Role of Statistics in Business and Industry

GERALD J. HAHN, PhD, was manager of applied statistics in the Corporate Research and Development Center at General Electric (GE) for twenty-eight years, where he was named a GE Coolidge Fellow, the organization's highest honor. Dr. Hahn is the coauthor of Statistical Models in Engineering and Statistical Intervals: A Guide for Practitioners, both published by Wiley. NECIP DOGANAKSOY, PhD, is a Statistician and Principal Technologist at General Electric's Global Research Center and is also Adjunct Professor in the School of Management at Union Graduate College. A Six Sigma Master Black Belt, Dr. Doganaksoy has written over fifty papers and journal articles on statistical applications in quality, reliability, and productivity improvement.

• Major Applications. Preface.Acknowledgments.PART I. SETTING THE STAGE.Chapter 1. Statistics: An Overview.1.1 About this Chapter.1.2 What is Statistics?1.3 Areas of Application.1.4 Statistical Literacy.1.5 Better Decisions Require Better Data.1.6 Statistical Thinking.1.7 Related Disciplines.1.8 Major Takeaways.Discussion Questions.Chapter 2. Statistics in Business and Industry.2.1 About this Chapter.2.2 Evolution of Statistics for Manufactured Product Applications.2.3 Applications Beyond Manufactured Products.2.4 Forces Impacting the Use of Statistics Today.2.5 Major Takeaways.Discussion Questions.PART II. MANUFACTURED PRODUCT APPLICATIONS.Chapter 3. Product Design: Concepts.3.1 About this Chapter.3.2 The Product Design Process.3.3 Setting the Design Goals.3.4 Ensuring Measurement Capability.3.5 Design and Development.3.6 Design Validation.3.7 Transition to Manufacturing.3.8 Major Takeaways.Discussion Questions.Chapter 4. Product Design: Example.4.1 About this Chapter.4.2 Thermoplastic Resin for Child Car Seat: Introduction.4.3 Some Basic Elements of Plastic Part Design and Manufacture.4.4 Setting the Design Goals.4.5 Ensuring Measurement Capability.4.6 Design and Development.4.7 Design Validation.4.8 Transition to Manufacturing.4.9 Major Takeaways.Discussion Questions.Chapter 5. Product Reliability Assurance.5.1 About this Chapter .5.2 The Key Role of Reliability.5.3 Design for Reliability: The Need.5.4 The Process and the Participants.5.5 Setting Reliability Goals.5.6 Reliability Evaluation of a Conceptual Design.5.7 Product Reliability Development.5.8 Reliability Validation.5.9 Product Safety.5.10 Reliability Growth Analysis.5.11 Product Burn-In.5.12 Software Reliability.5.13 Further Reading.5.14 Major Takeaways.Appendix: Product Life Distributions and Concepts.Discussion Questions.Chapter 6. Manufacturing Quality Improvement: Concepts.6.1 About this Chapter.6.2 The Need for Manufacturing Quality Improvement.6.3 Different Industries.6.4 Considerations in Manufacturing Quality Improvement.6.5 Disciplined Approaches to Manufacturing Quality Improvement.6.6 Quality Assessment and Improvement.6.7 Statistical Monitoring.6.8 Major Takeaways.Discussion Questions.Chapter 7. Manufacturing Quality Improvement: Example.7.1 About this Chapter.7.2 Generator Stator Bar Example.7.3 Manufacturing Capability and Stability Assessment.7.4 Addressing Measurement Error.7.5 Reducing Deviations from Target and Variability.7.6 Statistical Monitoring.Discussion Questions.Chapter 8. Product Manufacturing: Further Applications.8.1 About this Chapter.8.2 Integrating Engineering Process Control and Statistical Process Control.8.3 Polymer Resin Example.8.4 Materials and Parts Quality Assurance.8.5 Final Product Assessment.8.6 Productivity Improvement.8.7 Major Takeaways.Discussion Questions.Chapter 9. Product Field Support.9.1 About this Chapter.9.2 Reliability Data Tracking.9.3 Reliability Data Tracking for Nonrepairable Products.9.4 Reliability Data Tracking for Repairable Products.9.5 Planning the Failure Reporting System.9.6 A Note on Product Safety .9.7 Tracking Customer Satisfaction.9.8 Competitive Evaluations and Advertising Claims.9.9 Proactive Product Servicing.9.10 Major Takeaways.Discussion Questions.PART III. OTHER APPLICATIONS.Chapter 10. Pharmaceutical Products.10.1 About this Chapter.10.2 Drug Development: Process Overview.10.3 The Role of a Pharmaceutical Statistician: An Overview.10.4 Preclinical Studies.10.5 Clinical Studies.10.6 Case Study: Phase 2 Clinical Trial.10.7 Regulatory Review.10.8 Some Other Applications.10.9 Some Statistical Tools Used in Pharmaceutical Applications.10.10 Sources of Further Information.10.11 Major Takeaways.Discussion Questions.Chapter 11. Financial Services.11.1 About this Chapter .11.2 Financial Services and Its Uncertainties: .11.3 Credit Scoring for Consumer Loan Approval .11.4 Credit Scoring Example .11.5 Model Development and Implementation: Some Important Nitty-Gritties.11.6 Modeling in Credit Management: A Broader Look.11.7 Specific Application Areas.11.8 Statisticians in Financial Services.11.9 Further Reading.11.10 Major Takeaways.Discussion Questions.Chapter 12. Business Processes.12.1 About this Chapter.12.2 Business Processes.12.3 Example: Improving the Loan Decision Process for a Business Equipment Financing Company.12.4 Steps for Process Improvement.12.5 Another Example: Improving the Skip Tracing Process.12.6 Some Further Concepts and Methods.12.7 Operations Research and Management Science.12.8 Major Takeaways.Discussion Questions.Chapter 13. Further Applications.13.1 About this Chapter.13.2 Food, Beverage and Related Industries.13.3 Semiconductor Industry.13.4 Communications Industry.13.5 Statistical Image Analysis for Medical, Security and Other Applications.13.6 Other Application Areas.13.7 Emerging Areas: A Glance Into the Future.13.8 Major Takeaway.Discussion Questions.References.Index.

“The wealth of applied examples and clear language will attract student readers and keep their attention whilst reading what is at times highly technical information.”   (Significance, 1 March 2011)"This book is not just of interest to statisticians, but may be even more valuable to professionals outside of our area, such as managers and engineers, who are frequently involved in data-based decisions...  I appreciate the authors’ strategy to motivate statistical tools by first posing the business problem or industrial question of interest. Every chapter of the book concludes with a summary of “Major Takeaways” and a set of useful and stimulating discussion questions. The book can also serve as a resource for aspiring statisticians, providing insight into the daily work of our profession." (The American Statistician, August 2009) "The Role of Statistics in Business and Industry is a perfect name for this book. The authors provide a powerful discussion on the challenges of business and industry and how statistics and statistical thinking fit in attaching those challenges. The book is meaningful, relevant and valuable to students, educators, technical professionals, managers and executives in their quest to field highly-reliable products, services and organizations to meet the challenges of today's marketplace." (Journal of Quality Technology, April 2009)"With its emphasis on real-world problems and applications, this is a good handbook for all statisticians in the manufacturing field. It also could be used in graduate or industrial training classes." (Quality Progress, April 2009)"This book is meaningful, relevant and valuable to students, educators, technical professionals, managers and executives in their quest to field highly-reliable products, services and organizations to meet the challenges of today’s marketplace." (Journal of Quality Technology Vol. 41, No. 2, April 2009)"Highlighting the relevance of statistical methods in everyday applications, the book addresses more than 45 application areas that keep the use of statistics fresh and pertinent." (Entrepreneur, 2009)"Undergraduate students will find valuable connection points with the basic theory they are learning while manufacturing the managers overseeing projects on statistics will find valuable enlightenment here." (MAA Reviews, December 2008)"This book is a unique resource guide that addresses relevant problems and case studies in the areas of business and industry prior to any discussion of the statistical methods necessary to resolve these problems. Highly recommended.(CHOICE, December 2008)