Emphasizing the importance of understanding and reducing process variation to achieve quality manufacturing performance, this work establishes how statistical process control (SPC) provides powerful tools for measuring and regulating manufacturing processes. It presents information derived from time-tested applications of SPC techniques at on-site process situations in manufacturing. It is designed to assist manufacturing organizations in explaining and implementing successful SPC programmes.

A major tool for quality control and management, statistical process control (SPC) monitors sequential processes, such as production lines and Internet traffic, to ensure that they work stably and satisfactorily. Along with covering traditional methods, Introduction to Statistical Process Control describes many recent SPC methods that improve upon

This book provides an introduction to statistical process control in automated manufacturing and suggests implementation strategies. It focuses on time series applications in statistical process control and explores the role of knowledge-based systems in process control.

The business, commercial and public-sector world has changed dramatically since John Oakland wrote the first edition of Statistical Process Control – a practical guide in the mid-eighties. Then people were rediscovering statistical methods of ‘quality control’ and the book responded to an often desperate need to find out about the techniques and use them on data. Pressure over time from organizations supplying directly to the consumer, typically in the automotive and high technology sectors, forced those in charge of the supplying production and service operations to think more about preventing problems than how to find and fix them. Subsequent editions retained the ‘took kit’ approach of the first but included some of the ‘philosophy’ behind the techniques and their use. The theme which runs throughout the 7th edition is still processes - that require understanding, have variation, must be properly controlled, have a capability, and need improvement - the five sections of this new edition. SPC never has been and never will be simply a ‘took kit’ and in this book the authors provide, not only the instructional guide for the tools, but communicate the management practices which have become so vital to success in organizations throughout the world. The book is supported by the authors' extensive and latest consulting work within thousands of organisations worldwide. Fully updated to include real-life case studies, new research based on client work from an array of industries, and integration with the latest computer methods and Minitab software, the book also retains its valued textbook quality through clear learning objectives and end of chapter discussion questions. It can still serve as a textbook for both student and practicing engineers, scientists, technologists, managers and for anyone wishing to understand or implement modern statistical process control techniques.

A comprehensive treatment for implementing Statistical Process Control (SPC) in the food industry This book provides managers, engineers, and practitioners with an overview of necessary and relevant tools of Statistical Process Control, a roadmap for their implementation, the importance of engagement and teamwork, SPC leadership, success factors of the readiness and implementation, and some of the key lessons learned from a number of food companies. Illustrated with numerous examples from global real-world case studies, this book demonstrates the power of various SPC tools in a comprehensive manner. The final part of the book highlights the critical challenges encountered while implementing SPC in the food industry globally. Statistical Process Control for the Food Industry: A Guide for Practitioners and Managers explores the opportunities to deliver customized SPC training programs for local food companies. It offers insightful chapter covering everything from the philosophy and fundamentals of quality control in the food industry all the way up to case studies of SPC application in the food industry on both the quality and safety aspect, making it an excellent "cookbook" for the managers in the food industry to assess and initiating the SPC application in their respective companies. Covers concise and clear guidelines for the application of SPC tools in any food companies' environment Provides appropriate guidelines showing the organizational readiness level before the food companies adopt SPC Explicitly comments on success factors, motivations, and challenges in the food industry Addresses quality and safety issues in the food industry Presents numerous, global, real-world case studies of SPC in the food industry Statistical Process Control for the Food Industry: A Guide for Practitioners and Managers can be used to train upper middle and senior managers in improving food quality and reducing food waste using SPC as one of the core techniques. It's also an excellent book for graduate students of food engineering, food quality management and/or food technology, and process management.

Mastering Statistical Process Control shows how to understand business or process performance more clearly and more effectively. This practical book is based on a rich and varied selection of case studies from across industry and commerce, including material from the manufacturing, extractive and service sectors. It will enable readers to understand how SPC can be used to maximum effect, and will deliver more effective monitoring, control and improvement in systems, processes and management. The common obstacle to successful use of SPC is getting bogged down with control charts, forgetting that visual representation of data is but a tool and not an end in itself. Mastering SPC demonstrates how statistical tools are applied and used in reality. This is a book that will open up the power of SPC for many: managers, quality professionals, engineers and analysts, as well as students, will welcome the clarity and explanation that it brings to understanding the use and benefit of SPC in a wide range of engineering, production and service situations. Key case studies include using SPC to: · Measure quality and human factors · Monitor process performance accurately over long periods · Develop best-practice benchmarks using control charts · Maximise profitability of fixed assets · Improve customer service and satisfaction

Once solely the domain of engineers, quality control has become a vital business operation used to increase productivity and secure competitive advantage. Introduction to Statistical Quality Control offers a detailed presentation of the modern statistical methods for quality control and improvement. Thorough coverage of statistical process control (SPC) demonstrates the efficacy of statistically-oriented experiments in the context of process characterization, optimization, and acceptance sampling, while examination of the implementation process provides context to real-world applications. Emphasis on Six Sigma DMAIC (Define, Measure, Analyze, Improve and Control) provides a strategic problem-solving framework that can be applied across a variety of disciplines. Adopting a balanced approach to traditional and modern methods, this text includes coverage of SQC techniques in both industrial and non-manufacturing settings, providing fundamental knowledge to students of engineering, statistics, business, and management sciences. A strong pedagogical toolset, including multiple practice problems, real-world data sets and examples, and incorporation of Minitab statistics software, provides students with a solid base of conceptual and practical knowledge.

A unique approach to understanding the foundations of statistical quality control with a focus on the latest developments in nonparametric control charting methodologies Statistical Process Control (SPC) methods have a long and successful history and have revolutionized many facets of industrial production around the world. This book addresses recent developments in statistical process control bringing the modern use of computers and simulations along with theory within the reach of both the researchers and practitioners. The emphasis is on the burgeoning field of nonparametric SPC (NSPC) and the many new methodologies developed by researchers worldwide that are revolutionizing SPC. Over the last several years research in SPC, particularly on control charts, has seen phenomenal growth. Control charts are no longer confined to manufacturing and are now applied for process control and monitoring in a wide array of applications, from education, to environmental monitoring, to disease mapping, to crime prevention. This book addresses quality control methodology, especially control charts, from a statistician’s viewpoint, striking a careful balance between theory and practice. Although the focus is on the newer nonparametric control charts, the reader is first introduced to the main classes of the parametric control charts and the associated theory, so that the proper foundational background can be laid. Reviews basic SPC theory and terminology, the different types of control charts, control chart design, sample size, sampling frequency, control limits, and more Focuses on the distribution-free (nonparametric) charts for the cases in which the underlying process distribution is unknown Provides guidance on control chart selection, choosing control limits and other quality related matters, along with all relevant formulas and tables Uses computer simulations and graphics to illustrate concepts and explore the latest research in SPC Offering a uniquely balanced presentation of both theory and practice, Nonparametric Methods for Statistical Quality Control is a vital resource for students, interested practitioners, researchers, and anyone with an appropriate background in statistics interested in learning about the foundations of SPC and latest developments in NSPC.