Statistical Process Control for Real-World Applications

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
Exercises
Solutions
Endnotes

Nonnormal Distributions
Transformations
General Procedure for Nonnormal Distributions
The Gamma Distribution
The Weibull Distribution
The Lognormal Distribution
Measurements with Detection Limits (Censored Data)
Exercises
Solutions
Endnotes

Range Charts for Nonnormal Distributions
Traditional Range Charts
Range Charts with Exact Control Limits
Range Charts for Nonnormal Distributions
Exercises
Solutions
Endnote

Nested Normal Distributions
Variance Components: Two Levels of Nesting
Exercise
Solution

Process Performance Indices
Process Performance Index for Nonnormal Distributions
Confidence Limits for Normal Process Performance Indices
Confidence Limits for Nonnormal Process Performance Indices
Exercise
Solution
Endnotes

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
Exercises
Solutions

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
Endnotes

Glossary
Appendix A: Control Chart Factors
Appendix B: Simulation and Modeling
Appendix C: Numerical Methods
References

Biography

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

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