Based on Dr. W. Edwards Deming's philosophy for the improvement of quality, productivity, and competitive position, this book is perfect for production, management science, statistics, and industrial engineering professionals. The book features enumerative and analytical statistical studies, showing the difference between fixed populations and processes; methods for improving a stable process with a known capability; techniques for analyzing and interpreting control chart patterns; and modern inspection policies, specifically Deming's kp rules, instead of traditional sampling plans. It also includes quality improvement stories, examples, and mini-case studies that convert complex topics into easy-to-understand material.
The book describes the most important quality management tools (e.g. QFD, Kano model), methods (e.g. FMEA, Six Sig-ma) and standards (e.g. IS0 9001, ISO 14001, ISO 27001, ISO 45001, SA8000). It reflects recent developments in the field. It is considered a must-read for students, academics, and practitioners.
Quality of care is a priority for U.S. Agency for International Development (USAID). The agency's missions abroad and their host country partners work in quality improvement, but a lack of evidence about the best ways to facilitate such improvements has constrained their informed selection of interventions. Six different methods - accreditation, COPE, improvement collaborative, standards-based management and recognitions (SBM-R), supervision, and clinical in-service training - currently make up the majority of this investment for USAID missions. As their already substantial investment in quality grows, there is demand for more scientific evidence on how to reliably improve quality of care in poor countries. USAID missions, and many other organizations spending on quality improvement, would welcome more information about how different strategies work to improve quality, when and where certain tools are most effective, and the best ways to measure success and shortcomings. To gain a better understanding of the evidence supporting different quality improvement tools and clarity on how they would help advance the global quality improvement agenda, the Institute of Medicine convened a 2-day workshop in January 2015. The workshop's goal was to illuminate these different methods, discussing their pros and cons. This workshop summary is a description of the presentations and discussions.
This new edition of this bestselling guide offers an integrated approach to process improvement that delivers quick and substantial results in quality and productivity in diverse settings. The authors explore their Model for Improvement that worked with international improvement efforts at multinational companies as well as in different industries such as healthcare and public agencies. This edition includes new information that shows how to accelerate improvement by spreading changes across multiple sites. The book presents a practical tool kit of ideas, examples, and applications.
Praise for the Second Edition "As a comprehensive statistics reference book for quality improvement, it certainly is one of the best books available." —Technometrics This new edition continues to provide the most current, proven statistical methods for quality control and quality improvement The use of quantitative methods offers numerous benefits in the fields of industry and business, both through identifying existing trouble spots and alerting management and technical personnel to potential problems. Statistical Methods for Quality Improvement, Third Edition guides readers through a broad range of tools and techniques that make it possible to quickly identify and resolve both current and potential trouble spots within almost any manufacturing or nonmanufacturing process. The book provides detailed coverage of the application of control charts, while also exploring critical topics such as regression, design of experiments, and Taguchi methods. In this new edition, the author continues to explain how to combine the many statistical methods explored in the book in order to optimize quality control and improvement. The book has been thoroughly revised and updated to reflect the latest research and practices in statistical methods and quality control, and new features include: Updated coverage of control charts, with newly added tools The latest research on the monitoring of linear profiles and other types of profiles Sections on generalized likelihood ratio charts and the effects of parameter estimation on the properties of CUSUM and EWMA procedures New discussions on design of experiments that include conditional effects and fraction of design space plots New material on Lean Six Sigma and Six Sigma programs and training Incorporating the latest software applications, the author has added coverage on how to use Minitab software to obtain probability limits for attribute charts. new exercises have been added throughout the book, allowing readers to put the latest statistical methods into practice. Updated references are also provided, shedding light on the current literature and providing resources for further study of the topic. Statistical Methods for Quality Improvement, Third Edition is an excellent book for courses on quality control and design of experiments at the upper-undergraduate and graduate levels. the book also serves as a valuable reference for practicing statisticians, engineers, and physical scientists interested in statistical quality improvement.
SPC METHODS FOR QUALITY IMPROVEMENT A comprehensive, applications-oriented guide to classical and cutting-edge SPC tools and techniques Written by a leading innovator in the field, SPC Methods for Quality Improvement provides a complete blueprint for integrating SPC methods into the manufacturing process. It explains methods for improving existing SPC systems and describes cutting-edge techniques that enable managers to develop full-fledged SPC systems in industries that traditionally were considered off-limits to this type of statistical analysis. The only guide to SPC geared exclusively to the practical concerns of manufacturing professionals, it translates statistical/mathematical concepts into real-world applications with the help of dozens of case studies and examples drawn from a variety of industries. SPC Methods for Quality Improvement is also a superb introductory text for students and newcomers to SPC. The author patiently introduces readers to essential SPC concepts and procedures and provides methodical, step-by-step instruction in the proper use of SPC tools and techniques. In the 1920s and 30s, Walter Shewhart of Bell Telephone Laboratories developed Statistical Process Control (SPC) as a means of analyzing manufacturing processes at the shop-floor level. Shewhart and his disciples—most notably W. Edwards Deming, father of total quality management—realized that SPC provided a sophisticated tool for assessing and improving quality at all levels. SPC, therefore, was the backbone of the quality management revolution of the 1980s and 90s. Yet, until now, there was no comprehensive, practical guide to SPC methods for engineers and managers working in manufacturing. SPC Methods for Quality Improvement fills that vacuum with complete coverage of SPC concepts, tools, and techniques geared to the practical concerns of manufacturing professionals. Dr. Charles Quesenberry introduces all statistical/mathematical essentials and carefully explains the rationale behind each concept. He employs vivid case studies to show how these concepts translate into real-world applications. Using examples drawn from a broad array of industries—from semiconductors to food processing, biomedical engineering to education—he deftly illustrates how SPC methods can streamline the manufacturing process and improve product quality. SPC Methods for Quality Improvement provides detailed, step-by-step guidance on the uses of both classical and second-generation SPC methods. Among cutting-edge methods described are those for charting processes without prior data, charting processes from start-up, and charting short runs with known false alarm rates. Readers also learn methods for studying the form of a reference distribution; how to use transformations to Q-statistics for various models; how to treat data from skewed distributions; and new ways of treating regression, multivariate, and autocorrelated data. An excellent text/primer for students and those new to SPC, SPC Methods for Quality Improvement is also a valuable guide for industrial and production engineers and managers who wish to improve existing SPC systems or to introduce SPC methods into industries where they were once inapplicable.
A guide to quality improvement methods from Healthcare Quality Improvement Partnership (HQIP) brings together twelve quality improvement (QI) methods, providing an overview of each and practical advice on how and when to implement them, with illustrative case examples. QI methods covered include clinical audit; Plan, Do, Study, Act; model for improvement; LEAN/Six Sigma; performance benchmarking, process mapping and statistical process control and it is aimed at all professionals with an interest in QI. The purpose of this guidance is to signpost those working within, leading, commissioning and using healthcare services to a broad range of quality improvement methods. It should be especially useful to those putting together quality improvement programmes.
This text is highly recommended for managers and serious students of quality. Major US companies issue this reference and training manual to all managers during their quality training. This volume is also very valuable as a stand-alone reference on using statistics with a business and quality perspective.
The Quality Toolbox is a comprehensive reference to a variety of methods and techniques: those most commonly used for quality improvement, many less commonly used, and some created by the author and not available elsewhere. The reader will find the widely used seven basic quality control tools (for example, fishbone diagram, and Pareto chart) as well as the newer management and planning tools. Tools are included for generating and organizing ideas, evaluating ideas, analyzing processes, determining root causes, planning, and basic data-handling and statistics. The book is written and organized to be as simple as possible to use so that anyone can find and learn new tools without a teacher. Above all, this is an instruction book. The reader can learn new tools or, for familiar tools, discover new variations or applications. It also is a reference book, organized so that a half-remembered tool can be found and reviewed easily, and the right tool to solve a particular problem or achieve a specific goal can be quickly identified. With this book close at hand, a quality improvement team becomes capable of more efficient and effective work with less assistance from a trained quality consultant. Quality and training professionals also will find it a handy reference and quick way to expand their repertoire of tools, techniques, applications, and tricks. For this second edition, Tague added 34 tools and 18 variations. The "Quality Improvement Stories" chapter has been expanded to include detailed case studies from three Baldrige Award winners. An entirely new chapter, "Mega-Tools: Quality Management Systems," puts the tools into two contexts: the historical evolution of quality improvement and the quality management systems within which the tools are used. This edition liberally uses icons with each tool description to reinforce for the reader what kind of tool it is and where it is used within the improvement process.
