An Introduction to Acceptance Sampling and SPC with R (Hardback)John Lawson (author)
An Introduction to Acceptance Sampling and SPC with R is an introduction to statistical methods used in monitoring, controlling and improving quality. Topics covered include acceptance sampling; Shewhart control charts for Phase I studies; graphical and statistical tools for discovering and eliminating the cause of out-of-control-conditions; Cusum and EWMA control charts for Phase II process monitoring; and the design and analysis of experiments for process troubleshooting and discovering ways to improve process output. Origins of statistical quality control and the technical topics presented in the remainder of the book are those recommended in the ANSI/ASQ/ISO guidelines and standards for industry. The final chapter ties everything together by discussing modern management philosophies that encourage the use of the technical methods presented earlier.
In the modern world sampling plans and the statistical calculations used in statistical quality control are done with the help of computers. As an open source high-level programming language with flexible graphical output options, R runs on Windows, Mac and Linux operating systems, and has add-on packages that equal or exceed the capability of commercial software for statistical methods used in quality control. In this book, we will focus on several R packages. In addition to demonstrating how to use R for acceptance sampling and control charts, this book will concentrate on how the use of these specific tools can lead to quality improvements both within a company and within their supplier companies.
This would be a suitable book for a one-semester undergraduate course emphasizing statistical quality control for engineering majors (such as manufacturing engineering or industrial engineering), or a supplemental text for a graduate engineering course that included quality control topics.
Publisher: Taylor & Francis Ltd
Number of pages: 298
Weight: 566 g
Dimensions: 234 x 156 mm
"In conclusion, among the few books that illustrate R for SQC, this book best uses the broadest range of state-of-the-art R packages. This breadth and up-to-date nature alone would make this book the top choice for those who want to use R for SQC. Technical discussions in the book are well-grounded in both statistical theories and in-depth knowledge of SQC practice. This book is an excellent addition to any quality engineer's library."
Youngjun Choe, University of Washington, Journal of the American Statistical Association, Vol. 117 Issue 537, 24th March 2022.
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