Statistical Process Control for Real-World Applications

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

• Introduction. What to Expect From This book. Chapter Overview. Traditional Control Charts. Statistical Hypothesis Testing. Control Chart Concepts. Theoretical and Empirical Control Charts. Nonnormal Distributions. Data Fitting and Verification. Control Chart Construction: Center Line, Control Limits, and Zone Tests. Process Capability Indices. Nested Normal Distributions. Calculation of the variance components. Tests for Goodness of Fit. Control Chart. Process capability indices. Confidence Intervals for Process Capability Indices. Confidence Intervals for Cp. Confidence Intervals for CPL and CPU. The Noncentral t Distribution. Confidence Intervals for Cpk. The Bivariate Noncentral t Distribution. Exact Confidence Intervals for the Gamma Distribution Cpk. Multivariate Normal Systems. T' Chart. Calculation of Nonconforming Fraction, and a Capability Index.

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