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Six Sigma Case Studies with Minitab® [Hardback]

3.50/5 (4 ratings by Goodreads)
(Southern New Hampshire University, Manchester, USA), (Northeastern University, Boston, USA)
  • Formāts: Hardback, 318 pages, height x width: 234x156 mm, weight: 750 g, 52 Tables, black and white; 395 Illustrations, black and white
  • Izdošanas datums: 06-Feb-2014
  • Izdevniecība: CRC Press Inc
  • ISBN-10: 1482205572
  • ISBN-13: 9781482205572
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Six Sigma Case Studies with Minitab®Palielināt
  • Formāts: Hardback, 318 pages, height x width: 234x156 mm, weight: 750 g, 52 Tables, black and white; 395 Illustrations, black and white
  • Izdošanas datums: 06-Feb-2014
  • Izdevniecība: CRC Press Inc
  • ISBN-10: 1482205572
  • ISBN-13: 9781482205572
Citas grāmatas par šo tēmu:
Permanent link: https://www.kriso.lv/db/9781482205572.html
Keywords:
The case studies presented in this volume illustrate the use of the quality analysis and improvement tools of the Minitab statistical software for Six Sigma projects. After an introduction to Six Sigma quality and the techniques and tools, the case studies follow, which involve health care, manufacturing, airline, fast food, and other sectors, and the tools of confidence interval estimation, hypothesis testing, chi-square analysis, process capability analysis, binary logistic regression, item analysis, cluster analysis, mixture design and analysis of experiments, multivariate analysis, Pareto charts, cause-and-effect diagrams, gage repeatability and reproducibility analysis, Taguchi design and analysis of experiments, factorial design and analysis of experiments, and statistical control charts. Each case study follows the DMAIC (define, measure, analyze, improve, and control) or DMADV (define, measure, analyze, design, and verify) approach. Annotation ©2014 Ringgold, Inc., Portland, OR (protoview.com) What happens when one of the most widely used quality improvement methodologies meets the world’s leading statistical software for quality improvement? Packed with case studies in a variety of sectors, including health care, manufacturing, airlines, and fast food restaurants, Six Sigma Case Studies with Minitab® shows you how to maximize the quality analysis and improvement tools available in Minitab® for your Six Sigma projects.Highly illustrated, the book includes detailed steps and more than 380 screenshots that explain how to use:Confidence Interval EstimationHypothesis TestingChi-Square AnalysisProcess Capability AnalysisBinary Logistic RegressionItem AnalysisCluster AnalysisMixture Design and Analysis of ExperimentsMultivariate AnalysisPareto ChartsCause-and-Effect DiagramGage Repeatability and Reproducibility AnalysisTaguchi Design and Analysis of ExperimentsFactorial Design and Analysis of ExperimentsStatistical Control ChartsThe case studies demonstrate the wide range of sectors and uses for Six Sigma and Minitab®. The screenshots provide exceptional detail and the book includes explanations for many Six Sigma terms and an appendix with the contents of the Minitab® worksheets that are referred to in most of the chapters. These features and more give you the tools to meet the challenges of continuous improvement expected in today’s marketplace.

Recenzijas

"This book is authored by experienced professors who have been teaching in the area and have also done several projects extensively. Six Sigma has been the most popular and widely used technique with the manufacturers for ensuring process quality these days. Therefore, the importance of a book for understanding Six Sigma in all its potential is highly welcome. The authors have done extremely well to present it in a simple-to-understand language and bring out the potential of Six Sigma by presenting numerous case studies ... As is well-known that Six Sigma uses a five-step methodology, called DMAIC, namely, Define, Measure, Analyze, Improve, and Control. The authors clearly demonstrate these steps with each and every case study presented. ... The book is recommended to all graduate students interested in quality engineering and to managers in various companies desirous of improving quality of their products or services." Krishna B. Misra, International Journal of Performability Engineering

"This book is an eclectic mix of case studies representing a diversity of industries, including healthcare, manufacturing, airlines and restaurants. The authors demonstrate how to combine the power of Six Sigma with Minitab to analyze data. The book starts with an introduction to Six Sigma quality, providing definitions for important terms with accompanying examples.... The authors follow the define, measure, analyze, improve and control method for each problem by indicating what kind of coverage the reader can expect for each phase. ... The book includes detailed steps and several pages of screenshots for conducting the analyses in Minitab. The contents of the Minitab worksheets are in the appendix and also can be downloaded from the publishers website. ... This book is a good reference and will be most useful to individuals engaged in continuous process improvement and Six Sigma, and those teaching, training or conducting analyses using Minitab." Kunita R. Gear, in Quality Progress (QP) Reviews, March 2016

"In the quality management literature, there is no shortage of Six Sigma books. However, many books on this topic take a conceptual approach, describing aspects of the Six Sigma philosophy or management approach in detail while glossing over the intricacies of how to actually organize and execute the analytical portion of Six Sigma projects. The latter information is particularly useful to practitioners and those applying for certification; unfortunately, without a portfolio of Six Sigma projects already completed, this background can be hard to come by. Pochampally and Guptas book effectively satisfies that gap." Dr. Nicole Radziwill, Quality Management Journal, Vol. 21, No. 3

" an excellent tool for both new and experienced Minitab users. This book is a must have for anyone looking to incorporate Six Sigma in their organization." James Brough, Chamberlain Companies Inc.

" provides a breadth of material combined with detailed illustration of its use that will make it valuable for any QA team trying to ensure the quality of their process statistically. The case studies and the careful step-by-step illustration of the statistical techniques make their practical implementation and their implications apparent. I intend to bring this book in as part of our training and reference material." Derek Kane, DEKA Research and Development Corporation

"This book serves a dual purpose as a quick reference guide for statistical tools and techniques used in Continuous Improvement/Six-Sigma/Quality departments of several organizations across various industries and as a handbook of Minitab with detailed screenshots that will immensely help readers with no prior experience with Minitab as well as seasoned Minitab users." Satish Nukala, PhD, Halliburton Energy Services

" a very timely and useful book. I believe industry professional, academicians, and students will greatly benefit from this source." Elif Kongar, University of Bridgeport

"Very well written in simple language to understand application of Minitab for Six Sigma case studies. A good reference book for six Sigma professionals." Dr. Abdul Razzak Rumane, Dar Alkuwait Alkhaleejia, Kuwait

Preface xi
Acknowledgments xiii
About the Authors xv
Section I Background
1 Introduction to Six Sigma Quality
3(12)
1.1 Definitions
3(7)
1.1.1 Defects Per Million Opportunities (DPMO)
5(39)
1.1.1.1 DPMO Example 1
5(2)
1.1.1.2 DPMO Example 2
7(2)
1.1.1.3 DPMO Example 3
9(1)
1.2 DMAIC Approach
10(1)
1.3 Book Outline
11(2)
References
13(2)
2 Quality Analysis and Improvement Tools/Techniques Used in This Book
15(8)
2.1 Confidence Interval Estimation
15(1)
2.2 Hypothesis Testing
15(1)
2.3 Chi-Square Analysis
16(1)
2.4 Process Capability Analysis
16(1)
2.5 Binary Logistic Regression
17(1)
2.6 Item Analysis
17(1)
2.7 Cluster Analysis
17(1)
2.8 Mixture Design and Analysis of Experiments
17(1)
2.9 Multivariate Analysis
18(1)
2.10 Pareto Chart
18(1)
2.11 Cause-and-Effect Diagram
18(1)
2.12 Gage Repeatability and Reproducibility Analysis
18(1)
2.13 Taguchi Design and Analysis of Experiments
19(1)
2.14 Factorial Design and Analysis of Experiments
19(1)
2.15 Statistical Control Charts
19(1)
2.16 Normality Test
19(1)
2.17 Analysis of Variance (ANOVA)
20(1)
References
20(3)
Section II Six Sigma Case Studies
3 Confidence Intervals to Assess Variation in Fat Content at a Fast-Food Restaurant
23(20)
3.1 Define Phase
23(1)
3.2 Measure Phase
23(8)
3.3 Analyze Phase
31(1)
3.4 Improve Phase
31(11)
3.5 Control Phase
42(1)
4 Hypothesis Testing for Quality Control at a Manufacturing Company
43(18)
4.1 Define Phase
43(1)
4.2 Measure and Analyze Phases
44(16)
4.2.1 Test 1
44(2)
4.2.2 Test 2
46(1)
4.2.3 Test 3
47(13)
4.3 Improve and Control Phases
60(1)
5 Chi-Square Analysis to Verify Quality of Candy Packets
61(20)
5.1 Define Phase
61(1)
5.2 Measure Phase
61(1)
5.3 Analyze Phase
62(17)
5.4 Improve and Control Phases
79(2)
6 Process Capability Analysis at a Manufacturing Company
81(24)
6.1 Define Phase
82(1)
6.2 Measure Phase
82(2)
6.3 Analyze Phase
84(4)
6.4 Improve Phase
88(15)
6.5 Control Phase
103(2)
7 Binary Logistic Regression to Predict Customer Satisfaction at a Restaurant
105(14)
7.1 Define Phase
105(1)
7.2 Measure Phase
106(1)
7.3 Analyze Phase
106(12)
7.4 Improve and Control Phases
118(1)
8 Item Analysis and Cluster Analysis to Gather "Voice of the Customer" (VOC) Data from Employees at a Service Firm
119(18)
8.1 Define Phase
119(1)
8.2 Measure Phase
120(4)
8.3 Analyze Phase
124(11)
8.4 Improve and Control Phases
135(2)
9 Mixture Designs to Optimize Pollution Level and Temperature of Fuels
137(24)
9.1 Define Phase
137(1)
9.2 Measure Phase
137(1)
9.3 Analyze Phase
137(23)
9.4 Design and Verify Phases
160(1)
10 Multivariate Analysis to Reduce Patient Waiting Time at a Medical Center
161(24)
10.1 Define Phase
161(1)
10.2 Measure Phase
161(2)
10.3 Analyze Phase
163(20)
10.4 Improve Phase
183(1)
10.5 Control Phase
183(2)
11 Pareto Chart and Fishbone Diagram to Minimize Recyclable Waste Disposal in a Town
185(10)
11.1 Define and Measure Phases
185(2)
11.2 Analyze Phase
187(7)
11.3 Improve and Control Phases
194(1)
12 Measurement System Analysis at a Medical Equipment Manufacturer
195(20)
12.1 Define Phase
195(1)
12.2 Measure Phase
195(18)
12.3 Analyze, Improve, and Control Phases
213(2)
13 Taguchi Design to Improve Customer Satisfaction of an Airline Company
215(16)
13.1 Define Phase
215(3)
13.2 Measure Phase
218(1)
13.3 Analyze Phase
219(10)
13.4 Improve and Control Phases
229(2)
14 Factorial Design of Experiments to Optimize a Chemical Process
231(26)
14.1 Define Phase
231(1)
14.2 Measure Phase
231(6)
14.3 Analyze Phase
237(18)
14.4 Improve and Control Phases
255(2)
15 Chi-Square Test to Verify Source Association with Parts Purchased and Products Produced
257(16)
15.1 Define Phase
257(1)
15.2 Measure Phase
257(1)
15.3 Analyze Phase
258(14)
15.4 Improve and Control Phases
272(1)
Appendix 273(20)
Index 293
Kishore K. Pochampally, PhD, is an associate professor of quantitative studies, operations and project management at Southern New Hampshire University (SNHU) in Manchester (NH). His prior academic experience is as a post-doctoral fellow at Massachusetts Institute of Technology (MIT) in Cambridge (MA). He earned a PhD in industrial engineering from Northeastern University in Boston. He teaches Six Sigma courses at SNHU and conducts Lean Six Sigma training at service organizations. He is a Six Sigma Black Belt (American Society for Quality) and a Project Management Professional (PMP®). Surendra M. Gupta, PhD, PE, is a professor of mechanical and industrial engineering and the director of the Laboratory for Responsible Manufacturing, Northeastern University. He earned his BE in electronics engineering from Birla Institute of Technology and Science, his MBA from Bryant University, and his MSIE and PhD in industrial engineering from Purdue University. He is a registered professional engineer in the state of Massachusetts. Dr. Guptas research interests are in the areas of production/ manufacturing systems and operations research. He is mostly interested in environmentally conscious manufacturing, reverse and closed-loop supply chains, disassembly modeling, and remanufacturing. He has authored or coauthored more than 450 technical papers published in books, journals, and international conference proceedings. His publications have been cited by thousands of researchers all over the world in journals, proceedings, books, and dissertations. He has traveled to all seven continentsAfrica, Antarctica, Asia, Australia, Europe, North America, and South Americaand presented his work at international conferences on six continents. Dr. Gupta has taught more than 100 courses in such areas as operations research, inventory theory, queueing theory, engineering economy, supply chain management, and production planning and control. He has received many recognitions, including the Outstanding Research Award and Outstanding Industrial Engineering Professor Award (in recognition of teaching excellence) from Northeastern University and the National Outstanding Doctoral Dissertation Advisor Award.