by Paul G. Mathews
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Editorial Reviews
Product Description
The motivation for this book comes from the author’s extensive experience with trying to apply the standard measurement systems analysis methods to real-world problems that arise in manufacturing and industry. The methods work well for simple systems that are not dynamic and have only two significant sources of error, but leave a lot to be desired in other circumstances. This shortfall is especially clear in the case of attribute measurement systems analysis in which the standard method is far from adequate. This book provides clear procedures for situations in which the part values change or are destroyed. It also provides procedures that work when the measurements are dynamic and cannot be separated from the process. It extends the simple methods to cases in which the measurement systems have several sources of uncertainty. And it completely overhauls the attribute methodology and enables it for many difficult but practical applications. Each extension of the method is detailed in a chapter complete with realistic examples and end-of-chapter summaries called “Take Home Pay” which clue the reader into the key points that are critical for the attempt to enable bottom line success. The reader who uses these methods will find that they can quickly make significant improvement in their destructive, dynamic, and attribute measurement systems with less effort. Contents: Chapter 1: The Need for Measurement Systems Analysis Chapter 2: Review of the Standard Variables Measurement Systems Analysis Chapter 3: The Variability in the Estimate of Repeatability and Reproducibility Chapter 4: Extending the Standard MSA to Sources of Uncertainty Chapter 5: Deformative Measurements Chapter 6: Destructive Measurement Systems Chapter 7: In-line and Dynamic Measurement Systems Chapter 8: The Design of Measurement System Analyses Chapter 9: The Basic Approach to Attribute Measurement Analysis Chapter 10: A More Powerful Approach to Attribute Analysis Chapter 11: Extending The Attribute MSA Chapter 12: The Evaluation of Measurement System Value Chapter 13: The Reliability of Measurement Systems Chapter 14: A Review of Progress With An Eye to the Future
About the Author
William D. Mawby has been with Michelin Tire Corporation for 18 years and currently serves as manager for statistical and mathematical support for Michelin North America. Prior to this position, Mawby filled the role of chief statistician for Michelin Tire Corporation Research and Development Corporation in South Carolina. While there, he trained and consulted in SPC, DOE, reliability, multivariate methods, and other disciplines. Mawby holds a B.S. in natural systems from the Defiance College in Ohio and a Ph.D. in biomathematics from North Carolina State University.
The motivation for this book comes from the author’s extensive experience with trying to apply the standard measurement systems analysis methods to real-world problems that arise in manufacturing and industry. The methods work well for simple systems that are not dynamic and have only two significant sources of error, but leave a lot to be desired in other circumstances. This shortfall is especially clear in the case of attribute measurement systems analysis in which the standard method is far from adequate. This book provides clear procedures for situations in which the part values change or are destroyed. It also provides procedures that work when the measurements are dynamic and cannot be separated from the process. It extends the simple methods to cases in which the measurement systems have several sources of uncertainty. And it completely overhauls the attribute methodology and enables it for many difficult but practical applications. Each extension of the method is detailed in a chapter complete with realistic examples and end-of-chapter summaries called “Take Home Pay” which clue the reader into the key points that are critical for the attempt to enable bottom line success. The reader who uses these methods will find that they can quickly make significant improvement in their destructive, dynamic, and attribute measurement systems with less effort. Contents: Chapter 1: The Need for Measurement Systems Analysis Chapter 2: Review of the Standard Variables Measurement Systems Analysis Chapter 3: The Variability in the Estimate of Repeatability and Reproducibility Chapter 4: Extending the Standard MSA to Sources of Uncertainty Chapter 5: Deformative Measurements Chapter 6: Destructive Measurement Systems Chapter 7: In-line and Dynamic Measurement Systems Chapter 8: The Design of Measurement System Analyses Chapter 9: The Basic Approach to Attribute Measurement Analysis Chapter 10: A More Powerful Approach to Attribute Analysis Chapter 11: Extending The Attribute MSA Chapter 12: The Evaluation of Measurement System Value Chapter 13: The Reliability of Measurement Systems Chapter 14: A Review of Progress With An Eye to the Future
About the Author
William D. Mawby has been with Michelin Tire Corporation for 18 years and currently serves as manager for statistical and mathematical support for Michelin North America. Prior to this position, Mawby filled the role of chief statistician for Michelin Tire Corporation Research and Development Corporation in South Carolina. While there, he trained and consulted in SPC, DOE, reliability, multivariate methods, and other disciplines. Mawby holds a B.S. in natural systems from the Defiance College in Ohio and a Ph.D. in biomathematics from North Carolina State University.
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Inside This Book
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Key Phrases - Statistically Improbable Phrases (SIPs):
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part estimate variation, true part value, destructive measurement systems, true product value, appraiser analysis, attribute measurement systems, repeatability effect, attribute gage, reproducibility estimates, measurement system error, many measurement systems, repeatability estimate, repeatability variation, two appraisers, three appraisers, measurement systems analysis, randomized pattern, weighted study, fitted probabilities, digital micrometer, complete randomization, attribute study, dowel rod, factorial approach Key Phrases - Capitalized Phrases (CAPs): (learn more)
No-go No-go, Error Source Variance Estimate Standard Deviation, Take-Home Pay, Extending the Attribute, Extending the Standard, Obs Reps Appraiser Parts Noncons Predict, More Powerful Approach, The Basic Approach, Days Type Cens, The Evaluation of Measurement System Value, Obs Part App Rep Meas, Obs Reps Order Noncons Predict, Obs Seq Part App Setup Meas, Obs Seq Part App Temp Meas, Review of Progress, Weibull Scale, Weibull Shape, Days Type Obs, Maximum Loglikelihood, Mean Std Dev Minimum Maximum, Probability Estimated Value, Right Censored Values, Summary of Fit Observations Used, Uncensored Values, Weibull Parameter Estimates Asymptotic Normal New!
Concordance | Text Stats Browse Sample Pages:
Front Cover | Table of Contents | First Pages | Index | Back Cover | Surprise Me!
part estimate variation, true part value, destructive measurement systems, true product value, appraiser analysis, attribute measurement systems, repeatability effect, attribute gage, reproducibility estimates, measurement system error, many measurement systems, repeatability estimate, repeatability variation, two appraisers, three appraisers, measurement systems analysis, randomized pattern, weighted study, fitted probabilities, digital micrometer, complete randomization, attribute study, dowel rod, factorial approach Key Phrases - Capitalized Phrases (CAPs): (learn more)
No-go No-go, Error Source Variance Estimate Standard Deviation, Take-Home Pay, Extending the Attribute, Extending the Standard, Obs Reps Appraiser Parts Noncons Predict, More Powerful Approach, The Basic Approach, Days Type Cens, The Evaluation of Measurement System Value, Obs Part App Rep Meas, Obs Reps Order Noncons Predict, Obs Seq Part App Setup Meas, Obs Seq Part App Temp Meas, Review of Progress, Weibull Scale, Weibull Shape, Days Type Obs, Maximum Loglikelihood, Mean Std Dev Minimum Maximum, Probability Estimated Value, Right Censored Values, Summary of Fit Observations Used, Uncensored Values, Weibull Parameter Estimates Asymptotic Normal New!
Concordance | Text Stats Browse Sample Pages:
Front Cover | Table of Contents | First Pages | Index | Back Cover | Surprise Me!
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