Table of Contents
Part I: Introduction
1. The Need for and Objectives and Benefits of Design of Experiments
2. Fads; Potions; Nostrums of the Quality Movement in the Last 50 Years
3. A Powerful Tool Kit for the 21st Century.
Part II: Preamble to the Design of Experiments (DOE)
4. The Measurement of Process Capability
5. Variation: An Industrial Epidemic
6. The Three Approaches to DOE: Classical, Taguchi, and Shainin
7. A Synopsis of the 10 Powerful DOE Tools
Part III: "Talking to the Parts" - A Set of Clue-Generating Tools
8. The Multi-Vari Analysis: Homing In on the Red X
9. The Concentration Chart: Pinpointing Locations of Repetitive Problems
10. Components Search: Simple, Smooth Swapping
11. Paired Comparisons: An Elegant, Versatile Tool
12. Product / Process Search: Pinpointing Process Variables
Part IV: Formal DOE to Characterize a Product / Process
13. Variables Search: The Mount Everest in the Search for the Red X
14. The Full Factorial: Purest Technique for Separating and Quantifying Each Interaction Effect
15. B versus C: An Excellent Validation Technique
Part V: DOE Optimization
16. Scatter Plots to Achieve Realistic Specifications and Tolerances
17. Response Surface Methodology (RSM): To Optimize Interactions
Part VI: The Transition from DOE to SPC: Vital Disciplines
18. Positrol: Freezing Process Gains
19. Process Certification: Eliminating Peripheral Causes of Poor Quality
Part VII: Statistical Process Control: For Monitoring Quality
20. Control Charts: A Technique Whose Time Has Gone
21. Pre-Control: A Technique Whose Time Has Come
Part VIII: Linkage of DOE to Reliability
22. Multiple Environment Over Stress Tests: As Effective for Reliability as DOE is for Quality
Part IX: A Logical Sequence in the Use of DOE Tools
23. Case Studies in Sequential DOE Tools to Solve Chronic Problems
Part X: From Classroom Instruction to True Learning on the Job
24. Learning by Doing
References
Index