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Statistical Methods for Six Sigma: In R&D and Manufacturing [Anglais] [Relié]

Anand M. Joglekar

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Description de l'ouvrage

7 octobre 2003
A guide to achieving business successes through statistical methods Statistical methods are a key ingredient in providing data–based guidance to research and development as well as to manufacturing. Understanding the concepts and specific steps involved in each statistical method is critical for achieving consistent and on–target performance. Written by a recognized educator in the field, Statistical Methods for Six Sigma: In R&D and Manufacturing is specifically geared to engineers, scientists, technical managers, and other technical professionals in industry. Emphasizing practical learning, applications, and performance improvement, Dr. Joglekar’s text shows today’s industry professionals how to: Summarize and interpret data to make decisions Determine the amount of data to collect Compare product and process designs Build equations relating inputs and outputs Establish specifications and validate processes Reduce risk and cost–of–process control Quantify and reduce economic loss due to variability Estimate process capability and plan process improvements Identify key causes and their contributions to variability Analyze and improve measurement systems This long–awaited guide for students and professionals in research, development, quality, and manufacturing does not presume any prior knowledge of statistics. It covers a large number of useful statistical methods compactly, in a language and depth necessary to make successful applications. Statistical methods in this book include: variance components analysis, variance transmission analysis, risk–based control charts, capability and performance indices, quality planning, regression analysis, comparative experiments, descriptive statistics, sample size determination, confidence intervals, tolerance intervals, and measurement systems analysis. The book also contains a wealth of case studies and examples, and features a unique test to evaluate the reader’s understanding of the subject.

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Descriptions du produit

Revue de presse

"I highly recommend this book to anyone interested in applying statistics to solve problems." ( Journal of Food Quality , October 2004) "…an interesting collection of material in nice summary form…" ( Journal of the American Statistical Association , December 2004) "Overall, Statistical Methods for Six Sigma in R & D and Manufacturing offers some good insights and practical views of the statistical concepts covered." ( Technometrics , August 2004, Vol. 46, No. 3) "...covers a large number of useful statistical methods compactly...contains a wealth of case studies and examples..." ( Food Trade Review , May 2004) “...can be used as a reference or as a self–study...also as a textbook for an engineering statistics course...recommended...” ( E–Streams , Vol. 7, No. 3)

Quatrième de couverture

A guide to achieving business successes through statistical methods Statistical methods are a key ingredient in providing data–based guidance to research and development as well as to manufacturing. Understanding the concepts and specific steps involved in each statistical method is critical for achieving consistent and on–target performance. Written by a recognized educator in the field, Statistical Methods for Six Sigma: In R&D and Manufacturing is specifically geared to engineers, scientists, technical managers, and other technical professionals in industry. Emphasizing practical learning, applications, and performance improvement, Dr. Joglekar’s text shows today’s industry professionals how to: Summarize and interpret data to make decisions Determine the amount of data to collect Compare product and process designs Build equations relating inputs and outputs Establish specifications and validate processes Reduce risk and cost–of–process control Quantify and reduce economic loss due to variability Estimate process capability and plan process improvements Identify key causes and their contributions to variability Analyze and improve measurement systems This long–awaited guide for students and professionals in research, development, quality, and manufacturing does not presume any prior knowledge of statistics. It covers a large number of useful statistical methods compactly, in a language and depth necessary to make successful applications. Statistical methods in this book include: variance components analysis, variance transmission analysis, risk–based control charts, capability and performance indices, quality planning, regression analysis, comparative experiments, descriptive statistics, sample size determination, confidence intervals, tolerance intervals, and measurement systems analysis. The book also contains a wealth of case studies and examples, and features a unique test to evaluate the reader’s understanding of the subject.

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Première phrase
Much work in manufacturing and in research and development (R&D) is directed toward improving the performance of products, processes, and measurement systems. Lire la première page
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Couverture | Copyright | Table des matières | Extrait | Index | Quatrième de couverture
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5.0 étoiles sur 5 GREAT REFERENCE 9 janvier 2007
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Format:Relié
I WAS LOOKING FOR A BOOK TO USE AS A MFG/DESIGN ENG FOR QUICK REFERENCE TO COMMONLY USED METHODS, GAGE R&RS, POPULATION COMPARISONS, STATISTICAL SIGNIFICANTS, THIS BOOK DOES IT. VERY CONCISE AND WELL THOUGHT OUT.
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