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.

Performance improvement thought leader Dean Spitzer explains why performance measurement should be less about calculations and analysis and more about the crucial social factors that determine how well the measurements get used. Transforming Performance Measurement presents a breakthrough approach that will not only significantly reduce those dysfunctions, but also promote alignment with business strategy, maximize cross-enterprise integration, and help everyone to work collaboratively to drive value throughout your organization. Spitzer’s "socialization of measurement" process focuses on learning and improvement from measurement, and on the importance of asking such questions as: How well do our measures reflect our business model? How successfully are they driving our strategy? What should we be measuring and not measuring? Are the right people having the right measurement discussions? Performance measurement is a dynamic process that calls for an awareness of the balance necessary between seemingly disparate ideas: the technical and the social aspects of performance measurement. This book gives you assessment tools to gauge where you are now and a roadmap for moving, with little or no disruption, to a more "transformational" and mature measurement system. The book also provides 34 TMAPs, Transformational Measurement Action Plans, which suggest both well-accepted and "emergent" measures (in areas such as marketing, human resources, customer service, knowledge management, productivity, information technology, research and development, costing, and more) that you can use right away. Transforming Performance Measurement tells you not only what to measure, but how to do it -- and in what context -- to make a truly transformational difference in your enterprise.

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

INCREASE your odds of learning STATISTICAL process control (SPC) Identify and reduce variation in business processes using SPC--the powerful analysis tool for process evaluation and improvement. Statistical Process Control Demystified shows you how to use SPC to enable data-driven decision making and gain a competitive advantage in the marketplace. Written in a step-by-step format, this practical guide explains how to analyze process data, collect data, and determine the suitability of a process in meeting requirements. Attribute and X-bar control charts are discussed, as are charts for individuals data. You'll also get details on process improvement and measurement systems analysis. Detailed examples, calculations, and statistical assumptions make it easy to understand the material, and end-of-chapter quizzes and a final exam help reinforce key concepts. It's a no-brainer! You'll learn about: Control chart interpretation Overcoming common errors in the use of SPC and general statistical analysis tools Sampling requirements Analysis using Excel Estimating process variation Designed experiments Measurement systems analysis, including R&R studies Continuous process improvement strategies Simple enough for a beginner, but challening enough for an advanced student, Statistical Process Control Demystified is your shortcut to this powerful analysis solution.

In production, measurement process capability studies are required. This requirement is obligatory according to several international standards, guidelines and company guidelines of the automotive industry. Due to this requirement, the risk of product liability is to become appreciable and controllable. While the automotive industry implemented gage capability studies during the last years, today, the determination of the extended measurement uncertainty serves as an alternative to capability studies or to the applicability of measurement processes. This book gives a comprehensive overview and assists you in dealing with these requirements in industrial production. Several guidelines contained in this book (Bosch, DaimlerChrysler, General Motors Powertrain) apply the procedures described here. The acquired experience confirms the great benefit of these procedures in practice. The following standards are considered " DIN EN ISO 9001:2000 and ISO/TS 16949 " QS-9000, MSA Third Edition " VDA 6.1, VDA 5 "Measurement Process Capability" " DGQ 13-61 "Gage Management" " GUM / DIN EN V 13005 " DIN EN ISO 14253 " DIN EN ISO 10012:2003 " VDI/VDE/DGQ 2618

This book gathers the most recent developments in fuzzy & intelligence systems and real complex systems presented at INFUS 2020, held in Istanbul on July 21–23, 2020. The INFUS conferences are a well-established international research forum to advance the foundations and applications of intelligent and fuzzy systems, computational intelligence, and soft computing, highlighting studies on fuzzy & intelligence systems and real complex systems at universities and international research institutions. Covering a range of topics, including the theory and applications of fuzzy set extensions such as intuitionistic fuzzy sets, hesitant fuzzy sets, spherical fuzzy sets, and fuzzy decision-making; machine learning; risk assessment; heuristics; and clustering, the book is a valuable resource for academics, M.Sc. and Ph.D. students, as well as managers and engineers in industry and the service sectors.