Revised and expanded, this Second Edition continues to explore the modern practice of statistical quality control, providing comprehensive coverage of the subject from basic principles to state-of-the-art concepts and applications. The objective is to give the reader a thorough grounding in the principles of statistical quality control and a basis for applying those principles in a wide variety of both product and nonproduct situations. Divided into four parts, it contains numerous changes, including a more detailed discussion of the basic SPC problem-solving tools and two new case studies, expanded treatment on variable control charts with new examples, a chapter devoted entirely to cumulative-sum control charts and exponentially-weighted, moving-average control charts, and a new section on process improvement with designed experiments.
"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, provides students with a solid base of conceptual and practical knowledge."--
Farnum's text takes a state-of-the-art approach to quality management. From the outset, it emphasizes the modern philosophy of continuous quality improvement and quality control. It is written for courses where both modern statistical methods for quality and their implementation into business are covered. In straightforward terms, the book explains the concepts and techniques that are essential to quality control, including cutting-edge topics.
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.
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
The 2015 version of ISO 9001 brings many enriching changes to promote quality excellence by organizations. The most significant change is the reinforcement of the fact that ISO 9001 is not just a quality issue. It is relevant as an overarching management topic. The book explains the requirements of the revised (2015) version of ISO 9001 in simple and practical manner. The objective has been to enhance understanding of the subject matter by managers and quality professionals. A conceptual understanding shall enable managers and professionals to design better systems and processes uniquely suited to their respective organizations. In view of this the first five chapters of the book explain concepts on QUALITY, PROCESS, PROCESS APPROACH / MANAGEMENT and PDCA. These are relevant for all management system standards being developed by International Organization for Standardization with the High Level Structure. Part II of the book goes into details of each clause focusing on processes and process interactions. We expect that the readers will appreciate that ISO 9001, now focuses more on expected outcomes through processes than mandating too many requirements.
Master Statistical Quality Control using JMP ! Using examples from the popular textbook by Douglas Montgomery, Introduction to Statistical Quality Control: A JMP Companion demonstrates the powerful Statistical Quality Control (SQC) tools found in JMP. Geared toward students and practitioners of SQC who are using these techniques to monitor and improve products and processes, this companion provides step-by-step instructions on how to use JMP to generate the output and solutions found in Montgomery’s book. The authors combine their many years of experience as passionate practitioners of SQC and their expertise using JMP to highlight the recent advances in JMP’s Analyze menu, and in particular, Quality and Process. Key JMP platforms include: Control Chart Builder CUSUM Control Chart Control Chart (XBar, IR, P, NP, C, U, UWMA, EWMA, CUSUM) Process Screening Process Capability Measurement System Analysis Time Series Multivariate Control Chart Multivariate and Principal Components Distribution For anyone who wants to learn how to use JMP to more easily explore data using tools associated with Statistical Process Control, Process Capability Analysis, Measurement System Analysis, Advanced Statistical Process Control, and Process Health Assessment, this book is a must!
"While it is usually helpful to launch improvement programs, many such programs soon get bogged down in detail. They either address the wrong problems, or they keep beating on the same solutions, wondering why things don't improve. This is when you need an objective way to look at the problems. This is the time to get some data." Watts S. Humphrey, from the Foreword This book, drawing on work done at the Software Engineering Institute and other organizations, shows how to use measurements to manage and improve software processes. The authors explain specifically how quality characteristics of software products and processes can be quantified, plotted, and analyzed so the performance of software development activities can be predicted, controlled, and guided to achieve both business and technical goals. The measurement methods presented, based on the principles of statistical quality control, are illuminated by application examples taken from industry. Although many of the methods discussed are applicable to individual projects, the book's primary focus is on the steps software development organizations can take toward broad-reaching, long-term success. The book particularly addresses the needs of software managers and practitioners who have already set up some kind of basic measurement process and are ready to take the next step by collecting and analyzing software data as a basis for making process decisions and predicting process performance. Highlights of the book include: Insight into developing a clear framework for measuring process behavior Discussions of process performance, stability, compliance, capability, and improvement Explanations of what you want to measure (and why) and instructions on how to collect your data Step-by-step guidance on how to get started using statistical process control If you have responsibilities for product quality or process performance and you are ready to use measurements to manage, control, and predict your software processes, this book will be an invaluable resource.
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.
Nahmias and Olsen skillfully blend comprehensive coverage of topics with careful integration of mathematics. The authors’ decades of experience in the field contributed to the success of previous editions; the eighth edition continues the long tradition of excellence. Clearly written, reasonably priced, with an abundance of expertly formulated practice problems and updated examples, this textbook is essential reading for analyzing and improving all facets of operations. Some of the material in the newest edition has been reorganized. For example, the first chapter introduces service strategy, the product/process matrix and flexible manufacturing systems, benchmarking, the productivity frontier, the innovation curve, and lean production as a strategy. The focus is slightly more international. The analysis of capacity growth planning now appears in the chapter on supply chain analytics. Aggregate planning details were added to chapter 3, including chase and level strategies in an appendix to the chapter. There is an expanded discussion on risk pooling in the chapter on supply chain strategy. The mechanics behind lean production are included in the chapter on push and pull production systems. The chapter on quality and assurance downplays sampling in favor of discussions of quality management, process capability, and the waste elimination side of lean. The separate chapter on facilities layout and location was eliminated and the information redistributed throughout the text. The authors reinforce the learning process through key points at the beginning of each chapter to guide the reader, snapshots that provide useful examples of applications to businesses, and historical notes that provide a context for the topics discussed. Production and Operations Analytics, 8/e provides the tools for adapting to the dynamic global marketplace.
