Statistical Methods for Quality Improvement


Book Description

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.







Modern Statistics for Engineering and Quality Improvement


Book Description

Through years of teaching experience, John S. Lawson and John Erjavec have learned that it doesn't take much theoretical background before engineers can learn practical methods of data collections, analysis, and interpretation that will be useful in real life and on the job. With this premise in mind, the authors wrote ENGINEERING AND INDUSTRIAL STATISTICS, which includes the basic topics of engineering statistics but puts less emphasis on the theoretical concepts and elementary topics usually found in an introductory statistics book. Instead, the authors put more emphasis on techniques that will be useful for engineers. With fewer details of traditional probability and inference and more emphasis on the topics useful to engineers, the book is flexible for instructors and interesting for students.




Introduction to Engineering Statistics and Lean Sigma


Book Description

Lean production, has long been regarded as critical to business success in many industries. Over the last ten years, instruction in six sigma has been increasingly linked with learning about the elements of lean production. Introduction to Engineering Statistics and Lean Sigma builds on the success of its first edition (Introduction to Engineering Statistics and Six Sigma) to reflect the growing importance of the "lean sigma" hybrid. As well as providing detailed definitions and case studies of all six sigma methods, Introduction to Engineering Statistics and Lean Sigma forms one of few sources on the relationship between operations research techniques and lean sigma. Readers will be given the information necessary to determine which sigma methods to apply in which situation, and to predict why and when a particular method may not be effective. Methods covered include: • control charts and advanced control charts, • failure mode and effects analysis, • Taguchi methods, • gauge R&R, and • genetic algorithms. The second edition also greatly expands the discussion of Design For Six Sigma (DFSS), which is critical for many organizations that seek to deliver desirable products that work first time. It incorporates recently emerging formulations of DFSS from industry leaders and offers more introductory material on the design of experiments, and on two level and full factorial experiments, to help improve student intuition-building and retention. The emphasis on lean production, combined with recent methods relating to Design for Six Sigma (DFSS), makes Introduction to Engineering Statistics and Lean Sigma a practical, up-to-date resource for advanced students, educators, and practitioners.




Statistical Methods for Quality of Life Studies


Book Description

On October 16 and 17, 2000, we hosted an international workshop entitled "Statistical Design, Measurement, and Analysis of Health Related Quality of Life." The workshop was held in the beautiful city of Arradon, South Brittany, France with the main goal of fostering an interdisciplinary forum for discussion of theoretical and applied statistical issues arising in studies of health-related quality of life (HRQoL). Included were biostatisticians, psychometricians and public health professionals (e.g., physicians, sociologists, psychologists) active in the study ofHRQoL. In assembling this volume, we invited each conference participant to contribute a paper based on his or her presentation and the ensuing and very interesting discussions that took place in Arradon. All papers were peer-reviewed, by anonymous reviewers, and revised before final editing and acceptance. Although this process was quite time consuming, we believe that it greatly improved the volume as a whole, making this book a valuable contribution to the field ofHRQoL research. The volume presents a broad spectrum of papers presented at the Workshop, and thus illustrates the range of current research related to the theory, methods and applications of HRQoL, as well as the interdisciplinary nature ofthis work. Following an introduction written by Sir David Cox, it includes 27 articles organized into the following chapters.




Notes On Statistics And Data Quality For Analytical Chemists


Book Description

This book is intended to help analytical chemists feel comfortable with more commonly used statistical operations and help them make effective use of the results. Emphasis is put upon computer-based methods that are applied in relation to measurement and the quality of the resulting data. The book is intended for analytical chemists working in industry but is also appropriate for students taking first degrees or an MSc in analytical chemistry.The authors have divided this book into quite short sections, each dealing with a single topic. The sections are as far as possible selfcontained, but are extensively cross-referenced. The book can therefore be used either systematically by reading the sections sequentially, or as a quick reference by going directly to the topic of interest. Every statistical method and application covered has at least one example where the results are analysed in detail. This enables readers to emulate this analysis on their own examples. All of the datasets used in examples are available for download, so that readers can compare their own output with that of the book and thus verify that they are entering data correctly into the statistical package that they happen to use./a




Applied Statistics Manual


Book Description

This book was written to provide guidance for those who need to apply statistical methods for practical use. While the book provides detailed guidance on the use of Minitab for calculation, simply entering data into a software program is not sufficient to reliably gain knowledge from data. The software will provide an answer, but the answer may be wrong if the sample was not taken properly, the data was unsuitable for the statistical test that was performed, or the wrong test was selected. It is also possible that the answer will be correct, but misinterpreted. This book provides both guidance in applying the statistical methods described as well as instructions for performing calculations without a statistical software program such as Minitab. One of the authors is a professional statistician who spent nearly 13 years working at Minitab and the other is an experienced and certified Lean Six Sigma Master Black Belt. Together, they strive to present the knowledge of a statistician in a format that can be easily understood and applied by non-statisticians facing real-world problems. Their guidance is provided with the goal of making data analysis accessible and practical. Rather than focusing on theoretical concepts, the book delivers only the information that is critical to success for the practitioner. It is a thorough guide for those who have not yet been exposed to the value of statistics, as well as a reliable reference for those who have been introduced to statistics but are not yet confident in their abilities.




Statistical Quality Assurance Methods for Engineers


Book Description

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).




Statistics for the Quality Control Chemistry Laboratory


Book Description

Statistical methods are essential tools for analysts, particularly those working in Quality Control Laboratories. This book provides a sound introduction to their use in analytical chemistry, without requiring a strong mathematical background. It emphasises simple graphical methods of data analysis, such as control charts, which are also a fundamental requirement in laboratory accreditation. A large part of the book is concerned with the design and analysis of laboratory experiments, including sample size determination. Practical case studies and many real databases from both QC laboratories and the research literature, are used to illustrate the ideas in action. The aim of Statistics for the Quality Control Chemistry Laboratory is to give the reader a strong grasp of the concept of statistical variation in laboratory data and of the value of simple statistical ideas ad methods in thinking about and manipulation such data, It will be invaluable to analysts working in QC laboratories in industry, hospitals and public health, and will also be welcomed as a textbook for aspiring analysts in colleges and universities.




Federal Statistics, Multiple Data Sources, and Privacy Protection


Book Description

The environment for obtaining information and providing statistical data for policy makers and the public has changed significantly in the past decade, raising questions about the fundamental survey paradigm that underlies federal statistics. New data sources provide opportunities to develop a new paradigm that can improve timeliness, geographic or subpopulation detail, and statistical efficiency. It also has the potential to reduce the costs of producing federal statistics. The panel's first report described federal statistical agencies' current paradigm, which relies heavily on sample surveys for producing national statistics, and challenges agencies are facing; the legal frameworks and mechanisms for protecting the privacy and confidentiality of statistical data and for providing researchers access to data, and challenges to those frameworks and mechanisms; and statistical agencies access to alternative sources of data. The panel recommended a new approach for federal statistical programs that would combine diverse data sources from government and private sector sources and the creation of a new entity that would provide the foundational elements needed for this new approach, including legal authority to access data and protect privacy. This second of the panel's two reports builds on the analysis, conclusions, and recommendations in the first one. This report assesses alternative methods for implementing a new approach that would combine diverse data sources from government and private sector sources, including describing statistical models for combining data from multiple sources; examining statistical and computer science approaches that foster privacy protections; evaluating frameworks for assessing the quality and utility of alternative data sources; and various models for implementing the recommended new entity. Together, the two reports offer ideas and recommendations to help federal statistical agencies examine and evaluate data from alternative sources and then combine them as appropriate to provide the country with more timely, actionable, and useful information for policy makers, businesses, and individuals.