Introduction to Engineering Statistics and Six Sigma

Many have heard that six sigma methods are necessary to survive, let alone thrive, in today's competitive markets, but are not really sure what the methods are or how or when to use them.

Introduction to Engineering Statistics and Six Sigma contains precise descriptions of all of the many related methods and details case studies showing how they have been applied in engineering and business to achieve millions of dollars of savings. Specifically, the methods introduced include many kinds of design of experiments (DOE) and statistical process control (SPC) charting approaches, failure mode and effects analysis (FMEA), formal optimization, genetic algorithms, gauge reproducibility and repeatability (R&R), linear regression, neural nets, simulation, quality function deployment (QFD) and Taguchi methods. A major goal of the book is to help the reader to determine exactly which methods to apply in which situation and to predict how and when the methods might not be effective.

Illustrative examples are provided for all the methods presented and exercises based on case studies help the reader build associations between techniques and industrial problems. A glossary of acronyms provides familiarity with six sigma terminology and solutions to homework and practice exams are included.

Auteur

Dr Theodore Allen is an associate professor in Industrial and Systems Engineering at The Ohio State University and a co-founder of the software company, Sagata Ltd. He is a senior member of the American Society of Quality and an associate editor of The Journal of Manufacturing Systems (Elsevier).

Texte du rabat

This book contains precise descriptions of all of the many related six sigma methods. It also includes many case studies that detail how these methods have been applied in engineering and business to achieve millions of dollars of savings. This book will help readers to determine exactly which methods to apply in which situations and to predict how and when the methods might not be effective. Illustrative examples are provided for all the methods presented and exercises based on the case studies help build associations between techniques and industrial problems.

Contenu

List of Acronyms Introduction Part I Statistical Quality Control Statistical Quality Control and Six Sigma Define Phase and Strategy Measure Phase and Statistical Charting Analyze Phase Improve or Design Phase Control or Verify Phase Advanced SQC Methods SQC Case Studies SQC Theory Part II Design of Experiments (DOE) and Regression DOE: The Jewel of Quality Engineering DOE: Screening Using Fractional Factorials DOE: Response Surface Methods DOE: Robust Design Regression Advanced Regression and Alternatives DOE and Regression Case Studies DOE and Regression Theory Part III Optimization and Strategy Optimization and Strategy Tolerance Design Six Sigma Project Design Glossary Problem Solutions Index