BUSI 830 Liberty University Week 6 Report Audience Multiple Case Case Study assign.pdf

In this module, we will discuss the final stage of case studies – sharing or reporting of your case study.

Many business problems (complex, with breadth and depth) warranting a case study that a single

holistic case cannot address on its own. A Lean Six Sigma integrated Multiple-Case Case Study is just

the business solution because generally these cases will require some quantitative or mixed methods

elements. Use the excellent case presented in the Zhang et al. (2015) article as a model for your

multiple-case case study. After reviewing the Reading & Study material for the module, address the

following paper in current APA format:

1. Define the case study report audience and the appropriate reporting methodology

2. Compose visual and textual materials of a case study report

3. Explain the appropriate amount of evidence to present to facilitate the reader’s own conclusions to a

case study

4. Design a multiple-case case study that while covering multiple cases still draws a single set of cross-

case conclusions (single large organization, not multi-organizational). You will include Lean Six Sigma

specifically in the Design (type 4), Collect and Analysis (cross-case synthesis) phases of your case

study (use the Zhang et al. (2015) article as a model). [Also see Boxes 3, 32, and 38 (Yin, 2018)]

BUSI 830

MULTIPLE-CASE CASE STUDY ASSIGNMENT INSTRUCTIONS

In this module, we will discuss the final stage of case studies – sharing or reporting of

your case study. Many business problems (complex, with breadth and depth) warranting a case

study that a single holistic case cannot address on its own. A Lean Six Sigma integrated

Multiple-Case Case Study is just the business solution because generally these cases will require

some quantitative or mixed methods elements. Use the excellent case presented in the Zhang et

al. (2015) article as a model for your multiple-case case study. After reviewing the Reading &

Study material for the module, address the following paper in current APA format:

1. Define the case study report audience and the appropriate reporting methodology

2. Compose visual and textual materials of a case study report

3. Explain the appropriate amount of evidence to present to facilitate the reader’s own

conclusions to a case study

4. Design a multiple-case case study that while covering multiple cases still draws a single set of

cross-case conclusions (single large organization, not multi-organizational). You will include

Lean Six Sigma specifically in the Design (type 4), Collect and Analysis (cross-case synthesis)

phases of your case study (use the Zhang et al. (2015) article as a model). [Also see Boxes 3, 32,

and 38 (Yin, 2018)]

Required Format

This 1600 minimum, 2400 maximum word paper needs to be written with these main sections:

Cover page

Abstract

Introduction

Case Study Report Audience and Reporting Methodology

Visual and Textual Materials of a Case Study Report

Reporting Evidence: Striking the Balance

Multiple-Case Case Study with Lean Six Sigma

Conclusion

References

Other Requirements

Materials submitted to fulfill requirements in one course may not be submitted in another course.

Concerns about the propriety of obtaining outside assistance and acknowledging sources should

be addressed to the instructor of the course before the work commences and as necessary as the

work proceeds.

 The cover page must include this statement as an author’s note: “By submitting this

assignment, I attest this submission represents my own work, and not that of another

student, scholar, or internet source. I understand I am responsible for knowing and

correctly utilizing referencing and bibliographical guidelines. I have not submitted this

work for any other class.”

BUSI 830

 In addition to the course textbook(s) and the Bible, this paper must include at least 5

references from scholarly articles that have publication dates no older than 5 years. Do

not use any books other than the Bible and the textbook. Do not conduct interviews.

 There should be at least one instance of biblical integration (at least one scripture

reference).

 In-text citations are required to support your statements, points, assertions, issues,

arguments, concerns, paragraph topic sentences, and statements of fact and opinion.

 The required cover page, abstract and the reference pages are not included in the required

assignment word count but are required as part of your paper.

 The APA required abstract and conclusion section headings and subject headings (see

above) are expected. For papers this length, there should be at least two (2) ‘levels of

headings’.

 The introduction and conclusion sections should not be longer than ½ page each since the

assignment is short in word count.

 The required abstract should be written as a stand-alone document and not written as an

introduction since an introduction section is required. Therefore, refrain from using

phrases such as, “in this paper,” and do not use citations. See example in APA manual.

 Sources of information from Wikipedia, dictionaries, and encyclopedia will not be

accepted. Similarity scores must not exceed 20%.

 Paragraph lengths: Each paragraph should have a topic sentence unless it continues from

or provides support to the prior paragraph. A paragraph is defined in this course as being

at least 4 sentences in length.

 All parts of the assignment must be based on scholarly and biblical literature.

 Avoid clichés, slang, jargon, exaggerations, abbreviations, figurative language, and

language that is too informal and too subjective.

 Submit your final document for grading with file name syntax: Last NameFirst Initial

Project#. For example: PhilebaumJ Project6.doc (no .pdfs)

Grading Metrics

Consult the accompanying rubric for how your instructor will grade this assignment. Also, any

form of plagiarism, including cutting and pasting, will result in zero points for the entire

assignment. All quoted materials must be properly cited in current APA format.

Note: Your assignment will be checked for originality via the SafeAssign plagiarism tool.

BUSI 830

Multiple-Case Case Study Grading Rubric

Criteria

Levels of Achievement

Content ‐ 53 Points

Advanced

Proficient

Developing

Not present

Points

Earned

Abstract,

Introduction

5 Points

4 to 5 points

Abstract clearly states the

purpose and main conclusion

and Introduction provides a

complete overview of the

discussion.

2 to 3 points

Abstract and Introduction

provides a partial purpose,

main conclusion, and

overview of the discussion.

1 to 1 point

Abstract and Introduction

present but does not provide

an overview of the

discussion.

0 to 0 points

Not completed.

Case Study Report

Audience and

Reporting

Methodology

10 Points

9 to 10 points

Section provides a complete

discussion of the audience

and reporting methodology.

Flow is logical and fully cited.

6 to 8 points

Section provides a partially

complete discussion of the

audience and/or reporting

methodology. Flow is mostly

logical and partially cited.

1 to 5 points

Section provides a minimal

discussion of the audience

and/or reporting

methodology. Flow is not

logical and/or insufficiently

cited.

0 to 0 points

Not completed or not

related to requirements

for the section.

Visual and Textual

Materials of a Case

Study Report

10 Points

9 to 10 points

Section provides a

comprehensive description of

visual and textual materials of

a Case Study Report. Flow is

logical and fully cited.

6 to 8 points

Section provides a partial

description of visual and

textual materials of a Case

Study Report. Flow is logical

and partially cited.

1 to 5 points

Section provides a minimal

description of visual and

textual materials of a Case

Study Report. Flow is not

logical and/or insufficiently

cited.

0 to 0 points

Not completed or not

related to requirements

for the section.

Reporting

Evidence: Striking

the Balance

10 Points

9 to 10 points

Section provides a complete

and thorough discussion of the

appropriate balance of

evidence to provide to be

comprehensive and yet

enough for the reader to draw

their own conclusions to the

case study. Flow is

logical and fully cited.

6 to 8 points

Section provides a partial

discussion of the appropriate

balance of evidence to

provide to be comprehensive

and yet enough for the reader

to draw their own conclusions

to the case study. Flow is

mostly logical and partially

cited.

1 to 5 points

Section provides a minimal

discussion of the appropriate

balance of evidence to

provide to be comprehensive

and yet enough for the

reader to draw their own

conclusions to the case

study. Flow is not logical

and/or insufficiently cited.

0 to 0 points

Not completed or not

related to requirements

for the section.

Multiple-Case Case

Study with Lean

Six Sigma

10 Points

9 to 10 points

Demonstrates critical thinking

to include analysis, evaluation,

and synthesis of the course

material to draft a multiple-

case case study integrated

with Lean Six Sigma in the

Design, Collect and Analyze

phases.

6 to 8 points

Mostly synthesized the course

material to draft a multiple-

case case study integrated

with or without Lean Six

Sigma in the Design, Collect

and/or Analyze phases.

1 to 5 points

Only partially demonstrated

critical thinking, analysis,

evaluation, and/or limited

synthesis of the course

material to draft a multiple-

case case study integrated

with or without Lean Six

Sigma in the Design, Collect

and/or Analyze phases.

0 to 0 points

Not completed or not

related to requirements

for the section.

BUSI 830

Conclusion &

Biblical Integration

8 Points

8 to 8 points

Conclusion provides a

complete summary of the

discussion and highlights key

points and robust biblical

integration is present.

7 to 7 points

Conclusion provides a partial

summary of the discussion

and highlights at least one key

point and some biblical

integration is present.

1 to 6 points

Conclusion present but does

not summarize discussion or

highlight key points and little

to no biblical integration is

present.

0 to 0 points

Not completed.

Structure ‐ 22

Points

Advanced

Proficient

Developing

Not present

Points

Earned

Mechanics,

Composition,

Grammar, Word

Count

11 Points

11 to 11 points

Mechanics, Composition, &

Word Count is thorough

(1600-2400 words).

10 to 10 points

Mechanics, Composition, &

Word Count is satisfactory (+/-

2%).

1 to 9 points

Mechanics, Composition, &

Word Count is insufficient

(+/- 3-4%).

0 to 0 points

There are many errors

in mechanics,

composition, grammar

or Word Count (>4%

diff).

APA Format,

Structure, &

References and

Citations

11 Points

11 to 11 points

Proper cover page and

section headings included.

Met all of the required

formatting. References

exceed requirements in

number and quality and/or

most statements are

supported by a variety of

citations.

10 to 10 points

Proper cover page and

section headings included.

Met most of the required

formatting. References meet

requirements in number and

quality and/or many

statements are supported by a

variety of citations.

1 to 9 points

No cover page and/or section

headings included. Met some

required formatting.

References do not meet

requirements in number and

quality and/or some

statements are supported by

a variety of citations.

0 to 0 points

No structure or

formatting provided.

Missing references

and/or citations are

rare, repetitious or non-

existent.

Total Points

/75

Instructor’s Comments:

Full Terms & Conditions of access and use can be found at

https://www.tandfonline.com/action/journalInformation?journalCode=tppc20

Production Planning & Control

The Management of Operations

ISSN: 0953-7287 (Print) 1366-5871 (Online) Journal homepage: https://www.tandfonline.com/loi/tppc20

Comprehensive Six Sigma application: a case study

Min Zhang, Wei Wang, Thong Ngee Goh & Zhen He

To cite this article: Min Zhang, Wei Wang, Thong Ngee Goh & Zhen He (2015) Comprehensive

Six Sigma application: a case study, Production Planning & Control, 26:3, 219-234, DOI:

10.1080/09537287.2014.891058

To link to this article: https://doi.org/10.1080/09537287.2014.891058

Published online: 10 Mar 2014.

Submit your article to this journal

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Citing articles: 7 View citing articles

Comprehensive Six Sigma application: a case study

Min Zhang

*, Wei Wang

, Thong Ngee Goh

and Zhen He

College of Management and Economics, Tianjin University, No. 92, Weijin Road, Nankai District, Tianjin, China;

Department of

Industrial and Systems Engineering, National University of Singapore, Singapore, Singapore

(Received 20 March 2013; accepted 29 January 2014)

Six Sigma as a framework for eliminating defects at the project level and improving performance and customer satisfaction

at the corporate level has been generally recognised. This case-oriented paper reports an important Six Sigma management

case study at the world’s largest cold rolling mill situated in China. The descriptions of measures taken at the company

level, as well as that of the exemplary application experience of this company, would constitute a most comprehensive

account of the impact brought about by Six Sigma to the company. A Black Belt project was conducted to improve the cold

rolling capability to meet the thickness requirements using the Six Sigma methodology –DMAIC (deﬁne, measure, analyse,

improve and control) principle. The implementation of Six Sigma methodology led to a signiﬁcant ﬁnancial impact on the

proﬁtability of the company. Seven key factors were also found to be instrumental to the successful Six Sigma management

implementation in the company.

Keywords: Six Sigma; DMAIC; quality management; quality improvement; metallurgy; China

1. Introduction

Six Sigma is a systematic methodology aimed at operational

excellence through continuous process improvements. As we

know, although Six Sigma originated from Motorola in 1986

arising from the need to improve product quality and cus-

tomer satisfaction in the face of ﬁerce competition from

Japan, some of the basic approaches and tools of Six Sigma

originated from the widespread application of statistical

methods in the American military industry since the Second

World War (Deming 1993). The procedures to obtain varia-

tion reduction systematically by statistical means or methods

were given by Shewhart and Deming. The essential nature

of ‘Six Sigma’is ‘conﬁdence building’, which in turn makes

it easier for a company to direct (modify, maintain and pre-

vent) the behaviour of ‘people’(customers, vendors, employ-

ees, etc.) in a manner that sustains the survival or growth of

the company (Christiansen 2011).

It is noteworthy that Aboelmaged (2010) pointed out that

case study is the most dominant research method in Six

Sigma articles (55.4% in 231 articles). There have been

reports on gains in ﬁnancial beneﬁts and competitive

advantages arising from Six Sigma applications from various

countries and districts (e.g. Bañuelas, Antony, and Brace

2005; Desai 2006; Kumar et al. 2006; Anand et al. 2007;Su

and Chou 2008; Aksoy and Orbak 2009; Chakravorty 2009;

Chen and Lyu 2009; El Haouzi, Petin, and Thomas 2009;

Lo, Tsai, and Hsieh 2009;YangandHsieh2009;Chenetal.

2010;Jouetal.2010; Zu, Robbins, and Fredendall 2010;

Gijo, Scaria, and Antony 2011;Lietal.2011; Antony, Gijo,

and Childe 2012; Bilgen and Sen 2012; Tanik and Sen 2012;

Ghosh and Maiti 2012;Linetal.2013). Although Six Sigma

wasintroducedtoChinasoonafteritsinceptioninAmerica

in the 1980s and an increasing number of Chinese compa-

nies are implementing or planningtodeploySixSigma,

research and case studies of Six Sigma implementation in

Chinese companies have seldom been reported until now. In

this paper, we present a case of comprehensive Six Sigma

application in a large stainless steel company, through the

illustration of an overall Six Sigma implementation strategy

and a successful project, to furnish an insight into the poten-

tial impact of Six Sigma in the industrial sector of the

world’

s second largest economy.

The paper is organised as follows. Section 2presents

the overall Six Sigma implementation strategy of Com-

pany T. Section 3illustrates how DMAIC (deﬁne, mea-

sure, analyse, improve and control) is used to solve an

important problem in what is referred to as Company T.

Section 4presents the economic beneﬁts of this Black Belt

project. Section 5consists of a discussion of the key fac-

tors of successful Six Sigma management implementation;

the last section presents the major conclusion of the paper.

2. Company-level Six Sigma implementation at

‘Company T’

2.1. Six Sigma start-up

The case study is related to quality management in a

stainless steel cold rolling mill, which for the purpose of

*Corresponding author. Email: [email protected]

Production Planning & Control, 2015

Vol. 26, No. 3, 219–234, http://dx.doi.org/10.1080/09537287.2014.891058

this presentation is referred to as ‘Company T’. The

company’s Six Sigma promotion approach is ﬁrst intro-

duced, and then a Black Belt project related to the thick-

ness of stainless steel cold rolling sheet is described

along with the economic beneﬁts.

Company T, founded in 1934, is a ‘mega’enterprise

in iron and steel encompassing iron mining, production,

machining, distribution and trading. It is also the largest

stainless steel enterprise in the world with advanced

technologies and equipments, complete product types

and speciﬁcations. Its annual production capability is

about 10 million tons of steel, including 3 million tons

of stainless steel.

As a conventional state-owned enterprise, Company

T has been in constant search for effective quality man-

agement methods. For example, quality control circles

have a history of more than two decades; in early 1990s,

the company began to implement ISO9000 and was cer-

tiﬁed. These efforts have played an important role in

motivating the staff and solving on-site quality problems.

With the rapid development of the company and the

need for continuous improvement in quality, statistical

process control theory and methods have been deployed

to enhance quality performance. Various quality manage-

ment techniques, such as 5S, TPM and JIT, have been

implemented as well, in efforts to improve site manage-

ment, elevate operational efﬁciency of equipment and

facilitate on-time production.

At the turn of the century, it was determined that to

build a globally competitive stainless steel enterprise, it

takes a breakthrough from management by experience to

management by scientiﬁc tools. Thus, QC circles were

found to be inadequate in handling inter-process, inter-

departmental quality issues, while teams with responsibili-

ties in quality improvement would face a lack of system-

atic improvement procedures and effective analytical

tools. And the deployments of QC circles, TPM, 5S and

other initiatives belong to different departments, and col-

laborations among them were less common. Thus, the

potential of these initiatives is not fully utilised. The

reported successful experience of domestic as foreign

companies such as Posco of Korea led to the strategic

decision, in 2004, by the leadership of Company T to turn

to Six Sigma management, which made the company one

of the earliest among steel enterprises in China to embrace

Six Sigma.

With high-level management commitment, the com-

pany drew up the 2006–2010 Five-Year Plan for Six

Sigma management. The entire company senior manage-

ment team attended the introductory training. And with

the ﬁve-year plan, the company chairman took the lead for

its implementation, set up a company Six Sigma ofﬁce,

with additional rewards to those promoting Six Sigma.

The company CEO initiated the corresponding human

resource incentives, attended meetings for Six Sigma

promotion and project selection, and secured various

needed resources. As Six Sigma champion, the chief engi-

neer took the lead for formulating annual Six Sigma pro-

motion plans, identifying improvement projects,

conducting project reviews and promoting the presence of

a Six Sigma culture in general.

2.2. Integration of Six Sigma and other initiatives

Like many other Chinese state-owned enterprises, Com-

pany T faced some problems raised by some employees.

Typical questions were: What are the differences between

Six Sigma and other management initiatives? and How

can we balance the resources required by Six Sigma and

other methods such as TQM, Lean Production and TPM?

With the help from outside consultants, Company T rea-

lised that the core values of Six Sigma and other manage-

ment initiatives are basically the same. The advantages of

Six Sigma are: (1) Six Sigma provides a systematic infra-

structure and mechanism for continuous improvement

through strong top-down management commitment; (2)

Though Six Sigma does not bring about any new tools,

and actually Six Sigma tools and methods existed before

the name Six Sigma was coined, Six Sigma provides a

clear and easy-to-implement DMAIC roadmap for busi-

ness process improvement, with DMADV (Deﬁne, Mea-

sure, Analyse, Design and Verify) or IDDOV (Identify,

Deﬁne, Develop, Optimise and Verify) and other roadmap

of design for Six Sigma for product/process design and

innovation; (3) The effective project management and rig-

orous problems-solving tools of Six Sigma provides a

general framework for problem identiﬁcation, problem

analysis and problem-solving. Thus, Six Sigma project

can reach accountable business results; and (4) The sys-

tematic action-learning-type training of Black Belts, Green

Belts and Yellow Belts provides an effective and efﬁcient

talent cultivation system. Thus, Six Sigma can be inte-

grated with Lean Production, TPM and other management

initiatives. And there are many successful stories of Six

Sigma integration. Thus Company T builds a big Six

Sigma umbrella at corporate level, which includes QCC

(Company T puts it as Quick Six Sigma projects), TPM

and Lean Production, etc.

2.3. Organisation for implementation

The Six Sigma management style in Company T focuses on

the full participation of all employees, with fast and continuous

improvements. The strategy and main thrusts are as follows.

2.3.1. Full participation

All employees are required to learn the basic principles

and contents of Six Sigma management through various

familiarisation programs and training. Every employee is

220 M. Zhang et al.

expected to be able to make good use of Six Sigma

ideas appropriate to their work responsibilities.

2.3.2. Multi-level and systematic organisation structure

The ﬁrst level encompasses quality-related teams or pro-

jects, related to complete processes, systems and long-

term activities; members comprise all related staff and

the main management and technical personnel.

The second level comprises ‘contract’project teams

aiming at solving speciﬁc quality problems and optimisa-

tion of management processes; team members consist of

technical and management specialists and experts.

The third level are ‘Quick Six Sigma’(QSS) teams

with projects focusing on existing problems and quick

improvements: depending on the depth and breadth of

the study, projects are categorised into those for Black

Belts (BB), Green Belts (GB) and Yellow Belts; team

members are made up of engineers, managers and opera-

tors directly related to the speciﬁc processes in question.

The fourth level is based on Lean Six Sigma pro-

jects, addressing work standardisation as well as opera-

tions quantiﬁcation and control; the bulk of the team

members are related operators.

2.3.3. Quick and continuous improvement

The multi-level structure of Six Sigma implementation

teams is formed to solve business problems of strategic

level and operational level. And this structure helps

Company T form the critical mass of Six Sigma. Thus,

Company T builds up a continuous improvement model

based on Six Sigma. On one hand, the ready formation

of different level Six Sigma teams to address critical

business issues as well as operational situations ensures

timely concentration of resources for problem-solving.

On the other hand, it is recognised that there is no ﬁnish-

ing line for quality improvement; thus, persistent Six

Sigma improvement efforts are essential: as soon as the

targets of one stage are reached, new ones are set for

further gains in quality performance.

3. Black Belt project: sheet thickness improvement

A signiﬁcant Black Belt project in the context of the above

company-wide Six Sigma improvement effort will now be

presented. The project is about improving the capability to meet

the thickness requirements of stainless steel cold rolling sheets.

3.1. Background of project

Stainless steel cold rolling sheet is the most competitive

product in Company T. The thickness of the cold rolling

sheet is recognised as the key quality characteristic.

Thickness variation control not only reﬂects product

quality, but also has a close relationship with the eco-

nomic beneﬁts that can be derived by the customers.

However, from market surveys and customers’responses,

the thickness variation of cold rolling sheet produced in

Company T has been too large. Through benchmarking

with its competitor Company P, Company T found that

the means of its cold rolling sheet thickness are about

0.01–0.04 mm larger than the corresponding values in

Company P, and the variation is quite larger than its

competitor’s. Thus, the managers in the cold rolling mill

made the decision to have a Six Sigma project aimed at

decreasing the variation of thickness and improving the

thickness compliance of stainless steel cold-rolled sheets

to enhance the market competitiveness of their products.

The team members were trained to use Minitab software

to do statistical analysis. In this paper, all statistical anal-

ysis outputs are based on Minitab.

3.2. Deﬁnitions

3.2.1. Deﬁnition of non-conforming product

Based on quality inspection standards, the thickness of

steel rolls is measured as the vertical diameter of steel

sheet. If the thickness of a roll is within the upper and

lower speciﬁcations, then the roll is regarded as a con-

forming product, otherwise it is non-conforming.

3.2.2. Deﬁnition of yield

Total inspection is used here. The number of wholly

tested rolls is the denominator and the number of con-

forming rolls is the numerator. Thus, this ratio is taken

as the yield of the production line.

3.2.3. Goal of the Black Belt project

The thickness yield in Company T is only 68.9% now.

However, it is 85.2% in Company P. Through team work

analysis using SMART (speciﬁc, measurable, attainable,

relevant and time-bound) rule, the goal of this Black Belt

project is to increase the yield in Company T to 90%.

3.2.4. Team members

The chief engineer in Company T acts as the project

champion. Through Supplier, Input, Process, Output,

Customer and project stakeholder analysis, we found that

several departments are involved in this project including

the technical department (product and process design),

testing, equipment maintenance, etc. A cross-functional

team is formed including team members from each

department. Also, some experienced front line workers

are invited to be extended team members. A Black Belt

from technical department works as the team leader. The

Production Planning & Control 221

team makes a detailed project plan and reaches consen-

sus on the conduct of behaviour for the project activities.

3.3. Measure

3.3.1. Measurement system analysis

The cold rolling sheet thickness leads to continuous data.

The measurement system is analysed based on the thick-

ness data measured by micrometre and four testers. The

measurement system analysis is shown in Table 1. It can

be seen that the variance of total gauge R&R% is only

1.49% of the total variance, and the number of distinct

categories is 94. Thus, the capability of this measurement

system is reliable.

3.3.2. Process ﬂow analysis and key process input

variables identiﬁcation

In cold rolling mill, the key process is the rolling pro-

cess, for which the ﬂow chart is shown in Figure 1. For

each process step in rolling, we identiﬁed the possible

factors that may impact the thickness of the stainless

steel plate. The cause and effect diagram as shown in

Figure 2is then used to ﬁnd the main factors that might

inﬂuence the large sheet thickness variation from consid-

erations of human, machine, materials and method ele-

ments, aided by the brainstorming process. Eventually

32 potential factors are identiﬁed.

3.4. Analyse

3.4.1. Factors selected

In this project, the defect is thickness of out speciﬁcation

including large thickness variation and extra thickness.

Here, a cause-and-effect matrix is used to show the rela-

tionship of these 32 factors and the defects. The impor-

tance of defects is set up by its weighted score in

Table 2. Nineteen factors (bold type in Table 2) with

total score larger than 50 are selected as key factors

related to the main defects. Next, a failure mode and

effect analysis (FMEA) is carried out for these factors,

as shown in Table 3.

Table 1. Measurement system analysis of stainless steel cold

rolling sheet thickness.

Source

Study var. % study Var.

Std. dev. (SD) (6 × SD) (% SV)

Total gauge R&R 0.010973 0.06584 1.49

Repeatability 0.010452 0.06271 1.42

Reproducibility 0.003340 0.02004 0.45

Operator 0.003340 0.02004 0.45

Part-to-part 0.737699 4.42620 99.99

Total variation 0.737781 4.42669 100.00

Note: Number of distinct categories = 94.

Input

variables:

Coils of hot

plate after

annealed and

pickling

Uncoiling Stretching Rolling Coiling

Input variables:

Thickness set

Roller type

Power source

Rolling pressure

Pull type

Standard plates

Rolling deformation rate

Type of steel

Rolling oil

Rolling pass

Defects:

Thickness of out

specification

Figure 1. The ﬂow chart of cold rolling process.

222 M. Zhang et al.

Effect of plate

temperature

Oil of steel plates

Foreign matter in

radioactive source

Unreasonable

compensating factor

Effect of heavy metal

elements in steel rolls

Abnormal failure

Effect of rolling oil

Uncorrected thickness

of standard plates

Uninitialized

Thickness Gauge

Not executing

set values

False use

of micrometer

Wrong input

of steel type

Wrong measurement

No training or poor training

Not measuring

thickness manually

Not checking

ERP information

Operator

Operating rollers

Inconsistent measurement

method with the customers

Plates thickness reduction

of different steel types

Inconsistent measurement

positions

Thickness standard

Method

Operation of temper mill

Different flattening level thinning

for different steel types

Improper pressure adjustment

Rolling tension

Large thickness variation

of incoming materials

Confusion of

different plate types

Effect of covexity

of incoming plates

Effect of rolling

ingredients variation

Effect of hot

rolling plate wedge

Materials

Inconsistent annealing

properties

Over thickness

Figure 2. The cause and effect diagram of over thickness.

Table 2. C&E matrix of cold rolling plate thickness.

Rating of importance (1–10) 5 9

Key requirements Large variance Extra thickness

Process step Rating: 0–10 Total

1Thickness standard 8 5 85

2 Order 3 1 24

3Rolling parameters 3 9 96

4Stretching force 3 9 96

5 Plate temperature 3 3 42

6Compensating factor of thickness gauge 3 9 96

7Standard plates 1 9 86

8 Rolling oil 3342

9Power source 3 9 96

10 Oil residue on plate surface 3342

11 Measure position 6 2 58

12 Thickness reference revision 2 9 91

13 Thickness reference ﬁlled 2228

14 Contract requirement 5 3 52

15 Wedge-shaped raw material 9 3 72

16 Plate crown of raw material 4 3 47

17 Thickness of raw material 3 1 24

18 Ingredient Ni of raw material 9 1 54

19 Ingredient Cu of raw material 9 3 72

20 Ingredient Mo of raw material 9 3 72

21 Ingredient Cr of raw material 3 4 51

22 Ingredient Al of raw material 3124

23 Inspectors 3 3 42

24 Raw materials annealed 3 1 24

25 Flattening passes 9 3 72

26 Rolling passes 3 3 42

27 Rolling strain of ﬁnal product pass 5 4 61

28 Rolling tension 1 3 32

29 Manual thickness measurement 3 9 96

30 Difference of rolling shift teams 6 3 57

31 Difference of rollers 6 3 57

32 Total rolling strain 3 4 24

Production Planning & Control 223

Table 3. FMEA of cold rolling plates.

Item

Potential failure

mode

Potential

effects of

failure

(Severity

rating) Potential causes

(Occurrence

rating)

Current

controls

(Detection

rating) RPN

Wedge-shaped

raw

material

Large variance Large

variation of

thickness

7 Incorrect wedge

control of hot

rolling raw

material

4N 4112

Ingredient Cr

of raw

material

Inaccurate

thickness

gauge

measurement

Thickness of

out

speciﬁcation

6 Melting control 4 N 4 96

Ingredient Ni

of raw

material

Inaccurate

thickness

gauge

measurement

Thickness of

out

speciﬁcation

6 Melting control 4 N 4 96

Ingredient Mo

of raw

material

Inaccurate

thickness

gauge

measurement

Thickness of

out

speciﬁcation

6 Melting control 4 N 4 96

Ingredient Cu

of raw

material

Inaccurate

thickness

gauge

measurement

Thickness of

out

speciﬁcation

6 Melting control 4 N 4 96

Rolling

parameters

Disunity Large

variation of

thickness

8 Failure to obey

design

6 3 144

Unreasonable

values

Extra

thickness

9 Design

parameters

insufﬁciency

4 Temporarily

set up

references

3 108

Rolling strain Non-standard Bad rolling

performance

5 Lack of quality

consciousness

6 Process

periodical

inspection

390

Rolling strain

of ﬁnal

product

pass

Disunity Final product

thickness of

out

speciﬁcation

3 Steel ingredient,

annealing and

process

7 N 6 126

Compensating

factor of

thickness

gauge

Not able to

ﬁnd the best

value

Final product

thickness of

out

speciﬁcation

7 Variance of

ingredients or

system error of

thickness gauge

3 N 6 126

Manual

thickness

measurement

Inaccurate

measurement

Inaccurate

actual

thickness

measurement

7 Incorrect

micrometre

calipers

5 Training 2 70

Power source Abnormal work Not scheduled

for

maintenance

or abnormal

9 Abnormal

problems such as

equipment

failure

1 Temporary

treatment

872

Rolling shift

teams

Different

operation

process

Poor

thickness

unity

4N 6 N 4 96

Rollers Different

system

Poor

thickness

unity

4 N 6 N 5 120

Standard plates Incorrect size Incorrect roller

thickness

control

10 Abnormal when

calibrating

1N 990

Flattening

passes

Non-standard Incorrect

thinning level

6 Strong

arbitrariness

5 Wide ﬂow

for various

plate types

390

Stretching force Disunity Different

thinning level

6 Different raw

plate shape level

4 Focus on

improving

plate shape

248

(Continued)

224 M. Zhang et al.

There are 16 factors whose risk priority number

(RPN) is larger than or equal to 90. The cause of nine

factors, marked by bold type in Table 3, will be analysed

and improved by the statistical tools in the following

section. Another seven factors can be immediately

corrected through a simple and quick improvement

scheme. Then, a second FMEA of these seven factors is

analysed. Except that thickness standards need to be

coordinated with the design department, the RPN values

of the other six factors are all below 90, which are

shown in Table 4.

3.4.2. Analysis schemes

In this section, the effects of wedge-shaped raw material,

chemical ingredients, rolling shift teams and roller unit

Table 3. (Continued).

Item

Potential failure

mode

Potential

effects of

failure

(Severity

rating) Potential causes

(Occurrence

rating)

Current

controls

(Detection

rating) RPN

Thickness

standard

Many

personalised

standards

Poor process

control, order,

inspection and

judge

7 No standards

provided to

customers or

little standards

8N 2112

Measure

position

Incorrect

measurement

thickness

Not

conforming

with thickness

measured by

customer

5 Thickness

inconsistency

between the

middle and edge

of plate

4 C100

position

required

240

Thickness

reference

revision

Non-conformity

to the standard

Poor reference

thickness

6 Did not grasp

the points of

thickness

revision

5 Training and

check

390

Contract

requirement

Did not

distribute the

products

according to the

raw orders

Inconsistent

thickness

6 Handle non-

scheduled

products

3 Strengthen

equipment

inspection

236

Table 4. The improved FMEA of cold rolling process.

Items Failure mode Current status

Prior

RPN Measures taken S O D RPN

Rolling

parameters

Disunity Thickness speciﬁcation is not

consistent with customer

requirements. Rolling parameters

are not fully carried out in practice

144 Parameters are redesigned. New

thickness standards and process needs

are well trained

823 48

Unreasonable 108 9 2 3 54

Thickness

standard

Many

personalised

standards

There are 1379 types of

thickness requirements and is

no uniﬁed standard

112 Based on customer requirements,

current standards and experience

in the industry, new thickness

standards are set down

772 98

Rolling

strain

Non-standard The relationship between raw

materials and ﬁnished products is

lack of standardisation

90 Based on the steel characteristics and

real production conditions, such

relationship is standardised

533 30

Standard

plates

Incorrect size In practice standard thicknesses of

some standard plates are not

precise

90 Each standard plate has to be

manually inspected to make sure

thickness is ok

10 0 9 0

Flattening

passes

Non-standard Thickness reduction amount is not

clear enough after ﬂattening

process

90 After thorough learning of thickness

reduction amount of each process,

thickness unity is provided according

to steel types, thickness speciﬁcation

and process requirements

623 36

Thickness

reference

revision

Non-

conformity to

the standard

Thickness revision concept is

misunderstood and not executed

consistently

90 Thickness reference is classiﬁed and

revised. Each inspector is well

trained

623 36

Production Planning & Control 225

on thickness yield control are analysed. Different tools

are used for different data types.

3.4.2.1. Effect of wedge-shaped raw materials. The

effect of wedge value of hot rolling plates on the thick-

ness of cold rolling plates is investigated here. Wedge is

a measure of the thickness at one plate edge as opposed

to the other edge. It may be expressed as absolute mea-

surements or as relative measurements. Here, absolute

measurements are used. In a hot rolling process, wedge

may be caused by rigidity of rolling mill, work piece

deviation, raw material wedge or uneven temperature.

Ten coils with target cold rolling plate thickness of 2.0

mm were randomly assigned to each nominal wedge val-

ues of 0.01, 0.04 and 0.07 mm. The thickness values of

cold rolling plates are shown in Table 5.

In the analysis, the hypothesis tested is as follows.

: there is no statistically signiﬁcant thickness differ-

ence for different wedge values. H

: there is statistically

signiﬁcant thickness difference for different wedge val-

ues. One-way ANOVA is used and the results are shown

in Figure 3. Boxplots of thickness by wedge value are

shown in Figure 4. Because the resulting pvalue is vir-

tually zero, the null hypothesis is rejected, i.e. there are

statistically signiﬁcant differences in the thickness for

different wedge values. Besides, when the wedge value

is 0.01 mm, the mean thickness is 1.85 mm, which is the

closest to target thickness 2.00 mm and the thickness

standard deviation is also the smallest. Therefore, the

wedge value of hot rolling plates should be 0.01 mm in

order to control the thickness variation of cold rolling

plates with target thickness 2.0 mm.

3.4.2.2. Effect of chemical ingredients Cr, Ni, Mo and Cu.

The addition of chemical ingredients makes the stainless

steel respond well to heat treatment, resulting in different

mechanical strengths, such as hardness and corrosion

resistance. However, there is variation in the chemical

ingredients due to measurement positions and the smelt-

ing processes. In this project, one type of stainless steel

with target thickness 2.00 mm contains 17–19% chro-

mium (Cr), 12–16% nickel (Ni), 1.2–2.5% copper (Cu)

and 1.5–2.5% molybdenum (Mo). The thickness is mea-

sured with the use of X-ray thickness gauge for 100

coils where 10 positions are chosen in each coil. Regres-

sion analysis between thickness and chemical ingredients

is shown in Figure 5. It can be seen from Figure 5that

the standard error is 0.0128 mm. The thickness variation

due to the ingredients can be controlled within ±3 ×

0.0128 mm, that is 0.0768 mm.

Moreover, the pvalues of ingredients Ni and Cr are

0.624 and 0.491, respectively, which are much larger

than 0.05. Thus, ingredients Ni and Cr do not signiﬁ-

cantly affect the thickness. On the other hand, the pval-

ues of ingredients Cu and Mo are 0.015 and 0.004,

respectively, both being smaller than 0.05. Thus, there is

signiﬁcant relationship between thickness and ingredients

Cu and Mo. The scatter plots of thickness adjusted for

Cu vs. Mo adjusted for Cu are shown in Figure 6. Those

of thickness adjusted for Mo vs. Cu adjusted for Mo are

shown in Figure 7. Next, ingredients Ni and Cr are

deleted from the regression analysis. The regression

results are shown in Figure 8. The pvalues of ingredi-

ents Cu and Mo are 0.007 and 0.003, respectively, which

are smaller than 0.05. Thus, there is signiﬁcant relation-

ship between thickness and ingredients Cu and Mo. In

practice, high-quality copper and molybdenum wires are

ﬁrst mixed into the smelting furnace based on their lower

or middle speciﬁcations. The proportions of Cu and Mo

are measured at regular times. More wires may be used

in the smelting process.

One-way ANOVA: thickness versus Wedge

Source DF SS MS F P

Wedge 2 0.0022483 0.0011241 223.83 0.000

Error 27 0.0001356 0.0000050

Total 29 0.0023839

S = 0.002241 R-Sq = 94.31% R-Sq(adj) = 93.89%

Individual 95% CIs For Mean Based on Pooled StDev

Level N Mean StDev ---------+---------+---------+---------+

0.01 10 1.85020 0.00132 (-*-)

0.04 10 1.84000 0.00258 (--*-)

0.07 10 1.82900 0.00258 (-*-)

---------+---------+---------+---------+

1.8340 1.8410 1.8480 1.8550

Pooled StDev = 0.00224

Figure 3. Results of one-way ANOVA.

Table 5. Values of thickness with different wedges (unit: mm).

Wedge values 0.01 0.04 0.07

Thickness 1.850 1.840 1.830

1.852 1.842 1.828

1.851 1.843 1.830

1.852 1.841 1.826

1.850 1.844 1.824

1.849 1.838 1.828

1.851 1.839 1.831

1.849 1.837 1.832

1.848 1.836 1.829

1.850 1.840 1.832

226 M. Zhang et al.

3.4.2.3. Effect of rolling shift teams and roller unit.

Multi-vari analysis is used to analyse the effect of rolling

shift teams and roller unit on thickness. We chose three

rollers numbered 1#, 2# and 3# which are randomly

operated by four shifts named A, B, C and D. The thick-

nesses of ten coils are randomly measured for each shift

operating one roller. The thicknesses are shown in Fig-

ure 9. It can be seen that the thickness variation is

mainly caused by different shifts for each roller. How-

ever, the variation between different rollers is relatively

small. Thus, the front line workers should be well trained

according to operation instruction to guarantee produc-

tion consistency.

3.5. Improve

The main task in this step is to further analyse the effect

of rolling strain, compensating coefﬁcient and rolling

parameter on the cold rolling plate thickness with the use

of design of experiments (DOE) (Box, Hunter, and Hun-

ter 2009). A full factorial design with three factors at two

levels (i.e. a 2

factorial design) with three centre points

is adopted. For conﬁdential reason, the level selection for

each input variable and the raw data of experimental

design are not provided. The analysis is shown in Fig-

ure 10. It can be seen from Figure 10 that the three main

effects and the interaction between strain and compensat-

ing coefﬁcients are signiﬁcant. After deleting the insignif-

icant interactions in the model, the reduced model is

shown in Figure 11. There is no curvature and lack of ﬁt

of the model. Residual analysis validates the appropriate-

ness of the model. As the curvature coefﬁcient measures

the sum of the quadratic effects or strain and rolling

parameter, it is probably appropriate to add some star

points in the design in future investigations.

Optimisation is also used to ﬁnd the best values of

strain, compensating coefﬁcient and rolling parameter.

Based on the optimised values of these parameters, 20

coils of hot rolling plates with the target of thickness

2.0 mm are tested to observe if the actual thickness is

within the thickness speciﬁcation limits. The thickness of

experimental coils falls in the conﬁdence interval range,

which shows that the conclusions from the DOE analysis

are correct. The process parameters can be used in pro-

duction.

Figure 4. Boxplots of thickness by wedge value.

Regression Analysis: Thickness versus Cr, Ni, Mo, and Cu

The regression equation is

Thicknesses = 2.04 - 0.0111 Ni -0.00526 Cr – 0.0408 Cu – 0.197 Mo

Predictor Coef SE Coef T P

Constant 2.03570 0.18250 11.15 0.000

Ni -0.01112 0.02259 -0.49 0.624

Cr -0.00526 0.00759 -0.69 0.491

Cu -0.04083 0.01643 -2.49 0.015

Mo -0.19693 0.06560 -3.00 0.004

S = 0.0127556 R-S

= 80.9% R-S

(ad

) = 88.2%

Figure 5. Regression analysis between thickness and chemical

ingredients of Cr, Ni, Mo and Cu.

Production Planning & Control 227

2.22.01.81.61.41.2

2.03625

2.03600

2.03575

2.03550

2.03525

2.03500

2.03475

2.03450

Cu (%)

thickness (mm)

2.22.01.81.61.41.2

2.4

2.3

2.2

2.1

2.0

1.9

1.8

1.7

1.6

1.5

Cu (%)

Mo (%)

(a) (b)

Figure 6. (a) Thickness adjusted for Cu and (b) Mo adjusted for Cu.

1.5 1.6 1.7 1.8 1.9 2.0 2.1 2.2 2.3 2.4

2.03625

2.03600

2.03575

2.03550

2.03525

2.03500

2.03475

2.03450

Mo (%)

thickness (mm)

1.5 1.6 1.7 1.8 1.9 2.0 2.1 2.2 2.3 2.4

2.2

2.0

1.8

1.6

1.4

1.2

Mo (%)

Cu (%)

(a) (b)

Figure 7. (a) Thickness adjusted for Mo and (b) Cu adjusted for Mo.

Regression Analysis: Thickness versus Cu and Mo

The regression equation is

Thicknesses = 1.85 - 0.0443 Cu – 0.181 Mo

Predictor Coef SE Coef T P

Constant 1.85281 0.00212 875.77 0.000

Cu -0.04429 0.01592 -2.78 0.007

Mo -0.18053 0.05922 -3.05 0.003

S = 0.0126807 R-Sq = 80.1% R-Sq(ad

) = 88.8%

Figure 8. Regression analysis between thickness and chemical

ingredients of Cu and Mo.

1# 2# 3#

1.825

1.83

1.835

1.84

1.845

1.85

1.855

1.86

1.865

1.87

Roller

Thickness

Figure 9. Multi-vari chart of rollers and shifts.

228 M. Zhang et al.

3.6. Control

The signiﬁcant key factors found in the measurement,

analysis and experiment steps are controlled through

control plans to sustain the effectiveness achieved

through the project. The aim is to keep the current thick-

ness level and prevent any quality deterioration. Such

actions are shown in Table 6.

The cold rolling coils are inspected periodically to

monitor the improved results. Here, an individual mov-

ing range control chart is used. The chart shows that the

thickness is in control.

The original thickness yield is only 68.90%. How-

ever, it reaches to 95.82% after the improvement of the

Six Sigma project. There is a signiﬁcant increase in

thickness yield. Furthermore, the thickness yield is also

over the target value, that is 90%.

4. Economic beneﬁt analysis

There were about 40 cold rolling coils with over-large

thickness per month before this project was carried out.

However, such number decreases to 5 coils per month

after improvement project. The cost of rolling and pick-

ling processes is 651RMB per ton, the cost reduction in

these two processes is 296,000RMB every month. Then

the cost reduction each year is 3552,000RMB. At the

same time, the loss due to quality rejections is

125,000RMB in 2009. Such loss after this project can be

reduced by about 72,000RMB each year. It is noted that

the application cost during this project mainly includes

the salaries of Black Belts and various team members,

amounting to about 10,000RMB. Thus, the economic

beneﬁt is 3520,000RMB ($550,000) per year.

Factorial Fit: Thickness versus Strain, Compensation coefficient , Rolling parameter

Estimated Effects and Coefficients for Thickness (coded units)

Term Effect Coef SE Coef T P

Constant 1.84088 0.001061 1735.59 0.000

Strain 0.01125 0.00563 0.001061 5.30 0.034

Compensating coefficient 0.01575 0.00788 0.001061 7.42 0.018

Rolling parameter 0.01375 0.00687 0.001061 6.48 0.023

Strain*Compensating coefficient -0.00475 -0.00238 0.001061 -2.24 0.155

Strain*Rolling parameter 0.01125 0.00562 0.001061 5.30 0.034

Compensating coefficient* -0.00325 -0.00162 0.001061 -1.53 0.265

Rolling parameter

Curvature -0.00488 0.002031 -2.40 0.138

S = 0.003 R-Sq = 99.66% R-Sq(adj) = 95.43%

Analysis of Variance for Thickness (coded units)

Source DF Seq SS Adj SS Adj MS F P

Main Effects 3 0.00112738 0.00112738 0.00037579 41.75 0.023

2-Way Interactions 3 0.00031937 0.00031937 0.00010646 11.83 0.079

3-Way Interactions 1 0.00000613 0.00000613 0.00000613 0.68 0.496

Curvature 1 0.00005185 0.00005185 0.00005185 5.76 0.138

Residual Error 2 0.00001800 0.00001800 0.00000900

Pure Error 2 0.00001800 0.00001800 0.00000900

Total 10 0.00152273

Figure 10. Full factorial design analysis (full model).

Production Planning & Control 229

Factorial Fit: Thickness versus Strain, Compensation coefficient , Rolling parameter

Estimated Effects and Coefficients for Thickness (coded units)

Term Effect Coef SE Coef T P

Constant 1.83955 0.001468 1253.12 0.000

Strain 0.01125 0.00563 0.001721 3.27 0.017

Compensating coefficient 0.01575 0.00788 0.001721 4.57 0.004

Rolling parameter 0.01375 0.00688 0.001721 3.99 0.007

Strain*Rolling parameter 0.01125 0.00562 0.001721 3.27 0.017

S = 0.00286873 R-Sq = 98.82% R-Sq(adj) = 94.09%

Analysis of Variance for Thickness (coded units)

Source DF Seq SS Adj SS Adj MS F P

Main Effects 3 0.00112738 0.00112738 0.00037579 15.85 0.003

2-Way Interactions 1 0.00025312 0.00025312 0.00025312 10.68 0.017

Residual Error 6 0.00014223 0.00014223 0.00002370

Curvature 1 0.00005185 0.00005185 0.00005185 2.87 0.151

Lack of fit 3 0.00007238 0.00007238 0.00002413 2.68 0.283

Pure Error 2 0.00001800 0.00001800 0.00000900

Total 10 0.00152273

Figure 11. Factorial design analysis after optimisation (reduced model).

Table 6. The control plan of key factors.

No. Key factors Control style

Relative

unit

1 Process implementation of

rolling process

Check the implementation everyday Rolling

2 Implementation of thickness

inspection correctness

Check the thickness correctness everyday Inspection

3 Procedure of abnormal

thickness quality information

Thickness curve of abnormal coils has to be printed and recorded Rolling

4 Check and feedback of raw

material thickness control

Ten coils are sampled each month. The values of wedge and plate crown are

measured and fed back to the former process and management

Technique

5 Calibration of roller thickness

gauge

The compensating coefﬁcient of thickness gauge for all kinds of steels has to be

calibrated each month

Electric

6 Thickness standard plates Based on the average level of steel ingredients, thickness standard plates are

calibrated in automated company

Technique

7 Rolling strain The corresponding speciﬁcation between the ﬁnal product thickness and raw

material is planned. The requirement for raw materials is reported each month

according to the contracts

Production

230 M. Zhang et al.

5. Discussion

The above project is just one example of the Black Belt

and Green Belt projects ﬁnished in Company T. From

2009 to 2011, Company T successfully conducted 475

projects which yielded 600 million RMB ($100,000,000)

hard savings. Twenty-one projects were selected as

national excellent Six Sigma projects by the China Asso-

ciation for Quality (CAQ). And Company T was

awarded as Excellent Company for Six Sigma Imple-

mentation by CAQ.

For a typical Chinese state-owned enterprise, Com-

pany T gained competitive advantages through Six

Sigma deployment in terms of quality improvement, cost

reduction and service enhancement. Through our investi-

gation into Company T, we found the following key suc-

cess factors for its Six Sigma implementation. All these

factors are almost the same as the research ﬁndings of

the previous literature (Coronado and Antony 2002; Lin-

derman et al. 2003; Kwak and Anbari 2006; Pandey

2007; Schroeder et al. 2008; Zu, Fredendall, and

Douglas 2008; Kumar, Antony, and Cho 2009;

Büyüközkan and Öztürkcan 2010; Zu, Robbins, and

Fredendall 2010; Brun 2011; Nair, Malhotra, and Ahire

2011; Parast 2011; Manville et al. 2012).

5.1. Strong support and involvement of top

management

Because Six Sigma is a top-down management activity,

commitment of top management becomes a key success-

ful factor of Six Sigma implementation. Commitment

does not only mean strong support by providing visible

resources for Six Sigma, but also means personal

involvement or participation in Six Sigma projects. In

Company T, top leaders act as the champions of Six

Sigma projects, which can make sure that each project

links to the company strategy and guarantees resources

input in the improvement process.

5.2. Career plan of belt employees

Six Sigma will never succeed without active participation

of Black Belts, Green Belts and Yellow Belts. To

motivate these belts employees, Company T designed a

career plan for them besides a monetary reward based on

the hard savings of the successful projects they ﬁnished.

Some managers are selected from the Black Belt or

Master Black Belt employees. Thus, Six Sigma manage-

ment can be carried out by the managers of each level in

the organisation, and become their daily work. The

continuous improvement mechanism and culture are

formed through continuously ﬁnding projects, deﬁning

projects, managing projects and reviewing project

results.

5.3. Six Sigma infrastructure

Six Sigma infrastructure is one of the key elements to

maintain sustainable implementation of Six Sigma. In

Company T, a well-established infrastructure was estab-

lished at the very beginning when Six Sigma was

announced. A Six Sigma ofﬁce was formed to be

responsible for Six Sigma project management. The head

of the ofﬁce directly reported to the CEO. A ﬁve-year

Six Sigma implementation plan was drafted with speciﬁc

goals and tasks for each year. Also, a set of documents

was set up for Six Sigma project selection, project

review and ﬁnancial results assessment.

5.4. Well-established action-learning training system

The uniqueness of Six Sigma training is based on prob-

lem-solving. Projects were selected before project team

members received Six Sigma training. Six Sigma training

is divided into different phases such as DMAIC or

DMADV and the training is in parallel with project exe-

cution. The belts employees are required to utilise what

they learned in the classroom to their projects with the

help of consultants. And Company T established a hier-

archy of training system targeted at champions, Black

Belts, Green Belts, Yellow Belts, staff members and

front line workers.

5.5. Information system

Information system can also be regarded as an important

element of infrastructure for Six Sigma companies. Suc-

cessful Six Sigma implementation needs reliable data

collection and analysis, which were poor before Six

Sigma was introduced into Company T. Along with Six

Sigma deployment, Company T also introduced MES

and ERP systems and upgraded its intranet system. The

well-established information system provides online data

collections. And Six Sigma ofﬁce also developed its pro-

ject management system and put it on the website for

instant monitoring of project progress. Six Sigma project

success story sharing is also realised via intranet.

5.6. Six Sigma culture

For managers at each level, such idea as making use of

Six Sigma to promote operation performance and

increase company competition is sent out to each man-

agement area. All the managers know very well the core

of Six Sigma management and provide support and

resources to Six Sigma implementation. For engineers

and quality management employees, such idea as making

good use of data in Six Sigma implementation to achieve

quality management innovation is popularised. All of

them consciously use the theory and tools of Six Sigma

to raise the efﬁciency and quality management level of

Production Planning & Control 231

Company T. For the basic level employees, such idea as

using Six Sigma to reduce poor quality cost and increase

economic value added is practicable. Six Sigma manage-

ment becomes an essential part of their daily work.

5.7. Integration with other management methods

Other management methods such as Lean Production,

TPM, QC, ISO90001 and performance excellence model

were also introduced into Company T before Six Sigma

management. As mentioned above, Company T builds a

big Six Sigma umbrella at the corporate level which

includes Lean Production, TPM and others, since the

core value of these initiatives is continuous improve-

ment. The integration avoids the separations of continu-

ous improvement programmes with different names and

afﬁliated with different departments. And the integration

combines Six Sigma’s top-down strategy and the bot-

tom-up culture of lean to form critical mass for continu-

ous improvement.

6. Conclusions

It is well reported that many of the Top 500 corporations

in the world have implemented Six Sigma management

to improve their product and service quality. Systematic

and sustained applications of Six Sigma in China are,

however, not as widely known. This paper has outlined

the initiatives in the promotion of Six Sigma in one

famous steel organisation, namely Company T. A signiﬁ-

cant Black Belt project at this company is also pre-

sented.

It can be appreciated from the accounts given here

that Six Sigma has become a prime mover in a com-

pany’s drive for global competitiveness, and the aligned

statistical tools in Six Sigma offer unprecedented oppor-

tunities for non-statisticians to integrate analytical tools

with technical problem-solving. What follows is a chang-

ing company culture that results from the behaviour of

employees and managers alike, ultimately realising the

goal of a learning organisation. Business leaders with

organisational capability, project management techniques

and habits of statistical diagnosis have emerged along

with Six Sigma management. In fact, they are the ones

that planted the seeds for reform and increased competi-

tiveness of the company –this has certainly more signiﬁ-

cant and far-reaching implications than what many have

routinely seen in the DMAIC roadmap.

Funding

The authors were partially supported by the NSFC [grant

number 71002105], [grant number 71225006].

Notes on contributors

Min Zhang is an associate professor in the

College of Management and Economics,

Tianjin University. She received her MS in

materials engineering from Shandong

University, China, in 2003 and PhD in

management science and engineering from

Tianjin University, China, in 2006. Her

research interests focus on statistical quality

control, Six Sigma management and pro-

cess monitoring applications. She has published more than 20

papers in research journals, such as International Journal of

Production Economics, International Journal of Production

Research, Journal of Business Ethics, Total Quality Manage-

ment & Business Excellence, Quality and Reliability Engineer-

ing International et al.

Wei Wang is a quality engineer in Taiyuan Iron

& Steel Co., Ltd. He received his master of

engineering from the Tianjin University,

China, in 2011. His research interests focus on

Six Sigma management and quality control.

Thong Ngee Goh is a professor in the

Department of Industrial and Systems Engi-

neering at the National University of Singa-

pore. He has published some 300 peer-

reviewed research papers and ﬁve advanced

books related to Quality Engineering and

Management. He is currently on the edito-

rial boards of more than 10 research jour-

nals. His recent international honours and

competitive awards include: IAQ Inaugural Masing Medal in

2006 (for the book ‘Six Sigma: Advanced Tools for Black

Belts and Master Black Belts’, Wiley, UK), ASQ Statistics

Division William G Hunter award in 2007 and ASQ Eugene L

Grant Medal in 2012. He is one of the only two persons in the

world to have received both the Hunter the Grant awards from

ASQ, in the 50-year history of the Grant Medal. His research

interests focus on statistical process control, design of experi-

ment and Six Sigma management.

Zhen He is a professor in the College of

Management and Economics, Tianjin Uni-

versity. He is also the Six Sigma consultant

of Company T. He is the recipient of Out-

standing Research Young Scholar Award of

the National Natural Science Foundation of

China. He has published more than 100

papers and co-authored ﬁve books. He is

the chairman of the Six Sigma Expert

Steering Committee of China Association for Quality. His

research interests focus on quality management, statistical qual-

ity control, DOE and Six Sigma management.

232 M. Zhang et al.

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Abstract

I. Case study reporting is a complex task that requires the careful formatting and

presentation of relevant evidence.

Introduction

I. Case study results reporting is an intricate task requiring careful formatting and

presentation of relevant evidence (Alpi & Evans, 2019).

Case Study Report Audience and Reporting Methodology

I. Different case studies are conducted to address the needs of different potential audiences

(Yin, 2018).

II. According to Yin (2018), a case study investigation can have several potential audiences.

III. Yin (2018) discusses six approaches to composing a case study report.

Visual and Textual Materials of a Case Study Report

I. Case study data can be effectively reported by using a combination of visual and textual

materials (Midway, 2020).

II. Visual materials are used in reports to support textual materials (Midway, 2020).

Reporting Evidence: Striking the Balance

I. According to Kharasch et al. (2020), scientific studies are peer-reviewed by experts with

similar competencies by the researchers to ensure that the studies present quality findings

and reported findings are valid, among other things.

II. Peer review is one reason why a researcher should provide adequate evidence to help

experts evaluate their findings and conclusion (Kharasch et al., 2020).

Multiple-Case Case Study with Lean Six Sigma

I. The design multiple-case case study regards implementing the six sigma method in Hon

Hai Precision Industry Co., Ltd’s (Foxconn) manufacturing plants in China, Taiwan, and

Thailand.

II. Data relevant to the evaluation of process performance after implementing the lean six

sigma method will be collected to help determine whether the method is efficient in

improving Faxconn factories’ processes or otherwise.

Conclusion

I. Case study researchers have to be thorough when preparing the final case study report to

ensure that the report presents all necessary evidence to justify findings and conclusions

and caters to the needs of potential audiences.

Multiple-Case Case Study

Name

Institution Affiliation

Course Name

Instructor

Date

Author Note

Lakisha Lane

By submitting this assignment, I attest this submission represents my own work, and not

that of another student, scholar, or internet source. I understand I am responsible for

knowing and correctly utilizing referencing and bibliographical guidelines. I have not

submitted this work for any other class. Correspondence concerning this article should be

addressed to Lakisha Lane.

Email: lllane@liberty.edu

Abstract

Case study reporting is a complex task that requires the careful formatting and presentation of

relevant evidence. Case study report potential audiences include academics, policymakers,

sponsors or funders, committees, community leaders, practitioners, and relevant professionals.

Approaches used to report case study findings are the linear-analytic, comparative structure,

chronological structure, theory-building, suspense, and the unsequenced methods. Visual and

textual materials need to be effectively utilized in a case study report to improve the report’s

quality. The appropriate amount of evidence that a case study researcher should provide readers

is the evidence necessary to adequately evaluate all of the researchers’ findings and conclusions

regarding the research phenomenon. The Bible prohibits a Christian from lying. Colossians 3:9

states, “Lie not one to another, seeing that ye have put off the old man with his deeds” (King

James Bible, 2017). A Christian case study researcher ought not to lie in their case study report

as such would be unchristian.

Keywords: multiple-case case study, report audience, reporting methodology, visual

material, textual material

Introduction

Case study results reporting is an intricate task requiring careful formatting and

presentation of relevant evidence (Alpi & Evans, 2019). Evidence reporting needs to be guided

by a study’s target audience (Yin, 2018). Failure to consider the audience in evidence reporting

can result in a report that is inaccessible to the target audience or one that does not satisfy the

target audience's needs (Yin, 2018). A case study researcher has to determine the best visual aids

to use to help easily communicate research findings to the study’s intended audience (Yin, 2018).

Adequate evidence must be reported to aid readers to effectively assess a case study and its

findings (Yin, 2018). This discussion explains different case study audiences, reporting

methodologies, the textual and visual material that can be utilized in a case study report, and the

right amount of evidence to provide readers to help them understand a study. The discussion also

presents a sample multiple-case case study design aimed at evaluating the execution of the lean

six sigma methodology in an organization.

Case Study Report Audience and Reporting Methodology

Different case studies are conducted to address the needs of different potential audiences

(Yin, 2018). To ensure that a case study report suits the target audience's needs and can be easily

read by the audience, researchers have to carefully consider their reporting methodology vis-à-

vis the target audience (Shulman et al., 2020). Failure to make such consideration would result in

a case study report that either fails to suit target audience needs or is inaccessible to the target

audience (Shulman et al., 2020). Getting other people to review draft case study reports can help

improve the report (Yin, 2018). Thus, ensuring that it effectively presents case study evidence

vis-à-vis the target audience.

Case Study Report Audience

According to Yin (2018), a case study investigation can have several potential audiences.

One potential audience for a case study is an academic audience. Academics may read through a

case study report to understand a research phenomenon or identify the need for further research,

among other things. Policymakers are other potential audiences for a case study report.

Policymakers would be largely interested in a case study's contribution to policy evaluation or

policy-related decision-making (Uneke et al., 2018). Research sponsors or funders are other

potential case study audiences (Yin, 2018). For example, a business organization may sponsor or

fund a case study to help improve its processes or operations. Other potential audiences include

thesis committees, community leaders, practitioners, and relevant professionals (Yin, 2018). The

diverse range of potential audiences’ mean that case study researchers must tailor their reports to

cater to potential audiences’ needs (Yin, 2018).

Reporting Methodology

Yin (2018) discusses six approaches to composing a case study report. One of the

approaches is the linear-analytic method. The reporting method involves linearly writing

research report subtopics. A researcher begins with the problem or issue subtopic then proceeds

to the sequentially discuss the subtopics that are part of the analytic reporting approach. Another

reporting methodology is the comparative structure method. The approach involves comparing

differing explanations or descriptions in a report. The third methodology is the chronological

structure method. It involves presenting case study evidence in chronological order. Another

reporting approach open to case study researchers is the theory-building approach. The theory-

building approach involves presenting a theoretical argument in each report section. The fifth

reporting methodology is the suspense approach. It involves discussing the main outcome in a

report’s initial section or chapter and discussing explanations for the main outcome in the later

chapters. The sixth reporting approach available to case study researchers is the unsequenced

method which involves the report does not follow any particular sequence. When the sixth

approach is used, report sections or chapters carry no particular importance.

Visual and Textual Materials of a Case Study Report

Case study data can be effectively reported by using a combination of visual and textual

materials (Midway, 2020). Visual materials are used to visualize data (Midway, 2020). Data

visualization concerns the communication of data or information through the utilization of visual

objects (Midway, 2020). One of the visual materials or objects used to report case study data is

tables (Midway, 2020). Textual or numerical case study data or information can be formatted in

the form of a table to help ease the reading and understanding the data or information. Another

visualization object is graphs (Midway, 2020). Research data can be plotted into graphs for

easier reading and understanding (Midway, 2020). The third visual method is charting (Midway,

2020). Pie charts, bar charts, and line charts are examples of charts that can be used to easily

report case study data or information (Midway, 2020). A map is another visual material that can

be used to report case study data or information. (Midway, 2020) The utilization of visuals helps

make case study reports accessible to potential audiences (Midway, 2020).

Visual materials are used in reports to support textual materials (Midway, 2020). Textual

materials regard words, sentences, and paragraphs used to deliver certain information (Midway,

2020). According to Rashid et al. (2019), case study findings have to be explained thoroughly

using effective sentences and paragraphs. Textual materials are necessary in all case study report

sections. Text is needed to present the introduction, review relevant literature, methods used to

conduct the case study, findings, discussion, and conclusion, among other components of a case

study report (Yin, 2018). Textual materials are also needed to support visual objects or explain

the visual objects (Midway, 2020). The potential audience must inform the textual materials used

in a case study report to ensure that the report is accessible to the audience (Yin, 2018).

Reporting Evidence: Striking the Balance

According to Kharasch et al. (2020), scientific studies are peer-reviewed by experts with

similar competencies by the researchers to ensure that the studies present quality findings and

reported findings are valid, among other things. For a study to be effectively peer-reviewed, a

researcher has to clearly explain the method that they used to conduct the study, the evidence

collected and analyzed, and how they arrived at their conclusions based on analyzed evidence.

Thus, a researcher does not need to only prove to peer-reviewers how they arrived at their

conclusion. They also have to provide adequate evidence to help the reviewers arrive at their

conclusion regarding a research phenomenon. The appropriate amount of evidence that a case

study researcher should provide readers is the evidence necessary to adequately evaluate all of

the researchers’ findings and conclusions regarding the research phenomenon. Without adequate

evidence to evaluate all findings and conclusions, a reader cannot reliably arrive at their

conclusion regarding a particular case study.

Peer review is one reason why a researcher should provide adequate evidence to help

experts evaluate their findings and conclusion (Kharasch et al., 2020). Providing adequate

evidence to evaluate a case study's findings and conclusion and for the readers to come to their

conclusions is important as it would help prevent a study from spreading biased findings and

conclusions to readers (Kharasch et al., 2020). If a study’s findings and conclusions are biased

and there is no adequate evidence provided in the study report that can help identify the bias,

readers may accept the biased findings and conclusions and have a distorted image of reality

(Kharasch et al., 2020). A case study researcher should provide evidence that will help support

their findings and conclusions and also help readers evaluate their findings and conclusions.

Multiple-Case Case Study with Lean Six Sigma

The design multiple-case case study regards implementing the six sigma method in Hon

Hai Precision Industry Co., Ltd’s (Foxconn) manufacturing plants in China, Taiwan, and

Thailand. Foxconn is a manufacturing services provider with factories in countries in Asia,

Europe, and South America (Foxconn, n.d.). Foxconn is well-known for manufacturing iPhone

smartphones on behalf of Apple (Foxconn, n.d.). Foxconn aims to improve manufacturing

processes in its different factories worldwide. A lot of waste has been resulting from the

processes. Foxconn has decided to test the lean six sigma method in improving process

performance and reducing waste in three of its factories situated in China, Taiwan, and Thailand.

The three factories are the units of analysis. The multiple-case case study aims to evaluate the

performance of the lean six sigma method in Faxconn's China, Taiwan, and Thailand factories.

Data relevant to the evaluation of process performance after implementing the lean six

sigma method will be collected to help determine whether the method is efficient in improving

Faxconn factories’ processes or otherwise. Evidence sources for the study will include

interviews, documents, and archival records. The evidence from each case will first be analyzed

to evaluate lean six sigma's impact on the factories processes. Cross-case analysis and synthesis

will be conducted for all three cases to help evaluate whether the lean six sigma method is

effective in the three factories or otherwise. The cross-case analysis and synthesis will help

Foxconn determine whether there are factory-specific factors vital to the successful

implementation of the lean six sigma method in different factories. The case study will help

effectively implement lean six sigma on all Foxconn's factories if the company opts for the same.

Conclusion

Case study researchers have to be thorough when preparing the final case study report to

ensure that the report presents all necessary evidence to justify findings and conclusions and

caters to the needs of potential audiences. Case study report potential audiences include

academics, policymakers, sponsors or funders, committees, community leaders, practitioners,

and relevant professionals. The utilization of the relevant reporting methodology would help

effectively report research findings. Case study researchers must provide enough evidence for

readers to draw independent conclusions regarding their studies. One biblical teaching that ought

to guide case study reporting is honesty. Honesty regards being truthful. The Bible prohibits a

Christian from lying. Colossians 3:9 states, “Lie not one to another, seeing that ye have put off

the old man with his deeds” (King James Bible, 2017). A Christian case study researcher ought

not to lie in their case study report as such would be unchristian. Lying would also be contrary to

research ethics.

References

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reports as a publication type. Journal of the Medical Library Association: JMLA, 107(1),

1-5. https://doi.org/10.5195/jmla.2019.615

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https://doi.org/10.1080/09537287.2014.891058

Kharasch, E., Avram, M., Clark, J., Davidson, A., Houle, T., & Levy, J. et al. (2020). Peer

Review Matters: Research Quality and the Public Trust. Anesthesiology, 134(1), 1-6.

https://doi.org/10.1097/aln.0000000000003608

King James Bible. (2017). King James Bible

Online. https://www.kingjamesbibleonline.org/Colossians-3-9/ (Original work published

1769)

Midway, S. (2020). Principles of Effective Data Visualization. Patterns, 1(9), 100141.

https://doi.org/10.1016/j.patter.2020.100141

Rashid, Y., Rashid, A., Warraich, M. A., Sabir, S. S., & Waseem, A. (2019). Case study method:

A step-by-step guide for business researchers. International Journal of Qualitative

Methods, 18, 1609406919862424. https://doi.org/10.1177/1609406919862424

Shulman, H. C., Dixon, G. N., Bullock, O. M., & Colón Amill, D. (2020). The effects of jargon

on processing fluency, self-perceptions, and scientific engagement. Journal of Language

and Social Psychology, 39(5-6), 579-597. https://doi.org/10.1177/0261927X20902177

Uneke, C. J., Ezeoha, A. E., Uro-Chukwu, H. C., Ezeonu, C. T., & Igboji, J. (2018). Promoting

researchers and policy-makers collaboration in evidence-informed policy-making in

Nigeria: outcome of a two-way secondment model between university and health

ministry. International journal of health policy and management, 7(6), 522.

https://doi.org/10.15171/ijhpm.2017.123

Yin, R. K. (2018). Case study research and applications: Design and methods (6th edition).

SAGE.

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