Introduction to Statistical Process Control
1st Edition
Published on 14. October 2013
520 pages
978-1-040-05576-2 (ISBN)
Description
A major tool for quality control and management, statistical process control (SPC) monitors sequential processes, such as production lines and Internet traffic, to ensure that they work stably and satisfactorily. Along with covering traditional methods, this book describes many recent SPC methods that improve upon the more established techniques. The author-a leading researcher on SPC-shows how these methods can handle new applications. Pseudo codes are presented for important methods and all R functions and datasets are available on the author's website.
Reviews / Votes
"The material in all chapters is presented in a concise manner, without proofs, but with many relevant references. I find the last four chapters of the book valuable and worth having. Graduate students in statistics departments and experienced researchers would benefit from the quick exposure to the ideas and methodologies and in particular from the extensive bibliography. ... the book contains material not presented in other books along with many relevant references. It would be a useful addition to the libraries of graduate students and researchers."-Shelemyahu Zacks, The American Statistician, November 2014
"Bringing new statistical methods for quality control in line with the computer age, Introduction to Statistical Process Control presents state-of-the-art statistical process control (SPC) techniques for industrial and service processes. This book reflects major progress in the use of SPC for product and process improvement, introduces some of the newest discoveries-and sheds further light on existing ones-on the SPC approaches that can be applied across various areas of research, including engineering, medicine, and service.
It is accessible to SPC researchers as well as quality control engineers with varying levels of statistical expertise, with plenty of data examples that make reading and learning enjoyable. As it demonstrates how to apply the SPC methods to a broad range of processes and models encountered in practice, the book also serves as a valuable reference for professionals in the systems engineering, medical, and management science fields, as well as those in computer and information sciences who would like to learn more about quality control or sequential process monitoring. It is generally my first recommendation when asked for a valuable resource in the field due to the breadth of topics covered and its practical utility. In addition, I think the book would be an excellent choice as the primary textbook in an SPC course."
-Dr. Changliang Zou, Department of Statistics, Nankai University, China
More details
Series
Edition
1. Auflage
Language
English
Place of publication
London
United Kingdom
Publishing group
Taylor & Francis Ltd
Target group
College/higher education
ISBN-13
978-1-040-05576-2 (9781040055762)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions
Peihua Qiu
Introduction to Statistical Process Control
Book
10/2013
1st Edition
Chapman & Hall/CRC
€172.90
Shipment within 15-20 days
Person
Peihua Qiu, Ph.D., is the founding chair of the Department of Biostatistics at the University of Florida. He was previously a professor in the School of Statistics at the University of Minnesota. He is the editor of Technometrics, an elected fellow of the American Statistical Association and the Institute of Mathematical Statistics, and an elected member of the International Statistical Institute. His research focuses on jump regression analysis, medical image analysis, statistical methods for monitoring processes, and patient survival data analysis.
Content
Introduction. Basic Statistical Concepts and Methods. Univariate Shewhart Charts and Process Capability. Univariate CUSUM Charts. Univariate EWMA Charts. Univariate Control Charts by Change-Point Detection. Multivariate Statistical Process Control. Univariate Nonparametric Process Control. Multivariate Nonparametric Process Control. Profile Monitoring. Appendices. Bibliography. Index.
