Statistical Process Control for Real-World Applications: 1st Edition (Hardback) book cover

Statistical Process Control for Real-World Applications

1st Edition

By William A. Levinson

CRC Press

272 pages | 136 B/W Illus.

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pub: 2010-12-21
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The normal or bell curve distribution is far more common in statistics textbooks than it is in real factories, where processes follow non-normal and often highly skewed distributions. Statistical Process Control for Real-World Applications shows how to handle non-normal applications scientifically and explain the methodology to suppliers and customers.

The book exposes the pitfalls of assuming normality for all processes, describes how to test the normality assumption, and illustrates when non-normal distributions are likely to apply. It demonstrates how to handle uncooperative real-world processes that do not follow textbook assumptions. The text explains how to set realistic control limits and calculate meaningful process capability indices for non-normal applications. The book also addresses multivariate systems, nested variation sources, and process performance indices for non-normal distributions.

The book includes examples from Minitab®, StatGraphics® Centurion, and MathCAD and covers how to use spreadsheets to give workers a visual signal when an out of control condition is present. The included user disk provides Visual Basic for Applications functions to make tasks such as distribution fitting and tests for goodness of fit as routine as possible. The book shows you how to set up meaningful control charts and report process performance indices that actually reflect the process' ability to deliver quality.


With this book, the author provides a useful contribution to the literature for dealing with methods for describing the quality of a nonnormal process through the use of appropriate control charts and/or process performance indices. … I found this book interesting and valuable in discussing topics related to SPC that are not found in traditional textbooks on the subject. In order to get the same level of information as provided in this book, one would have to search for numerous journal articles for details and applications.

—Connie M. Borror, The American Statistician, November 2011

… a useful addition to the library of any industrial statistician, process engineer, or quality engineer engaged in improving processes. It represents material that is not typically covered in conventional books on statistical process control. In particular, with its focus on nonnormal distributions, this text provides a measure of reality that many quality and manufacturing professionals have known for years—that not all process distributions follow the normal distribution. In that respect, this book is a refreshing addition to the literature and I highly recommend it.

—Dean Neubauer, Journal of Quality Technology, Vol. 43, No. 4, October 2011

Table of Contents

Traditional Control Charts

Variation and Accuracy

Statistical Hypothesis Testing

Control Chart Concepts

Setup and Deployment of Control Charts

Interpretation of x‑bar/R and x‑bar/s Charts

X (Individual Measurement) Charts

Average Run Length (ARL)

z Chart for Sample Standard Normal Deviates

Acceptance Control Chart

Western Electric Zone Tests

Process Capability and Process Performance

Goodness-of-Fit Tests

Multiple Attribute Control Charts




Nonnormal Distributions


General Procedure for Nonnormal Distributions

The Gamma Distribution

The Weibull Distribution

The Lognormal Distribution

Measurements with Detection Limits (Censored Data)




Range Charts for Nonnormal Distributions

Traditional Range Charts

Range Charts with Exact Control Limits

Range Charts for Nonnormal Distributions




Nested Normal Distributions

Variance Components: Two Levels of Nesting



Process Performance Indices

Process Performance Index for Nonnormal Distributions

Confidence Limits for Normal Process Performance Indices

Confidence Limits for Nonnormal Process Performance Indices




The Effect of Gage Capability

Gage Accuracy and Variation

Gage Capability and Statistical Process Control

Gage Capability and Process Capability

Gage Capability and Outgoing Quality



Multivariate Systems

Multivariate Normal Distribution

Multivariate Control Chart

Deployment to a Spreadsheet: Principal Component Method

Multivariate Process Performance Index

Control Charts for the Covariance Matrix



Appendix A: Control Chart Factors

Appendix B: Simulation and Modeling

Appendix C: Numerical Methods


About the Author

William A. Levinson is the owner of Levinson Productivity Systems in Wilkes-Barre, Pennsylvania.

Subject Categories

BISAC Subject Codes/Headings:
BUSINESS & ECONOMICS / Quality Control