Statistical Process Control: 7th Edition (Paperback) book cover

Statistical Process Control

7th Edition

By John Oakland, Robert James Oakland

Routledge

430 pages | 135 B/W Illus.

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pub: 2018-10-22
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Description

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.

Reviews

John 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 Laser

The 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 Institute

SPC 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 Office

The 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 plc

An 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

Table of Contents

Part 1 Process Understanding

1 Quality, processes and control

Objectives

1.1 The basic concepts

1.2 Design, conformance and costs

1.3 Quality, processes systems, teams, tools and SPC

1.4 Some basic tools

Chapter highlights

References and further reading

Discussion questions

2. Understanding the process

Objectives

2.1 Improving customer satisfaction through process management

2.2 Information about the process

2.3 Process mapping and flowcharting

2.4 Process analysis

2.5 Statistical process control and process understanding

Chapter highlights

References and further reading

Discussion questions

3. Process data collection and presentation

Objectives

3.1 The systematic approach

3.2 Data collection

3.3 Bar charts and histograms

3.4 Graphs, run charts and other pictures

3.5 Conclusions

Chapter highlights

References and further reading

Discussion questions

 

Part 2 Process Variability

1. Variation: understanding and decision making

Objectives

1.1 How some managers look at data

1.2 Interpretation of data

1.3 Causes of variation

1.4 Accuracy and precision

1.5 Variation and management

Chapter 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 highlights

References and further reading

Discussion questions

Worked examples using the normal distribution 99

Part 3 Process Control

1. 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 159

2.4 Moving mean, moving range and exponentially weighted moving average (EWMA) charts

2.5 Control charts for standard deviation (σ)

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 Capability

4. 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 269

Chapter highlights

References and further reading

Discussion questions

Worked examples

Part 5 Process Improvement

1. 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

Appendices

A. 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 404

F. 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

About the Authors

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.

Subject Categories

BISAC Subject Codes/Headings:
BUS000000
BUSINESS & ECONOMICS / General
TEC009010
TECHNOLOGY & ENGINEERING / Chemical & Biochemical
TEC032000
TECHNOLOGY & ENGINEERING / Quality Control

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