- Paperback: 220 pages
- Publisher: Society for Industrial and Applied Mathematics (1 Jan 1987)
- Language English
- ISBN-10: 0898715881
- ISBN-13: 978-0898715880
- Product Dimensions: 24.9 x 17.5 x 1.3 cm
- Amazon Bestsellers Rank: 1,065,981 in Books (See Top 100 in Books)
- See Complete Table of Contents
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Review
'The authors have done an excellent job of providing practitioners with an up-to-date reference for constructing confidence intervals for a class of mixed models with application to gauge R&R studies.' José G. Ramírez, W.L. Gore & Associates, Inc.
'A pattern of presentation is established in early chapters and consistently used throughout the book. The notation is also unified throughout the book, which is a major contribution.' Greg Larsen, Agilent Technologies
'A pattern of presentation is established in early chapters and consistently used throughout the book. The notation is also unified throughout the book, which is a major contribution.' Greg Larsen, Agilent Technologies
Product Description
This book provides a protocol for conducting gauge repeatability and reproducibility (R&R) experiments. Such an experiment is required whenever a new test system is developed to monitor a manufacturing process. The protocol presented here is used to determine if the testing system is capable of monitoring the manufacturing process with the desired level of accuracy and precision. This protocol is not currently available in other books or technical reports. In addition to providing a protocol for testing a measurement system, the book presents an up-to-date summary of methods used to construct confidence intervals in normal-based random and mixed analysis of variance (ANOVA) models. Thus, this comprehensive book will be useful to scientists in all fields of application who wish to construct interval estimates for ANOVA model parameters. It includes approaches that can be applied to any ANOVA model.
Inside This Book
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First Sentence
To properly monitor and improve a manufacturing process, it is necessary to measure attributes of the process output. Read the first page
Front Cover | Copyright | Table of Contents | Excerpt | Index | Back Cover
To properly monitor and improve a manufacturing process, it is necessary to measure attributes of the process output. Read the first page
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Front Cover | Copyright | Table of Contents | Excerpt | Index | Back Cover
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0 of 1 people found the following review helpful
Excellent reading for people interested in quantifying uncertainty in measurement
30 Jan 2007
Format:Paperback
The book is excellent reading for people interested in quantifying uncertainty in measurement. However it is important to understand that the publication deals with quantifying uncertainty in measurement due to the measurement system and NOT the device under test it self. This means that one should compare notes with the ISO publication regarding uncertainty in measurement (eg Type A and Type B). In doing so one should be able to understand all within the field of uncertainty in measurement (given prior adequate basic statistical training).
In summary, the book is of up most importance.
In summary, the book is of up most importance.
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