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Process Capability Analysis: Estimating Quality presents a
systematic exploration of process capability analysis and how it
may be used to estimate quality. The book is designed for
practitioners who are tasked with insuring a high level of quality
for the products and services offered by their organizations. Along
with describing the necessary statistical theory, the book
illustrates the practical application of the techniques to data
that do not always satisfy the standard assumptions. The first two
chapters deal with attribute data, where the estimation of quality
is restricted to counts of nonconformities. Both classical and
Bayesian methods are discussed. The rest of the book deals with
variable data, including extensive discussions of both capability
indices and statistical tolerance limits. Considerable emphasis is
placed on methods for handling non-normal data. Also included are
discussions of topics often omitted in discussions of process
capability, including multivariate capability indices, multivariate
tolerance limits, and capability control charts. A separate chapter
deals with the problem of determining adequate sample sizes for
estimating process capability. Features: Comprehensive treatment of
the subject with consistent theme of estimating percent of
nonconforming product or service. Includes Bayesian methods.
Extension of univariate techniques to multivariate data.
Demonstration of all techniques using Statgraphics data analysis
software. Neil Polhemus is Chief Technology Officer at Statgraphics
Technology and the original developer of the Statgraphics program
for statistical analysis and data visualization. Dr. Polhemus spent
6 years on the faculty of the School of Engineering and Applied
Science at Princeton University before moving full-time to software
development and consulting. He has taught courses dealing with
statistical process control, design of experiments and data
analysis for more than 100 companies and government agencies.
Process Capability Analysis: Estimating Quality presents a
systematic exploration of process capability analysis and how it
may be used to estimate quality. The book is designed for
practitioners who are tasked with insuring a high level of quality
for the products and services offered by their organizations. Along
with describing the necessary statistical theory, the book
illustrates the practical application of the techniques to data
that do not always satisfy the standard assumptions. The first two
chapters deal with attribute data, where the estimation of quality
is restricted to counts of nonconformities. Both classical and
Bayesian methods are discussed. The rest of the book deals with
variable data, including extensive discussions of both capability
indices and statistical tolerance limits. Considerable emphasis is
placed on methods for handling non-normal data. Also included are
discussions of topics often omitted in discussions of process
capability, including multivariate capability indices, multivariate
tolerance limits, and capability control charts. A separate chapter
deals with the problem of determining adequate sample sizes for
estimating process capability. Features: Comprehensive treatment of
the subject with consistent theme of estimating percent of
nonconforming product or service. Includes Bayesian methods.
Extension of univariate techniques to multivariate data.
Demonstration of all techniques using Statgraphics data analysis
software. Neil Polhemus is Chief Technology Officer at Statgraphics
Technology and the original developer of the Statgraphics program
for statistical analysis and data visualization. Dr. Polhemus spent
6 years on the faculty of the School of Engineering and Applied
Science at Princeton University before moving full-time to software
development and consulting. He has taught courses dealing with
statistical process control, design of experiments and data
analysis for more than 100 companies and government agencies.
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