Statistical process control / John Oakland and Robert James Oakland.

Author(s)
Biography
John Oakland is one of the world’s top 10 gurus in quality & operational excellence; Executive Chairman, Oakland Consulting; Emeritus Professor of Quality & Business Excellence at Leeds University Business School , a Fellow of the Chartered Quality Institute (CQI) and a Member of American Society for Quality.

Robert Oakland works across the globe helping complex organisations to design and implement large-scale quality and operational excellence programmes to improve quality, cost and delivery of products and services. He is a consultant at Oakland Consulting, UK.

Includes bibliographical references and index.

Part 1 Process Understanding1 Quality, processes and controlObjectives1.1 The basic concepts1.2 Design, conformance and costs1.3 Quality, processes systems, teams, tools and SPC1.4 Some basic toolsChapter highlightsReferences and further readingDiscussion questions2. Understanding the processObjectives2.1 Improving customer satisfaction through process management2.2 Information about the process2.3 Process mapping and flowcharting2.4 Process analysis2.5 Statistical process control and process understandingChapter highlightsReferences and further readingDiscussion questions3. Process data collection and presentationObjectives3.1 The systematic approach3.2 Data collection3.3 Bar charts and histograms3.4 Graphs, run charts and other pictures3.5 ConclusionsChapter highlightsReferences and further readingDiscussion questions Part 2 Process Variability1. Variation: understanding and decision making Objectives 1.1 How some managers look at data 1.2 Interpretation of data1.3 Causes of variation 1.4 Accuracy and precision 1.5 Variation and managementChapter highlights References and further reading Discussion questions 2. Variables and process variation Objectives 2.1 Measures of accuracy or centring 2.2 Measures of precision or spread 2.3 The normal distribution 2.4 Sampling and averages 2.5 Chapter highlightsReferences and further reading Discussion questions Worked examples using the normal distribution 99Part 3 Process Control1. Process control using variables Objectives 1.1 Means, ranges and charts 1.2 Are we in control? 1.3 Do we continue to be in control? 1.4 Choice of sample size and frequency, and control limits 1.5 Short-, medium- and long-term variation: a change in the standard practice 1.6 Summary of SPC for variables using X and R charts Chapter highlights References and further reading Discussion questions Worked examples 2. Other types of control charts for variables Objectives 2.1 Life beyond the mean and range chart 2.2 Charts for individuals or run charts 2.3 Median, mid-range and multi-vari charts 1592.4 Moving mean, moving range and exponentially weighted moving average (EWMA) charts2.5 Control charts for standard deviation ( )2.6 Techniques for short run SPC 2.7 Summarizing control charts for variables Chapter highlights References and further reading Discussion questions Worked example 3. Process control by attributes Objectives 3.1 Underlying concepts 3.2 np-charts for number of defectives or non-conforming units 3.3 p-charts for proportion defective or non-conforming units 3.4 c-charts for number of defects/non-conformities 3.5 u-charts for number of defects/non-conformities per unit 3.6 Attribute data in non-manufacturing Chapter highlights References and further reading Discussion questions Worked examples 4. Cumulative sum (cusum) charts Objectives 4.1 Introduction to cusum charts 4.2 Interpretation of simple cusum charts 4.3 Product screening and pre-selection 4.4 Cusum decision procedures Chapter highlights References and further reading Discussion questions Worked examples Part 4 Process Capability4. Process capability for variables and its measurement Objectives 4.1 Will it meet the requirements? 4.2 Process capability indices 4.3 Interpreting capability indices 4.4 The use of control chart and process capability data 4.5 A service industry example: process capability analysis in a bank 269Chapter highlights References and further reading Discussion questions Worked examples Part 5 Process Improvement1. Process problem solving and improvement Objectives 1.1 Introduction 1.2 Pareto analysis 1.3 Cause and effect analysis 1.4 Scatter diagrams 1.5 Stratification 1.6 Summarizing problem solving and improvement Chapter highlights References and further reading Discussion questions Worked examples 2. Managing out-of-control processes Objectives 2.1 Introduction 2.2 Process improvement strategy 2.3 Use of control charts for trouble-shooting 2.4 Assignable or special causes of variation Chapter highlights References and further reading Discussion questions 3. Designing the statistical process control system Objectives 3.1 SPC and the quality management system 3.2 Teamwork and process control/improvement 3.3 Improvements in the process 3.4 Taguchi methods 3.5 Summarizing improvement Chapter highlights References and further reading Discussion questions 4. Six-sigma process quality Objectives 4.1 Introduction 4.2 The six-sigma improvement model 4.3 Six-sigma and the role of Design of Experiments 4.4 Building a six-sigma organization and culture 4.5 Ensuring the financial success of six-sigma projects 4.6 Concluding observations and links with Excellence Chapter highlights References and further reading Discussion questions 5. The implementation of statistical process control Objectives 5.1 Introduction 5.2 Successful users of SPC and the benefits derived 5.3 The implementation of SPC Chapter highlights References and further reading AppendicesA. The normal distribution and non-normality B. Constants used in the design of control charts for mean C. Constants used in the design of control charts for range D. Constants used in the design of control charts for median and range E. Constants used in the design of control charts for standard deviation 404F. Cumulative Poisson probability tables G. Confidence limits and tests of significance H. OC curves and ARL curves for -- and R charts I. Autocorrelation J. Approximations to assist in process control of attributes K. Glossary of terms and symbols Index

This is the go-to book for information on process control. It keeps the customer and the voice of the customer as its central thread throughout the book. It is refreshing to see the customer frequently referenced in the chapters... Statistical Process Control, 7th Edition, provides an in-depth practical guide for statistical process control, divided into digestible chapters with learning outcomes. This is suitable for quality professionals in a variety of industries, and students who want a useful guide for robust techniques.Jigisha Solanki, Quality Assurance Lead at Volkswagen Financial Services, UKJohn and Robert Oakland's 7th edition of SPC shows in an excellent way that understanding of processes still matters in 21st century. The logical structure, the combination of sound knowledge and profound application experience makes this book a must-read. The fundamental concepts are easy to read, with the right level of detail and excellent new case examples, enriched with insights from Oakland's vast experience in consulting work.Harald Schubert, Head of Quality and Business Excellence, Bystronic LaserThe 7th edition remains the go-to reference for the practical application of SPC, smartly updated to recognise the huge impact that quantum computing, interconnectivity, big data and artificial intelligence will increasingly have on organisations, and the inevitable need to transform business models, systems and processes at speed to retain competitive advantage.Vincent Desmond, CEO; Chartered Quality InstituteSPC 7th Edition excellently reflects how to take into account the variation in the way that services are delivered in the current digital era, understanding where the effort needs to be focused to make improvements in our organisations.Carlos Vazquez, Head of Performance Management, Transport for London, Programme Management OfficeThe updated edition of 'Statistical Process Control' continues to form part of the essential reference text for anyone looking to make sense of data used in everyday business. Through revised case studies - based upon real life & wide-ranging experiences of The Oakland Group, guidance is given on a variety of statistical approaches to help assess data in a manner that avoids unnecessary complexities, enabling broader understanding of concepts that in turn support decision making, thereby enabling good business and meaningful outcomes.Jonathan Davies, Group Quality Director, FireAngel plcAn essential reference point for all of those involved with process at whatever level, the latest update helps to open your eyes to the opportunities presented from the digital transformation of the 21st century. The book neatly challenges the myth that SPC can only be applied in manufacturing with a broad range of case studies to help the reader with a practical approach; well done!Ian Mitchell, Quality & Business Improvement Director, Network Rail; Chair Board of Trustees, CQI'This book has always been my go-to reference for all things related to statistical process control. This latest version with its revised case studies will continue to be an essential reference for a wide range of readers teaching them how to implement statistical process control techniques for effective monitoring and management of all types of processes.'Richard Allan, Director, Global Quality Assurance, Kimberly-Clark Corporation.'A timely update to this important book. If 'data science' and 'big data analytics' are to provide us with reliable repeatable insights then practitioners would do well to adopt the robust, well founded methods and techniques proposed in this work.'Dr. John Beckford, Visiting Professor, Centre for Information Management, Loughborough University, Author of 'Quality' and 'The Intelligent Organisation'"An understanding of Statistical Process Control is pivotal in life science research. This can be very scary territory for non-statisticians. Fortunately, the authors are quite clear that this book is not written for professional statisticians. The seventh edition has been updated to reflect developments in the availability and use of data and it remains the most valuable resource for readers from all backgrounds."Andrew Waddell, Director, TMQA and past Chair of the Research Quality Association"Effective implementation of statistical process control contributes to market competitiveness and increased profitability for many successful organisations. For those interested in process control for quality management and process improvement, the book is informative and not intimidating. The content allows for self-instruction by those unfamiliar with statistical process control...In summary, Statistical Process Control presents approaches for those wanting to understand and apply controls to the total quality strategy of their company to enhance profitability."Jennifer Bell, holds a PhD Molecular Microbiology and an MSc in Pharmaceutical Manufacturing Technology.