Chapter 9. Using Statistical Process Control for Continual Improvement
- Shirley Coleman Technical Director3,
- Tony Greenfield4,
- Dave Stewardson3,
- Douglas C. Montgomery5
Published Online: 3 MAR 2008
DOI: 10.1002/9780470997482.ch9
Copyright © 2008 John Wiley & Sons, Ltd
Book Title
Statistical Practice in Business and Industry
Additional Information
How to Cite
Wheeler, D. J. and Evandt, Ø. (2008) Using Statistical Process Control for Continual Improvement, in Statistical Practice in Business and Industry (eds S. Coleman, T. Greenfield, D. Stewardson and D. C. Montgomery), John Wiley & Sons, Ltd, Chichester, UK. doi: 10.1002/9780470997482.ch9
Editor Information
- 3
Industrial Statistics Research Unit, Newcastle University, Newcastle upon Tyne NE1 7RU, UK
- 4
Greenfield Research, Little Hucklow, Buxton SK17 8RT, UK
- 5
Regents' Professor of Industrial Engineering & Statistics, ASU Foundation Professor of Engineering, Department of Industrial Engineering Arizona State University Tempe, AZ 85287-5906, USA
Publication History
- Published Online: 3 MAR 2008
- Published Print: 7 MAR 2008
Book Series:
ISBN Information
Print ISBN: 9780470014974
Online ISBN: 9780470997482
- Summary
- Chapter
Keywords:
- statistical process control (SPC);
- Western approach to quality - burn the toast and scrape it';
- cut-your-losses approach;
- Shewhart's approach and two-point moving ranges;
- process behavior chart;
- threshold state (product trouble);
- brink of chaos (process trouble);
- cycle of despair;
- Shewart's approach - existing data learning
Summary
This chapter contains sections titled:
The problem of variation
Shewhart's approach
Learning from Process Data
The average and range chart
The chart for individual values and moving ranges
So what can we learn from a process behavior chart?
Four possibilities for any process
How can three-sigma limits work with all types of data?
Some misunderstandings about SPC
Shewhart's approach to learning from existing data
References
Further reading