Introduction to Statistical Process Control

Introduction to Statistical Process Control

Publisher: Chapman and Hall
ISBN: 9781439847992
Author: Peihua Qiu
Dispatch Time: Pre-Order
Format: Hard Cover
Number of Pages: 524
Year of Published: 2014
Our Price: £59.99

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, Introduction to Statistical Process Controldescribes 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.

After exploring the role of SPC and other statistical methods in quality control and management, the book covers basic statistical concepts and methods useful in SPC. It then systematically describes traditional SPC charts, including the Shewhart, CUSUM, and EWMA charts, as well as recent control charts based on change-point detection and fundamental multivariate SPC charts under the normality assumption. The text also introduces novel univariate and multivariate control charts for cases when the normality assumption is invalid and discusses control charts for profile monitoring

Table of Contents

Quality and the Early History of Quality Improvement 
Quality Management 
Statistical Process Control 
Organization of the Book


Basic Statistical Concepts and Methods 
Population and Population Distribution 
Important Continuous Distributions
Important Discrete Distributions 
Data and Data Description 
Tabular and Graphical Methods for Describing Data 
Parametric Statistical Inferences 
Nonparametric Statistical Inferences


Univariate Shewhart Charts and Process Capability 
Shewhart Charts for Numerical Variables 
Shewhart Charts for Categorical Variables 
Process Capability Analysis 
Some Discussions


Univariate CUSUM Charts 
Monitoring the Mean of a Normal Process 
Monitoring the Variance of a Normal Process 
CUSUM Charts for Distributions in Exponential Family 
Self-Starting and Adaptive CUSUM Charts 
Some Theory for Computing ARL Values 
Some Discussions


Univariate EWMA Charts 
Monitoring the Mean of a Normal Process 
Monitoring the Variance of a Normal Process
Self-Starting and Adaptive EWMA Charts 
Some Discussions


Univariate Control Charts by Change-Point Detection 
Univariate Change-Point Detection 
Control Charts by Change-Point Detection 
Some Discussions


Multivariate Statistical Process Control 
Multivariate Shewhart Charts 
Multivariate CUSUM Charts 
Multivariate EWMA Charts 
Multivariate Control Charts by Change-Point Detection 
Multivariate Control Charts by LASSO 
Some Discussions


Univariate Nonparametric Process Control 
Rank-Based Nonparametric Control Charts 
Nonparametric SPC by Categorical Data Analysis 
Some Discussions


Multivariate Nonparametric Process Control 
Rank-Based Multivariate Nonparametric Control Charts 
Multivariate Nonparametric SPC by Log-Linear Modeling
Some Discussions


Profile Monitoring 
Parametric Profile Monitoring 
Nonparametric Profile Monitoring 
Some Discussions


Appendix A: R Functions for SPC 
Appendix B: Datasets Used in the Book




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