This book is an introductory book on improving the quality of a process or a system, primarily through the technique of statistical process control (SPC). There are numerous technical manuals available for SPC, but this book differs in two ways: (1) the basic tools of SPC are introduced in a no-nonsense, simple, non-math manner, and (2) the methods can be learned and practiced in an uncomplicated fashion using free software (eZ SPC 2.0), which is available to all readers online as a downloadable product. The book explains QC7 Tools, control charts, and statistical analysis including basic design of experiments. Theoretical explanations of the analytical methods are avoided; instead, results are interpreted through the use of the software.

This hands-on book provides a simplified systems for solving quality problems in design and manufacturing using statistics. It covers methods for problem identificaiton, root cause analysist, and corrective action implementation. It aims to provide engineers and managers with proactive tools to avoid costly errors in prodcut desing and manufacturing.

This book is based on the papers presented at the International Conference 'Quality Improvement through Statistical Methods' in Cochin, India during December 28-31, 1996. The Conference was hosted by the Cochin University of Science and Technology, Cochin, India; and sponsored by the Institute for Improvement in Quality and Productivity (IIQP) at the University of Waterloo, Canada, the Statistics in Industry Committee of the International Statistical Institute (lSI) and by the Indian Statistical Institute. There has been an increased interest in Quality Improvement (QI) activities in many organizations during the last several years since the airing of the NBC television program, "If Japan can ... why can't we?" Implementation of QI meth ods requires statistical thinking and the utilization of statistical tools, thus there has been a renewed interest in statistical methods applicable to industry and technology. This revitalized enthusiasm has created worldwide discussions on Industrial Statistics Research and QI ideas at several international conferences in recent years. The purpose of this conference was to provide a forum for presenting and ex changing ideas in Statistical Methods and for enhancing the transference of such technologies to quality improvement efforts in various sectors. It also provided an opportunity for interaction between industrial practitioners and academia. It was intended that the exchange of experiences and ideas would foster new international collaborations in research and other technology transfers.

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 Extensive coverage of measurement quality evaluation (in addition to ANOVA Gauge R&R methodologies) New end-of-section exercises and revised-end-of-chapter exercises Two full sets of slides, one with audio to assist student preparation outside-of-class and another appropriate for professors’ lectures Substantial supporting material Supporting Material Seven R programs that support variables and attributes control chart construction and analyses, Gauge R&R methods, analyses of Fractional Factorial studies, Propagation of Error analyses and Response Surface analyses Documentation for the R programs Excel data files associated with the end-of-chapter problem sets, most from real engineering settings

Special features of Statistical Methods for Quality Improvement, Second Edition include: greatly expanded chapters on process capability indices and multivariate control chart methods; improved attributes control charts based on the author's research; a detailed presentation of Six Sigma programs; a new, separate chapter on CUSUM and EWMA procedures; new material on robust design and Taguchi-type procedures; chapter appendices for more in-depth coverage of selected topics; and very extensive and up-to-date references in each chapter, in addition to a bibliography of papers on a variety of control chart applications."--Jacket.

The essence of any root cause analysis in our modern quality thinking is to go beyond the actual problem. This means not only do we have to fix the problem at hand but we also have to identify why the failure occurred and what was the opportunity to apply the appropriate knowledge to avoid the problem in the future. Essential Statistical Concepts for the Quality Professional offers a new non-technical statistical approach to quality for effective improvement and productivity by focusing on very specific and fundamental methodologies and tools for the future. Written by an expert with more than 30 years of experience in management, quality training, and consulting, the book examines the fundamentals of statistical understanding, and by doing so demonstrates the importance of using statistics in the decision making process. The author points out pitfalls to keep in mind when undertaking an experiment for improvement and explains how to use statistics in improvement endeavors. He discusses data interpretation, common tests and confidence intervals, and how to plan experiments for improvement. The book expands the notion of experimentation by dealing with mathematical models such as regression to optimize the improvement and understand the relationship between several factors. It emphasizes the need for sampling and introduces specific techniques to make sure accuracy and precision of the data is appropriate and applicable for the study at hand. The author’s approach is somewhat new and unique; however, he details tools and methodologies that can be used to evaluate the system for prevention. These tools and methodologies focus on structured, repeatable processes that can be instrumental in finding real, fixable causes of the human errors and equipment failures that lead to quality issues.

A Practical Guide to Statistical Quality Improvement: Opening Up the Statistical Toolbox is designed as a reference guide for the engineer, supervisor, and manager. The intent of the text is to present conventional statistical quality improvement tools in a user-friendly form. We have worked to take some of the "mystique" out of the statistics and help others put these powerful tools to effective use in a Total Quality Manage Management (TQM) environment. This isn't a text on TQM. TQM has three elements (as shown in Figure i.1): 1. Creating the environment 2. The continuous improvement toolbox 3. Employee empowerment This text focuses almost exclusively on the middle element, the continuous improvement (CI) toolbox. Further, Opening Up the Statistical Toolbox does not present a complete set of tools intended to "fill" the CI toolbox; only the statistical tools and some of the basic team process tools are covered. The CI toolbox, in reality, will never get "filled". A comprehensive toolbox will include extensive team process skills and technology specific tools complimentary to the statistical tools included here. THE THREE KEY ELEMENTS OF TQM THE CONTINUOUS IMPROVEMENT TOOLBOX EMPLOYEE EMPOWERMENT FIGURE i.I.

A reference to the tools that may be used in the context of general quality improvement. The tools and techniques described can be applied in all areas of business, including all management areas.

This book discusses statistical process control (SPC) concepts, emphasizing the need to establish stability of work processes. It gives the elements required to develop a defect prevention system (DPS), and integrates the application of process control and problem analysis tools.