Statistical Engineering : An Algorithm for Reducing Variation in Manufacturing Processes.

Intro -- Contents -- Material on Enclosed CD-ROM -- Figures and Tables -- Acknowledgments -- Preface -- 1 Introduction -- PART I Setting the Stage -- 2 Describing Processes -- 3 Seven Approaches to Variation Reduction -- 4 An Algorithm for Reducing Variation -- 5 Obtaining Process Knowledge Empirically -- PART II Getting Started -- 6 Defining a Focused Problem -- 7 Checking the Measurement System -- 8 Choosing a Working Variation Reduction Approach -- PART III Finding a Dominant Cause of Variation -- 9 Finding a Dominant Cause Using the Method of Elimination -- 10 Investigations to Compare Two Families of Variation -- 11 Investigations to Compare Three or More Families of Variation -- 12 Investigations Based on Single Causes -- Chapter 13 Verifying a Dominant Cause -- PART IV Assessing Feasibility and Implementing a Variation Reduction Approach -- 14 Revisiting the Choice of Variation Reduction Approach -- 15 Moving the Process Center -- 16 Desensitizing a Process to Variation in a Dominant Cause -- 17 Feedforward Control Based on a Dominant Cause -- 18 Feedback Control -- 19 Making a Process Robust -- 20 100% Inspection -- 21 Validating a Solution and Holding the Gains -- References -- Index -- Case Studies -- Case Study I Brake Rotor Balance -- Case Study II Rod Thickness -- Case Study III Crankshaft Main Diameter -- Exercises -- Exercise Solutions -- Chapter Supplements -- Chapter 2 Supplement Describing Processes -- Chapter 4 Supplement An Algorithm for Reducing Variation -- Chapter 5 Supplement Obtaining Process Knowledge Empirically -- Chapter 6 Supplement Defining a Focused Problem -- Chapter 7 Supplement Checking the Measurement System -- Chapter 9 Supplement Finding a Dominant Cause Using the Method of Elimination -- Chapter 10 Supplement Investigations to Compare Two Families of Variation.

Chapter 11 Supplement Investigations to Compare Three or More Families of Variation -- Chapter 12 Supplement Investigations Based on Single Causes -- Chapter 13 Supplement Verifying a Dominant Cause -- Chapter 15 Supplement Moving the Process Center -- Chapter 16 Supplement Desensitizing a Process to Variation in a Dominant Cause -- Chapter 17 Supplement Feedforward Control Based on a Dominant Cause -- Chapter 18 Supplement Feedback Control -- Chapter 19 Supplement Making a Process Robust -- Using MINITAB -- Appendix A Data Storage and Manipulation -- Appendix B Numerical Summaries -- Appendix C Graphical Summaries -- Appendix D Analysis of Variance (ANOVA) -- Appendix E Regression Models and Analysis -- Appendix F Planning and Analysis of Designed Experiments.

Description based on publisher supplied metadata and other sources.

Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2024. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries.