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Statistical Process Control and Data Analytics

Autor John Oakland, Robert Oakland
en Limba Engleză Paperback – 2 sep 2024
The business, commercial and public-sector world has changed dramatically since John Oakland wrote the first edition of Statistical Process Control in the mid-1980s. 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 ‘tool kit’ approach of the first but included some of the ‘philosophy’ behind the techniques and their use.
Now entitled Statistical Process Control and Data Analytics, this revised and updated eighth edition retains its focus on processes that require understanding, have variation, must be properly controlled, have a capability and need improvement – as reflected in the five sections of the book. In this book the authors provide not only an 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 consulting work with thousands of organizations worldwide. A new chapter on data governance and data analytics reflects the increasing importance of big data in today’s business environment.
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 software, the book also retains its valued textbook quality through clear learning objectives and online end-of-chapter discussion questions. It can still serve as a textbook for both student and practicing engineers, scientists, technologists, managers and anyone wishing to understand or implement modern statistical process control techniques and data analytics.
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Specificații

ISBN-13: 9781032569024
ISBN-10: 1032569026
Pagini: 386
Ilustrații: 316
Dimensiuni: 174 x 246 x 24 mm
Greutate: 0.71 kg
Ediția:8
Editura: Taylor & Francis
Colecția Routledge
Locul publicării:Oxford, United Kingdom

Public țintă

Professional Practice & Development and Undergraduate Core

Cuprins

Preface                                                                                                                             
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
1.5 SPC, ‘big data’ and data analytics
Chapter highlights 
References and further reading 
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
 
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 Data quality and sharing  
3.6 Conclusions  
Chapter highlights  
References and further reading   
 
Part 2   Process variability
4  Variation understanding and decision making                                    
Objectives                                                                                                             
4.1       How some managers look at data                                                      
4.2       Interpretation of data                                                                              
4.3       Causes of variation                                                                                  
4.4       Accuracy and precision                                                                         
4.5       Variation and management                                                                   
Chapter highlights                                                                                             
References and further reading                                                                     
                                                                                                                                  
5  Variables and process variation                                                                   
Objectives                                                                                                             
5.1       Measures of accuracy or centering                                                     
5.2       Measures of precision or spread                                                         
5.3       The normal distribution                                                                         
5.4       Sampling and averages                                                                          
Chapter highlights
Worked examples using the normal distribution                                   
References and further reading                                                                     
                                                                                                                                                                               
Part 3   Process control
6  Process control using variables                                                                   
Objectives                                                                                                             
6.1       Means, ranges and charts                                                                      
6.2       Are we in control?                                                                                    
6.3       Do we continue to be in control?                                                        
6.4       Choice of sample size and frequency and control limits            
6.5       Short-, medium- and long-term variation
6.6       Process control of variables in the world of big data                
Chapter highlights
Worked examples                                                                                              
References and further reading
                                                                                                                                      
7  Other types of control charts for variables                                             
Objectives                                                                                                             
7.1       Beyond the mean and range chart                                                      
7.2       Process control for individual data                                                    
7.3       Median, mid-range and multi-vari charts                                       
7.4       Moving mean, moving range and exponentially weighted moving average (EWMA) charts                                
7.5       Control charts for standard deviation (σ)                                        
7.6       Techniques for short-run SPC                                                               
7.7       Summarizing control charts for variables and big data             
Chapter highlights
Worked example                                                                                                
References and further reading                                                                     
                                                                                                                                         
8  Process control by attributes                                                                        
Objectives                                                                                                             
8.1       Underlying concepts                                                                               
8.2       Process control for number of defectives or non-conforming units                                                                           
8.3       Process control for proportion defective or non-conforming units                                                                             
8.4       Process control for number of defects/non-conformities           
8.5       Attribute data in non-manufacturing
Chapter highlights
Worked examples                                                                                              
References and further reading                                                                     
                                                                                                              
9  Cumulative sum (cusum) charts                                                                 
Objectives                                                                                                             
9.1       Introduction to cusum charts                                                               
9.2       Interpretation of simple cusum charts                                              
9.3       Product screening and pre-selection                                                 
9.4       Cusum decision procedures                                                                 
Chapter highlights
Worked examples                                                                                              
References and further reading                                                                     
                                                                                                                                         
Part 4    Process capability
10  Process capability for variables and its measurement                        
Objectives                                                                                                             
10.1       Will it meet the requirements?                                                          
10.2       Process capability indices                                                                   
10.3       Interpreting capability indices                                                          
10.4       The use of control chart and process capability data                 
10.5       Service industry example of process capability analysis                                                                                                     
Chapter highlights
Worked examples                                                                                              
References and further reading
                    
Part 5   Process improvement
11  Process problem solving and improvement                                           
Objectives                                                                                                             
11.1       Introduction                                                                                             
11.2       Pareto analysis                                                                                        
11.3       Cause and effect analysis                                                                    
11.4       Scatter diagrams                                                                                     
11.5       Stratification                                                                                            
11.6       Summarizing problem solving and improvement                     
Chapter highlights
Worked examples                                                                                              
References and further reading                                                                     
 
12  Managing out-of-control processes                                                           
Objectives                                                                                                             
12.1       Introduction                                                                                             
12.2       Process improvement strategy                                                          
12.3       Use of control charts and data analytics for trouble-shooting
12.4       Assignable or special causes of variation and big data             
Chapter highlights                                                                                             
References and further reading                                                                     
                                                                                                                                  
13  Designing the statistical process control system with big data      
Objectives                                                                                                             
13.1       SPC and the quality management system                                     
13.2       Teamwork and process control/improvement                             
13.3       Improvements in the process                                                            
13.4       Taguchi methods
13.5       System performance – the confusion matrix                                
13.6       Moving forward with big data analytics and SPC                     
Chapter highlights                                                                                             
References and further reading                                                                     
                                                                                                                                  
14  Six-sigma process quality                                                                              
Objectives                                                                                                             
14.1       Introduction                                                                                             
14.2       The six-sigma improvement model                                                 
14.3       Six-sigma and the role of design of experiments                        
14.4       Building a six-sigma organization and culture                            
14.5       Ensuring the financial success of six-sigma projects                  
14.6       Concluding observations and links with excellence models and data analytics 
Chapter highlights
References and further reading                                                               
                        
15  Data governance and data analytics
Objectives                                                                                                             
15.1       Introduction – data attributes                                                            
15.2       Data governance strategies                                                                
15.3       Data analytics and insight
15.4       Future of process control and assurance                                       
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                                                                                    
F         Cumulative Poisson probability curves                                             
G       Confidence limits and tests of significance                                       
H      OC curves and ARL curves for X and R charts                               
I          Autocorrelation                                                                                          
J          Approximations to assist in process control of attributes             
K       Glossary of terms and symbols                                                             
Index
 
 
 
 
 

Notă biografică

John Oakland is one of the world’s top ten gurus in quality and operational excellence; Executive Chairman, Oakland Group; Emeritus Professor of Quality & Business Excellence at Leeds University Business School; Fellow of the Chartered Quality Institute (CQI); Fellow of the Royal Statistical Society (RSS); Fellow of the Cybernetics Society (CybSoc); Fellow of Research Quality Association (RQA).
Robert Oakland is Director in the Oakland Group and works across the globe helping complex organizations to unlock the power in their data using advanced analytical and statistical techniques to improve the quality, cost and delivery of their products and services.

Descriere

This revised and updated 8th edition retains its focus on processes that require understanding, have variation, must be properly controlled, have a capability, and need improvement – as reflected in the five sections of the book.