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Design of Experiments for Engineers and Scientists
- 3rd Edition - June 2, 2023
- Author: Jiju Antony
- Language: English
- Paperback ISBN:9 7 8 - 0 - 4 4 3 - 1 5 1 7 3 - 6
- eBook ISBN:9 7 8 - 0 - 4 4 3 - 1 5 1 7 4 - 3
This third edition of Design of Experiments for Engineers and Scientists adds to the tried and trusted tools that were successful in so many engineering organizations with new… Read more
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Request a sales quoteThis third edition of Design of Experiments for Engineers and Scientists adds to the tried and trusted tools that were successful in so many engineering organizations with new coverage of design of experiments (DoE) in the service sector. Case studies are updated throughout, and new ones are added on dentistry, higher education, and utilities.
Although many books have been written on DoE for statisticians, this book overcomes the challenges a wider audience faces in using statistics by using easy-to-read graphical tools. Readers will find the concepts in this book both familiar and easy to understand, and users will soon be able to apply them in their work or research.
This classic book is essential reading for engineers and scientists from all disciplines tackling all kinds of product and process quality problems and will be an ideal resource for students of this topic.
- Written in nonstatistical language, the book is an essential and accessible text for scientists and engineers who want to learn how to use DoE
- Explains why teaching DoE techniques in the improvement phase of Six Sigma is an important part of problem-solving methodology
- New edition includes two new chapters on DoE for services as well as case studies illustrating its wider application in the service industry
Graduate students and researchers in engineering subjects
- Cover image
- Title page
- Table of Contents
- Copyright
- Dedication
- About the author
- Preface
- Acknowledgements
- 1. Introduction to industrial experimentation
- Abstract
- 1.1 Introduction
- 1.2 Some fundamental and practical issues in industrial experimentation
- 1.3 Statistical thinking and its role within DOE
- Exercises
- References
- 2. Fundamentals of design of experiments
- Abstract
- 2.1 Introduction
- 2.2 Basic principles of DOE
- 2.3 Degrees of freedom
- 2.4 Confounding
- 2.5 Selection of quality characteristics for industrial experiments
- Exercises
- References
- 3. Understanding key interactions in processes
- Abstract
- 3.1 Introduction
- 3.2 Alternative method for calculating the two-order interaction effect
- 3.3 Synergistic interaction versus antagonistic interaction
- 3.4 Scenario 1
- 3.5 Scenario 2
- 3.6 Scenario 3
- Exercises
- References
- 4. A systematic methodology for design of experiments
- Abstract
- 4.1 Introduction
- 4.2 Barriers in the successful application of DOE
- 4.3 A practical methodology for DOE
- 4.4 Analytical tools of DOE
- 4.5 Model building for predicting response function
- 4.6 Confidence interval for the mean response
- 4.7 Statistical, technical and sociological dimensions of DOE
- Exercises
- References
- 5. Screening designs
- Abstract
- 5.1 Introduction
- 5.2 Geometric and non-geometric P–B designs
- Exercises
- References
- 6. Full factorial designs
- Abstract
- 6.1 Introduction
- 6.2 Example of a 22 full factorial design
- 6.3 Example of a 23 full factorial design
- 6.4 Example of a 24 full factorial design
- Exercises
- References
- 7. Fractional factorial designs
- Abstract
- 7.1 Introduction
- 7.2 Construction of half-fractional factorial designs
- 7.3 Example of a 2(7−4) factorial design
- 7.4 An application of 2-level fractional factorial design
- Exercises
- References
- Further reading
- 8. Some useful and practical tips for making your industrial experiments successful
- Abstract
- 8.1 Introduction
- Exercises
- References
- 9. Case studies
- Abstract
- 9.1 Introduction
- 9.2 Case studies
- 9.3 Discussion and limitations of the study
- References
- Further reading
- 10. Design of experiments and its applications in the service industry
- Abstract
- 10.1 Introduction to the service industry
- 10.2 Fundamental differences between the manufacturing and service organisations
- 10.3 DOE in the service industry: fundamental challenges
- 10.4 Benefits of DOE in service/non-manufacturing industry
- 10.5 DOE: case examples from the service industry
- 10.6 Role of computer simulation models within DOE
- Exercises
- References
- 11. Design of experiments and its role within Six Sigma
- Abstract
- 11.1 What is Six Sigma?
- 11.2 How Six Sigma is different from other quality improvement initiatives of the past
- 11.3 Who makes Six Sigma work?
- 11.4 Six Sigma methodology (DMAIC methodology)
- 11.5 DOE and its role within Six Sigma
- Exercises
- References
- 12. Design of Experiments in the service industry: a critical literature review and future research directions
- Abstract
- 12.1 Introduction
- 12.2 Methodology
- 12.3 Key findings
- 12.4 Discussion and implications
- 12.5 Limitations and future directions of research
- References
- 13. Design of Experiments in the service industry: results from a global survey and directions for further research
- Abstract
- 13.1 Introduction
- Appendix A Statements related to the challenges in applying Design of Experiments (DoE) in the service industry
- References
- Index
- No. of pages: 294
- Language: English
- Edition: 3
- Published: June 2, 2023
- Imprint: Elsevier
- Paperback ISBN: 9780443151736
- eBook ISBN: 9780443151743
JA
Jiju Antony
Jiju Antony is a professor of Industrial and Systems Engineering and certified LSS Master Black Belt in the department of Industrial and Systems Engineering at Khalifa University, Abu Dhabi, UAE. He has a proven track record for conducting internationally leading research in the field of quality management, quality engineering, continuous improvement, and operational excellence. Professor Antony has authored over 500 journal, conference, and white papers; 14 textbooks; and two conference proceedings. He is the Editor in Chief of the International Journal of Lean Six Sigma, Editor in Chief of the International Journal of Quality and Reliability Management, and Associate Editor of the TQM Journal and BE Journal. Professor Antony has worked on a number of consultancy projects with several blue-chip companies such as Rolls-Royce, Bosch, Siemens, Parker Pen, Siemens, Johnson and Johnson, GE Plastics, Ford, Scottish Power, Tata Motors, Thales, Nokia, Philips, General Electric, NHS, Glasgow City Council, ACCESS, Scottish Water, Police Scotland, university sectors, and a number of small- and medium-sized enterprises.
Affiliations and expertise
Professor of Operations and Supply Chain Management, Newcastle Business School, Northumbria University, Newcastle, United KingdomRead Design of Experiments for Engineers and Scientists on ScienceDirect