Process Improvement using Data
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Kevin Dunn, McMaster University
Copyright Year:
Publisher: Kevin Dunn
Language: English
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Conditions of Use
Attribution-ShareAlike
CC BY-SA
Table of Contents
- Preface
- 1. Data visualization
- 2. Univariate review
- 3. Process monitoring
- 4. Least-squares modelling
- 5. Design and analysis of experiments
- 6. Latent variable modelling
- 7. Product development and product improvement
- Index
About the Book
There is no other free, coherent text that covers what engineers and scientists actually do with process data (visualization, regression, designed experiments, process monitoring, and multivariate / latent-variable methods) in one volume.
Most textbooks pick one of those topics and go deep. Practitioners need all of them, and need to see how they fit together, because real industrial problems don't respect chapter boundaries. Process Improvement using Data was written to fill that gap, and has been continuously refined in industry-facing classrooms and in industrial practice since 2010.
It is suitable for upper-undergraduate or introductory-graduate courses, and for self-study by working engineers and data scientists with a basic statistics background.
About the Contributors
Author
Kevin Dunn, McMaster University