This undergraduate statistical quality assurance textbook clearly shows with real projects, cases and data sets how statistical quality control tools are used in practice. Among the topics covered is a practical evaluation of measurement effectiveness for both continuous and discrete data. Gauge Reproducibility and Repeatability methodology (including confidence intervals for Repeatability, Reproducibility and the Gauge Capability Ratio) is thoroughly developed. Process capability indices and corresponding confidence intervals are also explained. In addition to process monitoring techniques, experimental design and analysis for process improvement are carefully presented. Factorial and Fractional Factorial arrangements of treatments and Response Surface methods are covered. Integrated throughout the book are rich sets of examples and problems that help readers gain a better understanding of where and how to apply statistical quality control tools. These large and realistic problem sets in combination with the streamlined approach of the text and extensive supporting material facilitate reader understanding.Second Edition Improvements<ul>
<li>Extensive coverage of measurement quality evaluation (in addition to ANOVA Gauge R&amp;R methodologies) 
</li>
<li>New end-of-section exercises and revised-end-of-chapter exercises 
</li>
<li>Two full sets of slides, one with audio to assist student preparation outside-of-class and another appropriate for professors’ lectures 
</li>
<li>Substantial supporting material 
</li>
</ul>
 Supporting Material<ul>
<li>Seven R programs that support variables and attributes control chart construction and analyses, Gauge R&amp;R methods, analyses of Fractional Factorial studies, Propagation of Error analyses and Response Surface analyses</li>
<li>Documentation for the R programs</li>
<li>Excel data files associated with the end-of-chapter problem sets, most from real engineering settings</li>
</ul>

Statistical Methods for Quality Assurance: Basics, Measurement, Control, Capability, and Improvement (Springer Texts in Statistics)

Computers & Technology

Jobe, J. Marcus

Vardeman, Stephen B. B.

Computer Science

Springer

The Tools You Need To Be A Successful Engineer As you read through this new text, you'll discover the importance of Statistical Quality Control (SQC) tools in engineering process monitoring and improvement. You'll learn what SQC methods can and cannot do, and why these are valuable additions to your engineering tool kit. And instead of overwhelming you with unnecessary details, the authors make the implementation of statistical tools "user-friendly." The rich set of examples and problems integrated throughout this book will help you gain a better understanding of where and how to apply SQC tools. Real projects, cases and data sets show you clearly how SQC tools are used in practice. Topics are covered in the right amount of detail to give you insight into their relative importance in modern quality assurance and the ability to immediately use them. This approach provides the mix of tools you'll need to succeed in your engineering career. Key Features of the Text * Provides a coherent presentation of the role of statistics in quality assurance. * Places special attention on making sure that while the technical details are absolutely correct, they do not overwhelm the reader. * Presents the material in realistic contexts, with examples and problems that are based on real-world projects, cases and data sets. * The implementation of statistical tools is user-friendly. * The statistical treatment emphasizes graphics and estimation (and de-emphasizes hypothesis testing).

Statistical Quality Assurance Methods for Engineers

Business & Money

Vardeman, Stephen B.

Management & Leadership

John Wiley&Sons, Inc.

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