Introduction to Engineering Statistics and Six Sigma: Statistical Quality Control and Design of Experiments and Systems - Hardcover

Allen, Theodore T.

 
9781852339555: Introduction to Engineering Statistics and Six Sigma: Statistical Quality Control and Design of Experiments and Systems

Inhaltsangabe

It is said that six sigma methods are vital to survive, let alone thrive, in today’s competitive markets, but what are these methods and how or when do we use them?

This book describes related methods and details case studies showing how they've been applied in engineering and business to save millions of dollars. These methods include: 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. The aim is to help the reader determine which methods to use in which scenario and to predict the effectiveness of these methods.

Illustrative examples support all methods presented and case-study based exercises help the reader associate techniques with industrial problems. A glossary of acronyms is provided in addition to solutions to homework and practice exams.

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Über die Autorin bzw. den Autor

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).

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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.

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