ก��2� �� .ก��/2!2�� 62000

- -

16 �?�!��? �*+ ��ก�� > +�C :2@�I( �.2 � �� (ก��-�*�E�� .�*�E�� .$�H�+�(�ก�� .ก��/2!2�� 62140

0-5577-1377, 0-5577-1681

5453

17 �� ?�2�" �2@�A�* 2999 (ก��/2!2��) ��ก�� .7 �. 2�� ก�"�*� .2�� ก�"�*� �.ก��/2!2�� 62110

0-5571-7871-2 4384.3

�� ก� (HP)

18 �� /ก* ��, ��ก�� 261 �.4 �.��+ �� .ก�" + �.$ /ก* 40170 0-4343-1355, 0-4343-1344

5081.28

19 �� !/%0!�� $ /ก* 2@�I( ��ก�� .7 � ��D�2 �. ��, .�@! �.$ /ก* 40000 0-4337-9334 6,368.00 20 �?�!��? �*+ ��ก�� !/%0!�� +�C � 129 �.8 �.�� - ��"/ก?+ �.��A�� .�%'! E��? �.�� 22140 0-3936-0036-7 - 21 �� :� ��ก�� 99/6 �.4 �.�� $�+ .� ��+ �.�� 22180 0-3931-7243-4 7,060.00 22 �� ) �%�� ก�� 111 �.14 �.��?�! .� ��+ �.�� 22180 0-3938-5090 8,223.31 23 �� 2��% �� ก�� 74 �.22 �.��+� �+!6: �.6�(�/�! .��! E��%��E + �.G"��!�� 24000 - - 24 �� 1 �� :� �� ( � ��ก�� 99 �.3 �.$�� 1? .2 �� .G"��!�� 24120 - - 25 �� :�%��ก�: ��ก�� $�2 96/10-11 �.7 �.ก�"$ � .2 �� .G"��!�� 24120 0-4421-2414-5 4,088.30 26 �� .1�.� �� ก�� 66/6 �.3 �.$�� 1? .2 �� .G"��!�� 24120 0-5850-2143 17,017.00 27 �� A� +� ��ก�� (�� ) 87 �.3 � ��$��+�� .�*�$?�� .��!%"ก! �.G"��!�� 24130 0-2285-0040 151 28 �� ก��*!�@!��ก�� ก�� 20485 �.3 � ก�� :��-G"��!�� .$�� 1? .2 ��

�.G"��!�� 24120 0-3853-1284-5 33169.72

29 �� 2� � 1� ��:� �%��ก�: ��ก�� 999 �.5 �.� !K�,* .� !K�,* �.�(�� 20190 - - 30 �� (��, ��ก�� 204 �.3 �.� !��ก .�?� �J! �.�(�� 20170 0-3875-2633-4 10,530.32 31 ��. ��?+��)!�L "��ก��/%0!�� /("��& 101 �.1 �.�� 2�+�� .� !%�@ .��!("��! �.�(��20260 - 384 32 �� A� +�C :��ก�� ก�� 198, 198/30 �.10 �.��ก/!?+ �.�?+ K�,* .��!("��! �.�(�� 20260 0-3823-9120 2,055.50 33 �?�!��? �*+ ��ก�� /%0!�� (�� 101 �.4 �.��!("��! .��!("��! �.�(�� 20150 0-3848-0764-5 1279.36 34 1?!�(� 322 �.4 � ��$��+�� . �ก(@ .��!("��! �.�(�� 20150 0-4424-1785 145 35 ��?+��)!!�L � 74 �.10 � ��$��+�� .��*!��$(� .6�� .�(�� 20110 0-3835-1477 159.5 36 �?�!��? �*+ ��ก�� *!ก�) 310 �.4 � ��$��+�� . �ก(@ .��!("��! �.�(�� 20150 0-3842-1472 309.95 37 �?�!��? �*+ ��ก��M*ก�) 57 �.3 � ��$��+�� .��@! .�@! �.�(�� 20130 0-3835-7150 63 38 �� D&��:� ��ก�� 50 �.11 �.�� D&�� - ��E+ �?� � (" �� .("�� .�� .�� D&�� 0-4441-2307 1,457.65

�� ก� (HP)

39 �� /%0!�� /�!2�� ก�� 84 �.5 �.� !��+�"�+ .� !��+�"�+ �.�� D&�� 36250 0-4489-7103-4 1,582.00 40 �� +(��E ��:� ��ก�� 222 �.10 �.�� H: �.��ก��!�� : .�� F�H�!�: �.�� D&�� 36160 0-4481-5555 14,772.87 41 �� 1�� A� ��:� ��ก�� 1/4 �.1 �.��2�(+! .�@! �. ��%B� 73000 0-3420-9491-6 3,077.00 42 �� A� �%��) (��E��:� ��ก�� 12/2 �.1 1 +�� .�?� K��* .��2�� . ��%B� 73110 - - 43 �� A� ก(&�� ก�� 32/8 �.1 �.�?� K��* .��2�� . ��%B� 73110 - - 44 �� (+!ก(&�� ก�� 67 �.1 �.�?� K��* .��2�� . ��%B� 73110 - - 45 �� /%1��N�� ก�� 81/2-3 �.10 �.A�*$�! .��2�� . ��%B� 73110 - - 46 �� ก��!�2��:�� ( ��ก�� 24 �.14 �.2��ก�� .A�*$�! .��2�� . ��%B� 73110 - - 47 �� !+ +!�:��ก�� ก�� 120 �.4 �.��-�� .� !��+6�(� .�@! �. ��

30000 0-4421-2723-6 11132.16

48 �� :�%��ก�: ��ก�� 76 �.4 �.� !��+6�(� .�@! �. �� 30000 - - 49 �� /%0!�� ก�� 35 �.1 �.��-�� (ก�.4) �.� !��+6�(� .�@! �. ��

30000 0-4421-2384-5 3553.37

50 �� ก��/%0!�� ก�� 61 �.3 �.�� -%Oก>!�� .� !�"�ก .�@! �. �� 30000 0-4424-3386 5095.8 51 �� 1�2�+� 2�P22�:��E ��ก�� (�?�2�" �2@�A�*) 269 �.1 �.��D�2 ก�. 237 �.��กก�+� .�@! �. �� 30000 0-22211-5595 3,100.07 52 �� /%0!�"+� กG� !� @ (1987) ��ก�� 67 �.��-�� .� !��+6�(� .�@! �. �� 30000 0-4424-1099 1440 53 �� -A� ��:�� ก�� 67 �.2 �.��-�� .� !��+6�(� .�@! �. �� 30000 - - 54 �� /%0!�� ก�� 108 �.9 �.��-��!��! �.��!��! .��!��! �. �� 30000 0-4445-7371-3 5,011.09 55 �� +�2� ��:� (2000) ��ก�� 117 �.16 �?� ��"%�"�� .��!��! .��!��! �. �� 30330 0-9846-0033 5,059.41 56 �� /%0!�� ) �M!��ก�� ก�� 15 �.12 �.ก��: .��!��! �. �� 30330 0-4444-7067 2591.79 57 �� 2� � ��:� ��ก�� 55 �.13 �.�� - �� .� !��+/�� .� !��

�. �� 30410

- -

�� ก� (HP)

58 �� 2�+�� : ��) / ( ��ก�� 99 �.4 �.� ! � �� .� !��+/�� .� !�� . �� 30410

0-2295-2136 1,865.49

59 �� A�� :��:� ��ก�� 290 �.4 �.� ! � �� .� !��+/�� .� !�� . �� 30410

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Documents

CONTENTS · Tapioca starch production is recognised as one of the most important agro-industries to the Thai economy. Tapioca starch is extracted from the root of the cassava plant,