Creating a universal language for problem solving, The Practical Application of the Process Capability Study: Evolving from Product Control to Process Control delineates the process capability study, a powerful tool that, when understood and implemented, provides benefits to every department within a manufacturing organization. With easy to read, step-by-step flow diagrams on how to perform process capability studies and measurement process analyses, the book’s coverage includes: The benefits of statistical process control over statistical product control Real-world industrial examples and case studies illustrating how to use the techniques Ways for management to determine if the investment in process capability studies is providing an appropriate return Methods to correct lack of stability and capability once either condition has been identified, such as the ANOVA technique and the simple three-factor designed experiment A flow chart that enables machine operators to execute a process capability study without interfering with productivity A great deal of information is available on the technical concepts of the process capability study, much of it emphasizing the mathematics. Unfortunately, concentrating on the math and fine distinctions, such as the difference between alpha- and beta-type errors, has created barriers preventing many from fully appreciating the basic concepts, the simplicity, and the usefulness of the tool. This book shows you how to use the process capability study to increase return on investment from your statistical process control/Six Sigma effort and make your company more competitive.

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.

Providing a single-valued assessment of the performance of a process is often one of the greatest challenges for a quality professional. Process Capability Indices (PCIs) precisely do this job. For processes having a single measurable quality characteristic, there is an ample number of PCIs, defined in literature. The situation worsens for multivariate processes, i.e., where there is more than one correlated quality characteristic. Since in most situations quality professionals face multiple quality characteristics to be controlled through a process, Multivariate Process Capability Indices (MPCIs) become the order of the day. However, there is no book which addresses and explains different MPCIs and their properties. The literature of Multivariate Process Capability Indices (MPCIs) is not well organized, in the sense that a thorough and systematic discussion on the various MPCIs is hardly available in the literature. Handbook of Multivariate Process Capability Indices provides an extensive study of the MPCIs defined for various types of specification regions. This book is intended to help quality professionals to understand which MPCI should be used and in what situation. For researchers in this field, the book provides a thorough discussion about each of the MPCIs developed to date, along with their statistical and analytical properties. Also, real life examples are provided for almost all the MPCIs discussed in the book. This helps both the researchers and the quality professionals alike to have a better understanding of the MPCIs, which otherwise become difficult to understand, since there is more than one quality characteristic to be controlled at a time. Features: A complete guide for quality professionals on the usage of different MPCIs. A step by step discussion on multivariate process capability analysis, starting from a brief discussion on univariate indices. A single source for all kinds of MPCIs developed so far. Comprehensive analysis of the MPCIs, including analysis of real-life data. References provided at the end of each chapter encompass the entire literature available on the respective topic. Interpretation of the MPCIs and development of threshold values of many MPCIs are also included. This reference book is aimed at the post graduate students in Industrial Statistics. It will also serve researchers working in the field of Industrial Statistics, as well as practitioners requiring thorough guidance regarding selection of an appropriate MPCI suitable for the problem at hand.

This unique volume provides an up-to-date and detailed description of the various process capability indices widely (and sometimes misleadingly) used in the applications at production sites. The authors, who are internationally recognized experts in this area with numerous contributions to the field, provide a lucid exposition, which covers all the main aspects, developments and advances.The concept of Process Capability Index (PCI) is barely 20 years old, but the multitude of available versions can overwhelm even the most seasoned practitioner. The organized and self-contained presentation of the material starting from 1980's primitive indices (Cp and Cpk) up to the newly proposed indices for the cases of multiple dependent characteristics results in an authoritative and indispensable reference.A proper balance between theoretical investigation and “rule-of-thumb” practical procedures is maintained in order to eliminate the tensions among various methodologies of assessing the capability of industrial processes.

A solid, rigorous, yet comprehensible analysis of process capability indices, this work bridges the gap between theoretical statisticians and quality control practitioners, showing how an understanding of these indices can lead to process improvement.

This work presents significant advances and new methods both in statistical process control and experimental design. It addresses the management of process monitoring and experimental design, discusses the relationship between control charting and hypothesis testing, provides a new index for process capability studies, offers practical guidelines for the design of experiments, and more.