OPTIMIZATION OF LASER CUTTING PARAMETER OF …eprints.utm.my/id/eprint/53535/1/ChuaYongPingMFKM2015.pdf · part nesting, time saving and low cost tooling. But, inappropriate control

OPTIMIZATION OF LASER CUTTING PARAMETER OF ACRYLIC BY

USING DMAIC APPROACH

CHUA YONG PING

UNIVERSITI TEKNOLOGI MALAYSIA

OPTIMIZATION OF LASER CUTTING PARAMETER OF ACRYLIC BY USING

DMAIC APPROACH

CHUA YONG PING

A project report submitted in partial fulfilment of the

requirements for the award of the degree of

Master of Engineering (Mechanical - Advanced Manufacturing Technology)

Faculty of Mechanical Engineering

Universiti Teknologi Malaysia

JULY 2015

iii

To my beloved mother and father

iv

ACKNOWLEDGEMENT

I would like to express the deepest appreciation from the bottom of my heart

to those who had lend a hand on the completion of this dissertation. First of all, I would

like to thank my supervisor and mentor Dr. Norizah bt Redzuan, for her continual

contribution of thoughts and ideas all times. Also, I am really impressed and admired

with the broad knowledge that she had shared about in recent research in Laser Cutting

Technology and Modern Machining Technology. Perhaps the dissertation couldn’t be

complete without her diligently guidance and support.

I also would like to extend my gratitude to En. Iskandar who constantly lends

me a hand in operating the laser cut machine all the times. And, I’m also indebted to

all the lecturer who had taught me before within the 2 years of masters’ taught course.

Next, I also would like to express my sincere appreciation to all my fellow

postgraduate students, Widodo, Salem, Didi, Zurina, Abbas, Soudesh, Ali

Esmaeilzadeh, M. Reza Yavari, Ibrahim Zaghdaoui, Abdul Azeez, Eswary Jane,

Amirul, Hafiz, Nabeel, Ken Wong, Chan Fook, Chian Yit, Edruce Muhammad, Wei

Huang, Geak Kun, Easy Wong, Chao Feng and Peggie Chia who had continuously

gave me support and comfort at various occasions although it’s impossible to list all

the names within the limited pages.

Finally, I would express my deepest gratitude to my parents who bringing me

up.

v

ABSTRACT

Laser cutting is the most common manufacturing process widely used

nowadays and this is due to its flexibility, reliability, maximize material utilization by

part nesting, time saving and low cost tooling. But, inappropriate control and setting

may lead to material defects, machine malfunction or even catastrophe. Hence, the

purpose of this study is to implement the ideas from lean six sigma for optimizing laser

cutting conditions to prolong the service life of the laser cutting machine. The entire

dissertation will be surrounded in optimize machining parameters for EPILOG Legend

36Ext – Model 9000 laser cutting machine in the FKM lab by using DMAIC approach.

And, the whole idea of optimal control was encapsulated in Lean Six Sigma

methodology which summarized in the abbreviation (DMAIC): Define, Measure,

Analyze, Improve and Control. First of all, a list of problem statement has constructed

to clarify the objectives of the project to be studied. Second, a value stream mapping

diagram has constructed to serve as an overview of the entire maintenance

management system in order to measure the bottlenecks between personnel and

information flow from relevant management level. Third, a mathematical modelling

software such as MATLAB was used to formulate the relationship between the cutting

parameters towards the cutting quality of acrylic specimens. Forth, solutions to

machining dysfunctions has proposed and optimum cutting conditions were developed

by using Design Expert software. Fifth, a standard practice such as SOP (standard of

procedure) was developed to replace current machining procedures. Finally, improved

plans were further monitored in order to ensure the improvements were sustainable.

After implementing DMAIC, it was found that the information given by supplier’s

manual should be continually revised since machining parameters due to deteriorate

of machine parts. The values of revising SOP may help FKM lab to save cost in

machine repair.

vi

ABSTRAK

Laser memotong ialah proses pembuatan paling biasa digunakan secara meluas

masa kini dan ini adalah disebabkan flexibiliti, kebolehpercayaan, memaksimumkan

penggunaan bahan dengan nesting, menjimatkan masa dan kos peralatan. Tetapi,

kawalan yang tidak sesuai dan persekitaran boleh menjurus kecacatan bahan,

kepincangan tugas mesin malahan malapetaka. Maka, tujuan kajian ini adalah untuk

melaksanakan idea bersandar enam sigma untuk mengoptimumkan keadaan

pemotongan laser dan memanjangkan hidup perkhidmatan mesin pemotong laser.

Seluruh disertasi akan dikelilingi dalam mengoptimumkan mesin parameter untuk

EPILOG Legend 36Ext - Model 9000 mesin pemotong laser di makmal FKM dengan

menggunakan pendekatan DMAIC. Dan, keseluruhan idea mengoptimumkan kawalan

tersirat di Lean Six Sigma metodologi yang ringkaskan di singkatan (DMAIC): Takrif,

Ukur, Analisa, Tambah Baik dan Kawal. Terlebih dahulu, satu senarai penyataan

masalah telah dibina untuk menjelaskan objektif projek yang dikaji. Kedua, suatu

gambar rajah pemetaan proses telah dibina untuk menjadi gambaran bagi keseluruhan

sistem pengurusan penyenggaraan supaya mengukur percanggahan antara kakitangan

dan aliran maklumat dari peringkat pengurusan berkaitan. Ketiga, perisian seperti

MATLAB telah digunakan untuk membentuk hubungan antara parameter memotong

dengan kualiti memotong spesimen-spesimen akrilik. Keempat, penyelesaian bagi

disfungsi telah dicadangkan dan keadaan optimum telah dibina dengan menggunakan

perisian Design Expert. Kelima, suatu amalan piawaian seperti SOP (standard

prosedur) dibangunkan untuk menggantikan prosedur memesin semasa. Akhirnya,

rancangan seterusnya dipantau supaya memastikan peningkatan secara mampan.

Selepas melaksanakan DMAIC, ia telah didapati bahawa maklumat diberi oleh buku

panduan pembekal seharusnya disemak secara berterusan kerana parameter dan

bahagian mesin dijangka merosot dari semasa ke semasa. Manfaat menyemak SOP

mungkin membantu makmal FKM menjimatkan kos dalam pembaikan mesin.

vii

TABLE OF CONTENTS

CHAPTER

TITLE PAGE

DECLARATION ii

DEDICATION iii

ACKNOWLEDGEMENT iv

ABSTRACT v

ABSTRAK vi

TABLE OF CONTENTS vii

LIST OF TABLES x

LIST OF FIGURES xi

LIST OF ABBREVIATIONS xv

LIST OF SYMBOLS xvii

LIST OF APPENDICES xix

1 INTRODUCTION 1

1.1 Overview 1

1.2 Background of Study 2

1.3 Research Problem 4

1.4 Research Objectives 5

1.5 Scope of Study 5

1.6 Significance of Study 6

2 LITERATURE REVIEW 7

2.1 A Brief Review on Lean Six Sigma 7

2.2 Process Optimization by Using DMAIC 8

2.3 Introduction to DMAIC 9

2.4 The Implementation of DMAIC Approach 11

viii

2.5 Quality Assessment and Optimize Control 14

2.5.1 Quality Assessment and Optimize Control

for Carbon Dioxide Laser Cutting of

Polymeric and Metallic Materials

15

2.6 General Types of Maintenance 17

2.6.1 Preventive Maintenance 17

2.6.2 Predictive Maintenance 18

2.6.3 Corrective Maintenance 19

2.6.4 Breakdown Maintenance 19

2.7 Modern Quality Maintenance Management

Systems and Strategy

19

2.7.1 Lean Maintenance 20

2.7.2 Total Quality Management 20

2.7.3 Lean Six Sigma for Maintenance

Management

20

2.8 Mathematical Modelling of Laser Machining 21

3 METHODOLOGY 23

3.1 Methodology of Research 23

3.2 The Implementation of DMAIC Methodology 25

3.3 Define Phase 27

3.4 Measure Phase 28

3.5 Analyze Phase 28

3.6 Improve Phase 30

3.7 Control Phase 31

3.8 Equipment and Instrumentations 33

3.9 Software 34

3.10 Workpiece Specification 34

3.11 Factorial Design 34

4 RESULTS AND ANALYSIS 36

4.1 Implementing DMAIC Approach for Single-unit

Machine

36

ix

4.2 A Case Study of Machine Maintenance Strategies

for EPILOG Laser Cutting Machine

36

4.3 An Overview of the Current Maintenance

Strategies for Epilog Laser Cutting Machine

37

4.4 Define Phase 38

4.5 Measure Phase 39

4.6 Analyse Phase 40

4.6.1 Experimental Analysis 42

4.6.2 Failure Mode and Effect Analysis 57

4.7 Improve Phase 58

4.7.1 Acrylic with Removed Protective Layer 59

4.7.2 Acrylic with Unremoved Protective Layer 75

4.8 Control Phase 85

4.9 Entrepreneurial Aspects 87

4.10 Improvement 89

5 CONCLUSIONS 91

REFERENCE 92 - 95

BIBLIOGRAPHY 96 - 97

APPENDIX A - O 98 – 123

GHANTT CHART 124

x

LIST OF TABLES

TABLE NO.

TITLE PAGE

2.1 Comparison between Lean and Six Sigma 8

2.2 Key Improvement Steps from DMAIC Methodology 10

2.3 Table of Definitions and Tools for each DMAIC Phases 14

3.1 List of Equipment and Instrumentations 33

3.2 Follow-up Experimentation 35

4.1 Design Matrix for 4mm Thickness Specimen 60

4.2 Kerf Width Experiment for 4mm Thickness Specimen 60


4.4 Results for Depth for 4mm Thickness Specimen 70

4.5 Kerf Width Experiment for 5mm Thickness Specimen 76


4.7 Results for Depth for 5mm Thickness Specimen 81

xi

LIST OF FIGURES

FIGURE NO.

TITLE PAGE

1.1 8 Forms of Waste 4

2.1 Illustration of DMAIC Approach 10

2.2 Classical Tools for DMAIC Methodology 11

3.1 Framework of Research Methodology 25

3.2 High-Level DMAIC Methodology 26

3.3 SIPOC Diagram for Making a Coffee 27

3.4 Value Stream Mapping Diagram 28

3.5 Cause and Effect Diagram 29

3.6 FMEA Table Diagram 30

3.7 Additional Improvement Phases 31

3.8 Factorial Design 31

3.9 Benchmarking Workpiece 32

3.10 EPILOG Legend 36EXT Laser Cutting Machine 33

4.1 Result from SIPOC Diagram 39

4.2 Result from Value Stream Mapping Diagram 40

4.3 Result from Cause and Effect Diagram on EPILOG

36Ext

41

4.4 Recommend Settings by the Supplier 42

4.5 Acrylic Specimen 43

4.6 Comparison of Wavy and Straight Cutting Edge 44

4.7 A 5mm Thickness Acrylic with Paper Protective Layer 45

4.8 A 5mm Thickness Acrylic with Removed Paper

Protective Layer

46

4.9 Depth of Cut Specimen 46

4.10 Burr 47

xii

4.11 Overlap of HAZ from Subsequent Cutting 47

4.12 Observation of Surface Roughness from Different Stand-

off Distance

48

4.13 Effect of Stand-off Distance towards the Quality of Cut 48

4.14 Raster and Vector Cutting Mode 49

4.15 Surface Damage in Vector Cutting Mode 50

4.16 Measurement of Kerf Width 50

4.17 Kerf Width versus Speed for 4mm Thickness Acrylic

when P = 100%, Varied Frequency

51


when f = 5000 Hz, Varied Power

52



53


when f = 5000Hz, Varied Power

53

4.21 Measurement of Depth of Cut 54

4.22 Depth of Cut versus Speed for 5mm Thickness Acrylic


54



55



56



56

4.26 Result from FMEA Table 58

4.27 A 5 by 4 Inches Acrylic Specimen for Experiment

Purpose

59

4.28 ANOVA Table for 4mm Thickness Specimen 61

4.29 Result from R2 Statistic for 4mm Thickness Specimen 61

4.30 Effect of Input Parameters on Kerf Width (a) Speed-

Power (b) Speed-Frequency (c) Power-Frequency

Relationship

62

4.31 Half Normal Plot for 4mm Thickness Specimen 63

xiii

4.32 Normal Plots of Residuals for 4mm Thickness Specimen 64

4.33 Residuals vs. Predicted Plot for 4mm Thickness

Specimen

65

4.34 Residuals vs. Run for 4mm Thickness Specimen 66

4.35 Outliner T Plot for 4mm Thickness Specimen 67

4.36 Cube Graph for 4mm Thickness Specimen 68

4.37 Result of Computational Optimization for 4mm

Thickness Specimen

69

4.38 Model Summary Statistics for 4mm Thickness Specimen 71


4.40 Effect of Input Parameters on Depth of Cut for Speed-

Power Relationship

72

4.41 Normal Plots of Residuals for 4mm Thickness Specimen 73

4.42 Outliner T vs. Run Number for 4mm Thickness

Specimen

73


4.44 Residual vs. Power Plots 75


4.46 Effect of Input Parameters on Kerf Width (a) Speed-

Power (b) Speed-Frequency (c) Power-Frequency

Relationship

77

4.47 Speed-Power Interaction Plot for 5mm Thickness

Specimen

78

4.48 Speed-Frequency Interaction Plot for 5mm Thickness

Specimen

78

4.49 Power-Frequency Interaction Plot for 5mm Thickness

Specimen

79


4.51 Residuals vs. Power Plot 80

4.52 Model Summary Statistics for 5mm Thickness Specimen 82


4.54 Effect of Input Parameters on Depth of Cut for Speed-

Power Relationship

83

xiv

4.55 One Factor Plot 84


4.57 Example of Machining Parameter 85

4.58 Computerized Maintenance Management System

(CMMS)

88

4.59 DMAIC Close-feedback Loop 89

4.60 Highlight the Cutting Zone Area by Marker Pen 90

xv

LIST OF ABBREVIATIONS

5S - Sort, Straighten, Scrub, System, Standardize

ANOVA - Analysis of Variance

CMMS - Computer Managed Maintenance System

CO2 - Carbon Dioxide

CTQ - Critical to Quality

CW - Continuous Wave

DMADV - Define, Measure, Analyze, Design, Verify

DMAIC - Define, Measure, Analyze, Improve, Control

DMARC - Define, Measure, Analyze, Redesign, Control

DOC - Depth of Cut

DOE - Design of Experiment

DOWNTIME - Defect, Overproduction, Waiting, Non-utilized Talent,

Transportation, Inventory, Motion, Extra-Processing

DPMO - Defects Per Million Opportunities

EAM - Enterprise Asset Management

FKM - Fakulti Kejuruteraan Mekanikal

FMEA - Failure Mode and Effect Analysis

FREQ - Frequency

GE - General Electric

HAZ - Heat Affected Zone

ISO - International Organization for Standardization

LHS - Left Hand Side

PRESS - Predicted Residual Sum of Squares

PW - Power

PWR - Power

Nd-YAG - Neodymium-doped Yttrium Aluminum Garnet (Nd: Y3Al5012)

R2 - R Square

xvi

RCFA - Root Cause Failure Analysis

RCM - Reliable Centered Maintenance

RHS - Right Hand Side

RPN - Risk Priority Number

RSM - Response Surface Method

SEM - Scanning Electron Microscope

SIPOC - Supplier, Input, Process, Output, Customer

SOP - Standard of Procedure

SP - Speed

TPM - Total Productive Maintenance

TPS - Toyota Production System

TQM - Total Quality Maintenance

WCM - World Class Maintenance

XRD - X-Ray Diffraction

xvii

LIST OF SYMBOLS

𝛼 - Thermal Diffusivity

𝑎 - Absorbability Percentage

𝑐𝑝 - Specific Heat

𝐷 - Depth of Cut

exp - Exponential

f - Frequency

h - Material Thickness

k - Thermal Conductivity

𝐾0(𝑥) - Modified Bessel Function of Second Kind of zero order

𝐿𝑚 - Latent heat of fusion per unit mass temperature

𝑚𝑎 - Mass

ℕ+ - Natural Numbers

𝜋 - Pi

𝑃 - Power

q - Heat Flux

𝑞𝑎 - Total Laser Power

𝑄 - Specific Heat

𝑄𝑎 - Absorbed Energy

𝑄1 - Energy lost by conduction, convection and radiation

𝜌 - Density of Workpiece

𝑅 - Beam Radius

r - Radial Distance from Origin

t - Total Cutting Time

T - Temperature

𝑇0 - Ambient Temperature

∆𝑇𝑚 - Change of melting Temperature with respect to Ambient Temperature

∆𝑇𝑣 - Change of vaporization temperature with respect to ambient

xviii

𝑢𝑥 - Traverse Velocity of Heat Source in x – direction

𝑢𝑐 - Cutting Speed

𝑉 - Volume of Cut

𝑉𝑠 - Laser Speed

𝑤𝑘 - Kerf Width

∅ - Unknown Analytic Function

𝜑 - Linear Transformation of x Coordinates

z - Z - direction from Workpiece

𝜕𝑇

𝜕𝑧 - Rate of change of temperature in z – direction

𝜕𝑇

𝜕𝑦 - Rate of change of temperature in y – direction

𝜕𝑇

𝜕𝜑 - Rate of change of temperature in x – direction

𝜕𝑇

𝜕𝑟 - Rate of change of temperature in r – direction

xix

LIST OF APPENDICES

APPENDIX TITLE PAGE

A Kerf Width vs. Speed at Various Power &

Frequency for t = 4mm Specimen

96

B Kerf Width vs. Speed at Various Frequencies

and Powers for t = 4mm Specimen

98

C Kerf Width vs. Speed at Various Powers and

Frequencies for t = 5mm Specimen

100

D Kerf Width vs. Speed at Various Frequencies


102

E DOC vs. Speed at Various Powers and

Frequency for t = 5mm Specimen

104

F DOC vs. Speed at Various Frequencies and

Powers for t = 5mm Specimen

106

G DOC vs. Speed at Various Powers and

Frequencies for t = 4mm Specimen

108

H DOC vs. Speed at Various Frequencies and

Powers for t = 4mm Specimen

110

I Table Kerf Width vs. Speed at Various

Frequencies and Powers for t = 4mm Specimen

112

J Table Kerf Width vs. Speed at Various

Frequencies and Powers for t = 5mm Specimen

113

K Table DOC vs. Speed at Various Frequencies


114

L Table DOC vs. Speed at Various Frequencies


115

M Laser Engraving Techniques 116

N SIPOC Diagram 120

xx

O Cause and Effect Diagram 121

CHAPTER 1

INTRODUCTION

1.1 Overview

The rapid growth of economics since last two decades has brought out a brand

new perspective which emphasizes on quality rather than increase productivity. This

can be observed through several conditions such as, demand for high quality products,

growth of competitors, reduce waste, shorten lead time, customer oriented, increase

profitability, etc. Hence, a new concept is necessary to enlarge the quality assessment

in manufacturing factors due to global competition. Consequently, it led to the birth of

total quality management (TQM) and its by-products such as ISO 9000, DMAIC and

Lean Six Sigma. Those ideas highlighted the importance of organization-wide effort

and its capability to produce high quality products at lowest cost. Besides that, those

concepts have their common features such as redefined the concept of quality, require

involvement from top to floor management, customer oriented, streamlining principles,

and robust to variations.

TQM is a continuous effort of an organization to implement awareness

regarding continuous improve its ability to produce quality product to the end users.

Moreover, TQM had eventually penetrated into both business and management

strategy to enhance both business and management process in an organization. The

methodology of implementing TQM is called Lean Six Sigma DMAIC or DMAIC

alone. DMAIC is a streamlining process or framework to conduct any Six Sigma

projects. Also, DMAIC is a data driven process and its improvement process can be

either open, close or cycle loop. The application of DMAIC can be found in most of

2

the industry such as biomedical, construction, services, mechanical, maintenance etc.

which seek for a sustainable and improved solutions to a problems. DMAIC approach

also aims to optimize process, robust control, and to revise current methods or

strategies for various case studies in industries.

Tough economic conditions and rapidly rising costs continue to strain higher

education institutions’ budgets, especially for machinery maintenance operations. [a]

Hence, the well-known DMAIC approach could be used to provide deepen insights

into machining process in order to reduce the probability of machine failure results by

both human and procedural errors. Eventually, it helps to reduce maintenance budget

through optimizing machining process rather than in house maintenance alone.

1.2 Background of Study

Lean six sigma is a methodology that relies on a collaborative team effort to

improve performance by systematically removing waste; combining lean

manufacturing or lean enterprise and Six Sigma to eliminate the eight kinds of waste:

defects, overproduction, waiting, non-utilized talent, transportation, inventory, motion,

extra-processing which summarized in the acronym (DOWNTIME). [b] Lean mindset

was first distinguished through viewers of the Toyota Production System (TPS) in

early of the 1940s, which highlighted a context of eliminating waste with the goal of

creating value. [c] Lean thinking has substituted the conventional of manufacturer

“push” to customer “pull” process such that produce on the basis of customers’

demand. A broader sense of lean thinking underlies on developing reasoning ability

rather than force them accomplished tasks in a ready-made deriving system. Lean

thinking implied a flexible response, knowledge drive, and continuous improvement

among individual in order to achieve a common goal of an organization. Six Sigma

was first initiated by the CEO of General Electric (GE), Jack Welsh as central of his

business development strategies. The idea was emphasized on quality improvement

effort which was aligned to the needs of the business. [1] Six sigma explores the

possibility of improving output by identifying the cause as well as minimizing the

3

variability in the process. The approach of implementing Six Sigma involves the use

of statistical and non-statistical tools to evaluate a structured system or an environment

for the purpose of creating higher quality output. For so many years, Lean advocated

Six Sigma did not directly clarify speed, flow and waste. Meanwhile, Six Sigma

pointed out that Lean approach is not able to solving variability and optimizing issues

[2]. Hence, one unified approach emerges when Lean cooperate with Six Sigma to

compromise each other.

Lean Six Sigma is a long-term project based approach which lasts for several

months and the key to success rely on the proper techniques for a given problem. The

integration of Lean and Six Sigma has provided by seven principles as shown below:

i. Focus on customer (customer pull or customer driven process) [3]

ii. Identified and understand the overall processes include how the job has

been done [3]

iii. Manage, improve and smooth the process flow by developing reasoning

among individuals [3]

iv. Eliminate non value added process or waste [3]

v. Reduce the cause of variability [3]

vi. Involve and equip the people in the process by way of managing the

human aspects. [3]

vii. Embark improvement activities in a systematical way [3]

There are three well-known approaches which well described the “five phase – seven

principle” of Lean Six Sigma project methodology and they are:

i. DMAIC (Define – Measure – Analyze – Improve – Control)

ii. DMADV (Define – Measure – Analyze – Design – Verify)

iii. DMARC (Define – Measure – Analyze –Redesign – Control)

However, the backbone of the entire dissertation was enclosed with DMAIC

methodology which were used to describe the laser machining capability of EPILOG

Legend 36 Ext Laser Cutting Machine. And, the outcome is to optimize machining

parameters of this machine. The distinguishing between DMAIC and DMADV

depends on the consideration of redesign on existing process in order to meet the level

4

of customer specification. Occasionally, the application of DMAIC was treated as a

strategic to provide a total solution in enhancing processes while reducing wastes as

shown in Figure 1.1 in normal operation under economic stakes.

Figure 1.1 8 Forms of Waste [d]

1.3 Research Problem

The entire research in this dissertation would be devoted to analyze the

potential causes of failure for one of the laser cut machines, namely EPILOG

LEGEND 36 EXT 9000 Series in the FKM fabrication lab. The machine has several

serious recorded malfunction and break down event since 2014. Also, the accumulated

maintenance overhead costs incurred over the past two years were roughly about RM

10,000. And, most of the expenditure are predominated by maintenance services

provided by outside vendors. This decision apparently inevitable since it involved

5

replacement of crucial parts from sole distributor outside the country. Hence, the only

way to do is to limit the amount of usage.

However, the most interesting is breakdown event still remains high even

though the malfunction parts has replaced. And, there’s no evidence shows any results

of maintenance negligence. In this scenario, machining operation and procedure may

become the focus of attention.

A quality system often demands a documentation which clarifies regular and

standardized operation. However, there is a lack of information regarding process

parameter, optimizing control and procedural in laser cut machining from supplier’s

manual. Hence, machining operations are under supervision for most of the times.

Occasionally, some laser cutting operation even required assistance from experienced

technicians. [4] For this reason, most of the research and machining process is

forbidden because the improper machining procedure and parameters may harmful to

the machine.

1.4 Research Objectives

To optimize cutting parameters of acrylic on EPILOG Legend 36Ext by using

Lean Six Sigma and develop Standard Operating Procedure (SOP) and maintenance.

1.5 Scope of Study

The scope of study of this project is summarized as follows:

i. To examine the cause of failure for EPILOG Legend 36Ext laser cutting

machine via DMAIC, a Lean Six Sigma methodology.

ii. Only one of the most influential factors which affect the overall

performance will be determined from analyze phase and to be studied.

6

iii. Optimum cutting parameter, machine settings, and standard of procedure

will be developed for acrylic material.

iv. To improve and revise the existing machining strategies in order to

ensure that the quality of cut will continuously improve and sustain.

1.6 Significance of Study

The primordial purpose of this study is to provide recommendations and

insights towards maintenance costs incurred in EPILOG Legend 36Ext laser cutting

machine. Moreover, the importance of this study addresses the essential of shifting

focus from a business strategy tool into a standardized machining strategy through

optimizing machining process. However, the ideas were set forth from lean six sigma

standpoint, which was often regarded as a business strategic for improving enterprise

profitability. [5]

Second, this study also provides a deepen insight towards lean six sigma

methodology and its capability to eliminate nonproductive elements in maintenance

management. The constructive mapping process enables maintenance staff and

management level understand the essence of customer pull (student oriented) process

and inspiration of creating improvement, control and maintenance plans.

Third, the idea of DMAIC is analogue to a brainstorming process equipped

with rigorous statistical tools which is economical instead of long term spending on

seeking advices. The results obtained from the process, not merely to enhance the

overall performance, but useful for publishing journals.

Eventually, perhaps the ideas of Lean Six Sigma could turn out to be a common

practice among individuals in a higher local educational institution and a relief to the

strain of budget.

92

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OPTIMIZATION OF LASER CUTTING PARAMETER OF …eprints.utm.my/id/eprint/53535/1/ChuaYongPingMFKM2015.pdf · part nesting, time saving and low cost tooling. But, inappropriate control