Achieving Quality Improvement in the
Mask Manufacturing Industry by Using
Six Sigma Technique

Submitted to:
Science and Engineering Faculty
School of Chemistry, Physics and Mechanical Engineering
Queensland University of Technology

Submitted by: Wei-Fen Chiu
Research student
Queensland University of Technology

4th April 2012


Acknowledgements
Time flies, and the life of researching seems to be a challengeable but impressive
journey. I had a great time within the period of time since I have not only absorbed
and comprehended more in the particular area of knowledge but made friends with
some wonderful people who helped and supported me to accomplish my thesis.
First of all, I would like to offer my gratitude to my three supervisors Associate
Professor YuanTong Gu, Dr Azharul Karim and Professor Lin Ma. Thank you for
supporting and believing in me from beginning to end with your passion and
dedication. I also wish to thank you for always encouraging me to express my ideas
into my thesis with constructive feedback and positive praise. I am delighted with
having a good relationship with these two supervisors. They are not only my
supervisors but also my good friends inasmuch as they let me have absolute liberty
during the time and we would chat about everything like friends.
Secondly, I would like to acknowledge my lovely parents, Shaw-Kou Chiu and PaoChao Yu, and my three sisters, who are Wei-Yi Chiu, Wei-Hsuan Chiu, and Wei-Chih
Chiu. I appreciate them supporting and encouraging me spiritually and practically

with their constant love and wisdom. To satisfy my material requirements, Dad has
been working very hard overseas, and thereby, Mom has been flying laboriously
between two countries every two months in order to take care of us physically and
psychologically. Thank you for my three beautiful sisters who make my research life
interesting and happy with their smiles and thoughtfulness.
Thirdly, I would like to thank my friends in the research office. Thank you for
providing considerable and useful information and generous friendships. It is my
fortune to have met all my excellent researching friends. Finally, thank you
Queensland University of Technology for providing a marvellous researching
environment and also the staff at the Research Support Office for always helping me
when I needed it.

I


Abstract
The Six Sigma technique is one of the quality management strategies and is utilised
for improving the quality and productivity in the manufacturing process. It is
inspired by the two major project methodologies of D
P
Do Check
A PDCA C
which consists of DMAIC and DMADV. Those two methodologies
are comprised of five phases. The DMAIC project methodology will be
comprehensively used in this research. In brief, DMAIC is utilised for improving the
existing manufacturing process and it involves the phases Define, Measure, Analyse,
Improve, and Control.
Mask industry has become a significant industry
outbreak of some serious diseases such as the Severe Acute Respiratory Syndrome
(SARS), bird flu, influenza, swine flu and hay fever. Protecting the respiratory system,

then, has become the fundamental requirement for preventing respiratory deceases.
Mask is the most appropriate and protective product inasmuch as it is effective in
protecting the respiratory tract and resisting the virus infection through air. In order
thousands of mask products are
designed in the market. Moreover, masks are also widely used in industries
including medical industries, semi-conductor industries, food industries, traditional
manufacturing, and metal industries. Notwithstanding the quality of masks have
become the prioritisations since they are used to prevent dangerous diseases and
safeguard people, the quality improvement technique are of very high significance
in mask industry.
The purpose of this research project is firstly to investigate the current quality
control practices in a mask industry, then, to explore the feasibility of using Six
Sigma technique in that industry, and finally, to implement the Six Sigma technique
in the case company to develop and evaluate the product quality process. This
research mainly investigates the quality problems of musk industry and
effectiveness of six sigma technique in musk industry with the United Excel
Enterprise Corporation (UEE) Company as a case company. The DMAIC project
methodology in the Six Sigma technique is adopted and developed in this research.
This research makes significant contribution to knowledge. The main results
contribute to the discovering the root causes of quality problems in a mask industry.
Secondly, the company was able to increase not only acceptance rate but quality
level by utilising the Six Sigma technique. Hence, utilising the Six Sigma technique
could increase the production capacity of the company. Third, the Six Sigma
technique is necessary to be extensively modified to improve the quality control in
the mask industry. The impact of the Six Sigma technique on the overall
performance in the business organisation should be further explored in future
research.

II



Certification of Thesis
The work contained in this thesis has not been previously submitted for a degree or
diploma at any other higher education institution. To the best of my knowledge and
belief, this thesis contains no material previously published or written by another
person except where due reference is made.

Wei-Fen Chiu
4th April 2012

III


PREFACE
During the course of this project, one journal paper has been published and another
journal paper is being submitted for publication. They are listed here for reference.
JOURNAL PUBLICATIONS

1. WeiFen Chiu, YuanTong Gu, M.A.Karim and Lin MA, A modified quality control
method for manufacturing process in mask industry, Advanced Materials
Research Vols. 139-141 (2010) pp 1843-1846 (ERA ranking B)
JOURNAL PAPER UNDER PREPERATION

2. WeiFen Chiu, YuanTong Gu, M.A.Karim and Lin MA, Improving Quality Control
methodology in the Mask Industry by implementing the Six Sigma Technique,
Advanced Materials Research (ERA ranking B)
3. WeiFen Chiu, YuanTong Gu, M.A.Karim and Lin MA, The Enhanced Quality
Control for Six Sigma Technique in Mask Industry, publish with InTech in the
book project under the working title "Manufacturing System"


IV


Contents
Page Number
1. THESIS TITLE ....................................................................................................... IX
2.

PROJECT SUPERVISORS ................................................................................... IX

CHAPTER 1 INTRODUCTION ................................................................................ - 1 1.1
1.2
1.3
1.4

RESEARCH FRAMEWORK AND BACKGROUND ...................................................... - 1 PROBLEM STATEMENT, RESEARCH QUESTION AND RESEARCH OBJECTIVE .................... - 2 RESEARCH METHOD .................................................................................... - 5 OUTLINE OF THIS THESIS .............................................................................. - 6 -

CHAPTER 2 LITERATURE REVIEW ......................................................................... - 8 2.1
THE HISTORY OF THE SIX SIGMA TECHNIQUE ..................................................... - 8 2.1.1 The Six Sigma technique in practise................................................... - 9 2.2
THE QUALITY MANAGEMENT SYSTEMS............................................................ - 12 2.2.1 Total Quality Management (TQM) .................................................. - 12 2.2.2 The difference between the Six Sigma technique and the Total Quality
Management (TQM)................................................................................... - 13 2.2.3 Basics for Six Sigma technique ........................................................ - 15 2.2.4 The Six Sigma technique principles .................................................. - 17 2.3
THE SIX SIGMA TECHNIQUE METHODS ........................................................... - 18 2.3.1 The DMAIC method for the Six Sigma technique.............................. - 18 2.3.2 The DMADV method for the Six Sigma technique ............................ - 19 2.3.3 The Comparison between two methods .......................................... - 20 2.4
IMPLEMENTATION ROLES FOR THE SIX SIGMA TECHNIQUE ................................... - 21 2.5
USEFUL TOOLS AND METHODOLOGIES FOR THE SIX SIGMA TECHNIQUE ................... - 24 2.5.1 Failure Mode and Effects Analysis (FMEA) ....................................... - 24 2.5.2 Fault Tree Analysis (FTA) ................................................................. - 25 2.5.3 Flow Chart ...................................................................................... - 26 2.5.4 Histogram ....................................................................................... - 27 2.5.5 Pareto Diagrams ............................................................................. - 28 2.5.6 Cause and Effect Diagrams ............................................................. - 29 2.5.7 Control Chart .................................................................................. - 30 2.6
METHODS FOR OBTAINING THE DATA ............................................................. - 31 2.7
THE SIX SIGMA TECHNIQUE IN MASK INDUSTRY ................................................ - 34 2.8
CONCLUSION ........................................................................................... - 35 CHAPTER 3 QUALITY PROBLEMS IN THE MASK INDUSTRY A CASE STUDY ...... - 36 3.1
INTRODUCTION ........................................................................................ - 36 3.2
COMPANY BACKGROUND ............................................................................ - 36 3.2.1 Product Background........................................................................ - 37 3.3
PRODUCTION PROCESS IN CASE ORGANISATION ................................................ - 39 3.4

QUALITY CONTROL IN UEE.......................................................................... - 50 3.4.1 Quality control issues ...................................................................... - 50 V


CHAPTER 4 ROOT CAUSES OF QUALITY PROBLEMS IN CASE ORGANISATION .... - 54 4.1
INTRODUCTION ........................................................................................ - 54 4.2
SURVEY OF UEE MANAGEMENT AND EMPLOYEES ............................................. - 56 4.3
USE OF SIX SIGMA TOOLS TO IDENTIFY CAUSES OF QUALITY PROBLEMS .................... - 58 4.3.1 Cause and effect diagram ............................................................... - 59 4.3.2 Pareto chart.................................................................................... - 61 4.4
PRODUCTION DATA ANALYSIS ....................................................................... - 63 4.5
CONCLUSION ........................................................................................... - 73 CHAPTER 5 IMPROVING QUALITY USING THE SIX SIGMA TECHNIQUE .............. - 74 5.1
5.2
5.3
5.4
5.5

EMPIRICAL FINDINGS ................................................................................. - 74 STEP OF IMPLEMENTATION THE SIX SIGMA TECHNIQUE ....................................... - 76 THE SIX SIGMA TEAM IN THE UNITED EXCEL ENTERPRISE (UEE) CORPORATION........ - 78 RESULTS OF CASE IMPROVEMENT .................................................................. - 80 SUMMARY .............................................................................................. - 89 -

CHAPTER 6 CONCLUSION................................................................................... - 90 6.1
6.2
6.3
6.4
6.5
6.6

SUMMARY OF THE RESEARCH ....................................................................... - 90 CONCLUSIONS ABOUT RESEARCH QUESTIONS ................................................... - 93 CONCLUSIONS REGARDING THE RESEARCH PROBLEM .......................................... - 96 RESEARCH EVALUATION FOR THE MASK INDUSTRY.............................................. - 98 RESEARCH LIMITATIONS .............................................................................. - 99 RECOMMENDATION AND FUTURE RESEARCH .................................................. - 100 -

REFERENCES .................................................................................................... - 102 APPENDIX A - THE SYMBOL OF MASK PRODUCTION ....................................... - 113 APPENDIX B - SAMPLING CONTROL METHOD ................................................. - 115 APPENDIX C - SAMPLE OF INTERVIEWS ........................................................... - 116 -

VI



List of Figures
Page Number
Figure 1:
Figure 2:
Figure 3:
Figure 4:
Figure 5:
Figure 6:
Figure 7:
Figure 8:
Figure 9:
Figure 10:
Figure 11:
Figure 12:
Figure 13:
Figure 14:
Figure 15:
Figure 16:
Figure 17:
Figure 18:
Figure 19:
Figure 20:
Figure 21:
Figure 22:
Figure 23:
Figure 24:
Figure 25:
Figure 26:
Figure 27:
Figure 28:


The six sigma diagram ................................................................ - 17 DMAIC cycle ............................................................................... - 19 DMADV cycle ............................................................................. - 20 Levels of roles ............................................................................ - 23 FTA symbols ............................................................................... - 26 Flow chart symbols .................................................................... - 27 Example of histogram................................................................. - 28 Example for Pareto Diagram ........................................................ - 29 Example for Cause and Effect Diagram ....................................... - 30 Example of a Control Chart ........................................................ - 31 raw material Input process.......................................................... - 41 The process linking the company with its customers ................... - 42 Simplified depiction of output process ........................................ - 43 The process between purchase department and customers........ - 45 The whole production process for the mask company ................ - 47 Process for manufacturing masks ................................................ - 49 Theoretical Model for this thesis ................................................. - 55 Fishbone diagram for identifying defective products. .................. - 60 A Pareto chart of the main causes of defects............................... - 62 The p chart for finished goods in July 2009 ................................. - 68 The p chart for semifinished goods in July 2009 .......................... - 69 The P chart of total production in July 2009. ............................... - 72 Empirical Findings and Analysis ................................................... - 75 The lifecycle for implementing the Six Sigma technique .............. - 76 The Six Sigma deployment model ............................................... - 77 The p values for finished goods after improvement..................... - 83 The semi finished goods data after improvement. ...................... - 84 The total goods after improvement ............................................. - 85 -

VII


List of Table
Page Number
Table 1:
Table 2:
Table 3:
Table 4:
Table 5:
Table 6:
Table 7:
Table 8:
Table 9:
Table 10:
Table 11:
Table 12:
Table 13:
Table 14:
Table 15:
Table 16:
Table 17:

The sigma scale............................................................................... - 16 Comparison of DMAIC and DMADV................................................ - 21 FMEA calculation diagram............................................................... - 24 The classification of quality level for product quality. ..................... - 44 Weekly data for finished goods in July 2009 .................................... - 64 Weekly data for semifinished goods in July 2009 ............................ - 64 The proportion of finished goods in July 2009 ................................. - 65 The proportion of semifinished goods in July 2009 ......................... - 66 The CL, UCL and LCL for finished goods in July 2009. ....................... - 67 The CL, UCL and LCL for semifinished goods in July 2009. ............ - 68 Summary of July production in 2009 ........................................... - 71 The finished goods after improvement in July 2010 .................... - 81 The semi finished goods after improvement in 2010. .................. - 81 Summary of production after improvement in July of 2010 ........ - 86 Comparison of total goods data .................................................. - 87 The comparison for the case study. ............................................. - 88 Summary of results in the case ................................................... - 92 -

VIII



1. Thesis Title
Achieving Quality Improvement in the Mask Manufacturing Industry by Using the
Six Sigma Technique

2. Project Supervisors
Principal Supervisor: Associate Professor YuanTong Gu
School of Engineering Systems
Faculty of Built Environment and Engineering
Queensland University of Technology (QUT)
Associate Supervisor: Dr. Azharul Karim
School of Engineering Systems
Faculty of Built Environment and Engineering
Queensland University of Technology (QUT)
Associate Supervisor: Professor Lin Ma
School of Engineering Systems
Faculty of Built Environment and Engineering
Queensland University of Technology (QUT)

IX


CHAPTER 1 INTRODUCTION
In this chapter, the research framework is discussed first. The research problem,
research question and research objective are then explained. The next section
presents the research methodology. The outline of this thesis is given at the end of
chapter.

1.1


Research framework and background

For industry, quality has been an essential issue since World War II, and therefore,
improving quality has become an important business tactic for many organisations
including those involved in manufacturing, distribution, transportation, financial
services , health care, and government (Amasaka, 2000; Wienclaw, 2008c). In
engineering and manufacturing organisation, quality control and quality
management techniques are used to ensure products or services meet or exceed
customer requirements.

The most important
products and related services. Companies with superior quality products are more
competitive and are likely to have a larger market share (Azis & Osada, 2010).
Gradually, the demand for higher quality products is increasing because of a
competitive environment and rapidly improving technologies (Anil, Joe, & Jean,
2009).

Quality products need to be made economically so that they can compete in the
market. End products or services need to meet or exceed company goals (McCuiston
& DeLucenay, 2010). Producing high-quality products is also a competitive tool that
can result in considerable advantage to organisations. A business that can delight
customers by improving and controlling quality has the potential to dominate its
competitors. Developing an effective quality strategy is a factor in long-term
business success (Mast, 2004; Mast, Schippers, Does, & Heuvel, 2000).
-1-


The mask manufacturing industry has become an important sector due to the
spread of diseases like Severe Acute Respiratory Syndrome (SARS), bird flu, swine flu
and influenza. Covering the mouth is based on the need to ensure the prevention of

respiratory diseases (Centre for Disease Control, 2011; Organization, 2011). Masks
have been widely utilised both in industrial and domestic environments. In industry,
the product is essential for employees who perform tasks in environments which
involve potential hazards from inhaling harmful substances. Types of masks differ in
the materials they are made from, and in techniques of manufacturing. Producing
a

The applications for different types of masks can number in thousands. Clients need
to choose the masks which are most appropriate to their working environments. For
example, employees who work in hospitals select masks with high chemical and
bacterial resistance, whereas for workers on construction sites, need masks with
high protection from dust are needed.

Quality control is a key concern in mask industry. In recent decades, many types of
quality control methodologies have been developed, investigated and implemented.
They include the Seven basic Quality Tools, Total Quality Management (TQM), the
International Standards Organization (ISO) documentation, Statistical Process
Control (SPC), lean manufacturing, just in time (JIT), quality function deployment
(QFD) and the Six Sigma technique (Wienclaw, 2008b). However, many of these
tools, particularly six sigma techniques have not been used in musk industry.

This research will investigate the quality control methodologies used in the mask
manufacturing industry.

1.2

Problem statement, research question and research objective

As discussed before, the purpose of quality control tools is to support the
manufacturing process, improve product quality and reduce the numbers of product

-2-


defects. Quality control is an important element in manufacturing management
(Wienclaw, 2008e). To choose and utilise good quality control tools is an important
task for businesses and manufacturing managers.

In the recent time several quality control (QC) techniques and tools have been
developed and applied. These techniques include Seven basic Quality Tools, Total
Quality Management (TQM), the International Standards Organization (ISO)
documentation, Statistical Process Control (SPC), lean manufacturing, just in time
(JIT), quality function deployment (QFD) and the Six Sigma technique. The ultimate
goal of these tools is to improve operational performance and obtain higher
customer satisfaction (Jones, Parast, & Adams, 2010; Moosa & Sajid, 2010).

The Six Sigma technique is one of quality management strategy and is utilised
improving the productivity and the profitability in the manufacturing process. Sigma
original from Greek letter which is a symbol of standard deviation in the
statistical analysis (Ayad, 2010). However, it represents the variability level of
products and the process of observation in the six sigma technique. Specifically, the
maximum number of effects is 3.4 per million opportunities at Six Sigma level and
the higher level of sigma represents the lower level of defective goods (Ayad, 2010;
Kumar, Saranga, Ramírez-Márquez, & Nowicki, 2007).

The Six Sigma management program is a project framework and it involves two
possible approaches (Ali, 2005; Jones, 2004) O
A

DMAIC


efine

DMADV

Majority of the Mask Industries are still using the traditional quality control
methodologies to minimise quality problems. For example, the total examination
and the random inspection are the two common quality control methodologies in
the Mask Industry. However, some manufacturing managers in the Mask Industry
are facing quality problems mainly because of the traditional quality control
-3-


techniques. Therefore, selecting a appropriate quality control technique is the prime

Quality strategies in mask industry have not been thoroughly investigated in the
past owing to the mask industry is an emerging but burgeoning manufacturing
industry in the market and therefore right quality technique for the industry has not
been identified. Although six sigma technique has been successfully applied in many
industries, it has not been implemented in mask industry. Therefore, the purpose of
this thesis is to address the research problem:

Is the Six Sigma technique an appropriate quality control methodology to improve
the entire performance in the mask industry?

To answer the research question, the following research questions were designed to
investigate and evaluate the performance of the six sigma technique in the mask
industry as flows:

Research question 1: What is the quality control (QC) process in a mask company?
Research question 2: What are the possible root causes of defective products?

Research question 3: How could these root causes be addressed?
Research question 4: What quality control tools and software packages are used in
the mask industry?

Therefore, the main objective of this research is to address the research questions
listed above and the ultimate goal is to investigate the use and effectiveness of the
traditional quality control method in mask industry, identify a higher performing
quality control tool and apply this tool to a mask company. Specifically, this research
will investigate and apply the Six Sigma technique and identify a suitable statistical
software tool and apply it to the mask industry.

-4-


The outcomes of the project will pave the way for modifications of the quality
control tool used in an actual case. In this research, the United Excel Enterprise
Corporation (UEE) was selected as the real case organisation.

The case study was selected as the most appropriate technique to collect primary
data in this thesis regarding the research questions defined in the earlier..

1.3

Research method

A number of researchers have discussed empirical research methodology in
operations management. Reid and Sander(Reid & Sanders, 2005) proposed a
systematic approach to conducting empirical research. They suggested that one
method, or a combination of several data collection methods, should be used in
conjunction with the research design.


In this study, the research problem was firstly emphasised from the literature and
an in-depth case study. It has been suggested in the literature that case studies can
be applied to the area of theory development as well as problem solving (Creswell,
2008; Ponterotto, 2005). In general, case studies are often preferred when
researchers have little control over the event and when the focus is on a
contemporary phenomenon in some real life context(Cavana, Delahaye, & Sekaran,
2001; Reid & Sanders, 2005). The case study method was selected after careful
consideration of several issues.

First, one key aim of the study is to empirically identify quality related difficulties in
mask industry. Manufacturing takes place in a complex environment. Hence, it is
critical to capture the experiences of the relevant people and the context of their
actions to better understand quality practices and related difficulties. Case studies
are particularly suitable for identifying the difficulties. Second, as the research deals
with the difficulties and challenges mask manufacturers are currently facing, this
research deals with a contemporary event(Edmondson & Mcmanus, 2007;
-5-


Ponterotto, 2005). Third, as this study investigates in detail the quality practices in
its real life settings, no control over the behaviour of the organisation within the
plant is possible.

This research aims to identify root causes of quality problems and suggest a quality
improvement method for mask industry. Case study was conducted to identify the
root causes of quality problem, to investigate the suitability of six sigma technique
and suggest a quality control methodology for mask industry.

1.4


Outline of this thesis

This thesis comprises six chapters to develop the knowledge of improving the
quality in the Mask Manufacturing Industry by using the Six Sigma technique with
case study analysis. The chapter are summarised as follows:

Chapter 1 introduces the overall picture of this study. To begin with, the research
framework and background were introduced, and the research question and
research objective were identified after that. Chapter one also outlines the research
methodology and research classification for this study.

Chapter 2 particularises the Six Sigma technique from both theoretical and practical
perspectives. The history of the Six Sigma technique is firstly presented with
empirical literature. The principles and the methods of the Six Sigma technique then
are discussed later in this chapter.

Chapter 3 addresses the quality problems in the Mask Industry by analysing chosen
company, the United Excel Enterprise Corporation (UEE), as a case study in this
research. The research objectives and research questions are defined the following
explanation of mask industry in Taiwan.

Chapter 4 describes the research methodology in this research. In this chapter, the
-6-


research problems are attempted to be explained by using those Six Sigma
techniques with data analysis.

Chapter 5 summarises the findings of this research. Chapter 5 discusses the

requirements for improving quality control and also illustrates the implementation
and evaluation of the Six Sigma method.

Chapter 6 concludes those results in this study. The major implication for future
research is recommended at the end of this research.

-7-


Chapter 2 Literature Review
2.1

The history of the Six Sigma technique

Since the 1980s, applying statistical methods for quality control and overall business
improvement have grown rapidly not only in the United States but all over the world
(Antony & Banuelas Coronado, 2002). This was motivated, in part, by the
widespread loss of business and markets suffered by many US companies that
began during the 1970s. For example, the US automobile industry was nearly
destroyed by international competition during this period. One US automobile
company estimated its operating losses at nearly $1 million per hour in 1980
(Antony & Banuelas Coronado, 2002; Caulcutt, 2001). The adoption and use of
statistical methods with respect to quality have played a central role in the renewed
competitiveness of US industry.

The Six Sigma technique was first used in the 1980s at Motorola. In 1983, Bill Smith
who is a reliability engineer concluded that inspections and tests were not detecting
all product defects. Customers were finding defects and defects causing products to
fail (Zu, Fredendall, & Douglas, 2008). Since process failure rates were much higher
than the indication from final product tests, Smith decided that the best way to

solve the problem of defects was to improve the processes and to reduce or
eliminate the possibility of defects in the first place (Barney & McCarty, 2002). The
CEO of Motorola, Bob Galvin, was impressed by the early successes Smith achieved.
Therefore, Motorola began to apply the Six Sigma technique across the organisation
and to focus on manufacturing processes and systems (He, 2008).

Motorola established Six Sigma as both an objective for the corporation and as a
focal point for process and product quality improvement efforts. The Six Sigma
concept was tremendously successful at Motorola. It has been estimated that
Motorola reduced defects in semiconductor devices by 94% between 1987 and
-8-


1993 (Wienclaw, 2008a; Zhang, Hill, & Gilbreath, 2011). In recent years, Six Sigma
has spread beyond Motorola and has become a program for improving corporate
business performance by improving quality, reducing costs and expanding markets
for products and services. The Six Sigma technique has been adopted by thousands
of companies both large and small in scale.

2.1.1 The Six Sigma technique in practise
The Motorola Company first used the Six Sigma technique in 1987 and the Six Sigma
technique is now accepted and utilised in several famous companies, for example,
GE (the General Electric Company), Allied Signal, Philips Electronics, Sony and
Samsung (Montgomery & Woodall, 2008). The application of the Six Sigma
technique has helped global enterprises to save over a billion US dollars and it has
brought about remarkable improvements in enterprise management (Djurdjanovic
& Ni, 2003).

The Six Sigma technique brings the following benefits to businesses (Desai &
Shrivastava, 2008; George, 2003; Gygi, Williams, & Gustafson, 2005):


1). It can reduce the production cycle time and percentage of defective units.

2). It can increase productivity and product reliability.

3). It can enhance customer satisfaction, quality of employees and quality of
products.

4). It can also improve production capacity, outcomes and operation
processes.

-9-


On the other hand, using Six Sigma has two main disadvantages:

1). It will use up resources and time.

2). The company needs to invest an adequate amount of its budget for the
project at the outset.

Since data collection and analysis has become more important, there are some
famous software packages available for researchers. For instance, the Minitab,
Microsoft Excel and Sigma Work are widely implemented. These software packages
have some features including the statistical methods, statistical chart tools and
project management (Biehl, 2004; Redzic & Baik, 2006). Moreover, general users
find them easy to understand and utilise.

The Six Sigma technique has three powerful interconnected features (Connaughton,
2005a; Costello, Molloy, Lyons, & Duggan, 2005; Tayntor, 2007).


1). The executive leadership must choose a topic which is related with
B

“

“

department will select an area where there is potential for the greatest
amount of improvement.

2). A Black Belt (BB) employee should guide this project team so that the
company can execute and accomplish the project.

3). The project and training course should proceed simultaneously. During the
training course, the Black Belt (BB) has no other job except the project.

H

“

“

rate the

relationship between positive and negative characteristics (Azis & Osada, 2010;
Zackrisson, Franzén, Melbin, & Shahnavaz, 1995; Zhang, et al., 2011).
- 10 -



1). The key method of project improvement is to reduce waste but there are
also some positive effects from waste.

2). In the Six Sigma technique the improvement of cu
levels requires weekly action.

3). Initially, the Six Sigma technique does not play a prominent role and does
M
understand it and the only perceived effect is that it increases costs.
However, tactic management, which is part of the Six Sigma technique,
becomes a part of the way the company manages projects.

4). The Six Sigma technique does not have a method of unifying all the
employees in the company.

The basic components of the Six Sigma technique are not new, however, the
packaging of the method is new. The Six Sigma technique is a useful compilation of
proven techniques from many previous management methods (Redzic & Baik, 2006).
The power comes from the Six Sigma tech

-based approach, customer

orientation, financial motivation and assessment, tangible rewards for success,
qualitative and statistical tools and its focus on short duration and high impact
projects (He, 2008; Kim, 2008).

According to some researchers, there are some key elements which affect the
implementation of the Six Sigma technique. These factors also become problems
which need to be addressed by the company executives (Azis & Osada, 2010; Sekhar
& Mahanti, 2006; Tamura, 2006; Tayntor, 2007; Tká & Lyócsa, 2010; Tong, Tsung, &

Yen, 2004; Wienclaw, 2008d; Zou & Lee, 2010; Zu, et al., 2008). The problems are:

- 11 -




The company management levels of investment and commitment. In
successful cases, the company commits strongly to the Six Sigma
implementation.



Six Sigma involves changes to enterprise values and requires cultural
adjustment. This often involves changing the organisational structure and
the staff may resist the changes. Continuous communication, motivation
and training are the best methods to solve this problem.



T

project management skills. Team members should have some

basic knowledge of project management, including an awareness of its
limitations, its use in problem solving, its goals, the resources used, how
much time it will take, and how much it will cost.




The team should correctly choose the project. It must be consistent with
the enterprise's overall goal, output value and profits. The team also has
to respond to and understand what its customers want.



The company should choose suitable tools and techniques. Companies
sometimes choose inappropriate tools or methodologies and this
increases costs and wastes human resources. To understand all relevant
tools is the most important things for company leaders.

2.2

The quality management systems
2.2.1 Total Quality Management (TQM)

There are various management systems which have appeared as frameworks to
achieve quality improvement. The Total Quality Management (TQM), then, is
another familiar quality control technique to be applied in manufacturing industry.
TQM is a system for implementing and managing quality improvement activities on
an organisation-wide basis (Chau, Liu, & Ip, 2009). TQM began in the early 1980s
- 12 -


and was influenced by some eminent philosophies, for example, those of W.
Edwards Deming, Joseph Juran, and others (Wienclaw, 2008b).

It developed some concepts and ideas, which involved connections between
participating organisations, work culture, customer focus, supplier quality
improvement, and other activities. It focused on all essentials of the organisation in

achieving the goal of quality improvement. Normally, organisations establish TQM
operation quality councils or high-level teams that cope with strategic quality
initiatives; workforce-level teams that focus on routine production or business
activities; and cross-functional teams that address specific quality improvement
issues (Ali, 2005; Jones, et al., 2010; Montgomery et al., 2005).

2.2.2 The difference between the Six Sigma technique and the Total
Quality Management (TQM)

In general, the Six Sigma technique and the TQM have some similarities. For
instance, both techniques are basically the same. They are common manipulated for
the quality improvement in manufacturing industry. However, the Six Sigma
technique is not a part of TQM. Generally, the purpose of utilising TQM is to
improve the quality of manufacturing processes, the products, and even the
services. On the contrary, the Six Sigma technique is to make those improvements
more sharper and more focused (Amasaka, 2000; Ayad, 2010; Catherwood, 2002).

Compared with the Six Sigma technique, TQM has been more successfully and
extensively practised in the manufacturing industry (Zu, et al., 2008). It is inasmuch
as TQM is aimed at keeping already existing quality standards at a high while
TQM
level which the product reaches the standards produced inside the company
(Barney & McCarty, 2002). It is unlike TQM, the Six Sigma technique is more
emphasised the best results when focused on customers. The Six Sigma technique is
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a statistical process control and data driven approach and is highlighted the quality
is the fewest number of defects, which must be removed as much as possible.
F


“ “

segmentations (Besterfield, 2008; Pan, Park, Baik, & Choi, 2007).

Generally speaking, the Six Sigma technique is more focusing on the quality
improvement in entire business and TQM is more focusing on the simplex processes
or operations within departments. Considering the objectives in organisations,
therefore, managers in manufacturing industries would normally choose TQM to
attempt improving the quality in manufacturing department instead of the Six
Sigma technique (Barney & McCarty, 2002).

However, the importance of the Six Sigma technique has been maintained recently
since the growth of technology. Appling this technique in organisations has a strong
and a positive impact on the business financial performance (Yang & Hsieh, 2009;
Zou & Lee, 2010). Quality improvement projects with Six Sigma result in real savings,
expanded sales opportunities, or documented improvements in customer
satisfaction (Bengtson, 2008; Montgomery, 2010). Being a successful enterprise,
plant managers or managers who are in a higher managing positions start to pay
more attention to the entire business performance in the organisation (Azadegan &
Pai, 2008).

Moreover, the company leaders would be more likely to be fully concentrated,
provide the resources needed to train personnel and to establish full-time
employment positions related to Six Sigma once these improvements occur,. These
positions can be used as steppingstone to positions of higher responsibility in the
organisation (Bendell, 2004). It is much more likely that the techniques will actually
be used since the training is project-oriented, notwithstanding, the Six Sigma
technical training is normally deeper and more extensive than the typical TQM
program training (Antony, Banuelas, & Knowles, 2001; Patterson, Bonissone, &

Pavese, 2005).
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2.2.3 Basics for Six Sigma technique

Six Sigma is a statistical measurement tool. It is used to identify customer-critical
features and evaluate performances at each step in the production process. DPMO
(Defects per Million Opportunities) is one measurement of performance level and
this measurement is frequently used in Six Sigma. DPMO standardises the rejects
rate and it is based on the opportunities in terms of units (He, 2008; Wienclaw,
2008d).

The formula is:

DPMO = [Total number of defects / (Total number of units verified * Average
number of opportunities in a unit)] * 106

DPMO is the average number of defects in one million units. It is best used when the
process or characteristic is repeated many times (Evans, 2004). For instance,
company A manufactures 1,000 pieces of mask per hour every day and total 210 out
of 1,000 pieces of mask are defect goods. In the meanwhile, the manager also
discovered that there are four potential opportunities may result in those defect
goods during the manufacturing procedure. According to the formula above, it
computes that they will have 52,500 pieces of defect mask per million. The number
of DPMO, the 52,500 pieces of mask, is located in the range between 3 Sigma and 4
Sigma referring to the Sigma Scale in Table 1.

Table 1 below illustrates the DPMOs for a range of performance levels. Performance
at the Six Sigma level means that a process produces fewer than 3.4 defects or

errors per million opportunities for defects (Evans, 2004; Stevenson, 2005).
Therefore, the manager in Company A, then, can expect that there will be near 93
percentage of opportunity in producing the finished goods with reaching customer
satisfaction in normal circumstances.

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