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E-grāmata: Six Sigma Case Studies with Minitab® [Taylor & Francis e-book]

(Northeastern University, Boston, USA), (Southern New Hampshire University, Manchester, USA)
  • Formāts: 318 pages, 52 Tables, black and white; 395 Illustrations, black and white
  • Izdošanas datums: 06-Feb-2014
  • Izdevniecība: CRC Press Inc
  • ISBN-13: 9780429189739
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  • Taylor & Francis e-book
  • Cena: 164,53 €*
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  • Standarta cena: 235,05 €
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Six Sigma Case Studies with Minitab®Palielināt
  • Formāts: 318 pages, 52 Tables, black and white; 395 Illustrations, black and white
  • Izdošanas datums: 06-Feb-2014
  • Izdevniecība: CRC Press Inc
  • ISBN-13: 9780429189739
Citas grāmatas par šo tēmu:
Taylor & Francis e-booksMore info about Taylor & Francis e-books
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.
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.
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