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Chapter 1 Product Management and the Fundamental Metrics
Chapter 2 Product Value and Demand
Chapter 3 System Level Design and Strategic Experimentation
Chapter 4 Statistics
Chapter 5 Role of Variation on Product Value
Chapter 6 Design of Shear Pin using Monte Carlo Simulation
Chapter 7 Level 1: Multiple Regression with Constant Variance
Chapter 8 Level 2: Satterthwaite s df and Approximate t Test
Chapter 9 Level 3: Influence of the Factors on Mean and Variance
Chapter 10 Level 4: Testing for Strategic Significance 10.1
Chapter 11 When Plans Have Been Modified or Need to be
Chapter 12 Applications of Lognormal, Binomial, and Poisson Distributions
Chapter 13 LIB and the Weibull Distribution
Chapter 14 Signal Response (Dynamic or Multiple Target) Problems
Chapter 15 Strategic Response Surface Maps
Appendix A. Constructing Design Arrays
Appendix B. Bonferroni Method for Converting PWE to EWE
Appendix C. General Aspects of Regular Least Square Solution
Appendix D. Monte Carlo Analysis of a Binomial Distribution Problem
Appendix E. Monte Carlo Analysis of a Poisson Distribution Problem
Appendix F. Use of SDWs and Templates for Analysis Automation
Appendix G. Derivation of the Individual F Test for the Influence of Factors on Log Variance
Appendix H. Bits for Drilling Printed Circuit Vias
Appendix I. Point Estimates for the Variance of the SN Ratio
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Add Design for Six SIGMA as Strategic Experimentation: Attribute Improvements, Fundamental Metrics, Bottom-Line Metrics: Value, Cost, Pace of Innovation, Design for Six Sigma as Strategic Experimentation develops a practical, science-based methodology for guiding the product realization process for highly-competitive markets. Forecasts of cash flow, market share, and price are used to select the final desi, Design for Six SIGMA as Strategic Experimentation: Attribute Improvements, Fundamental Metrics, Bottom-Line Metrics: Value, Cost, Pace of Innovation to your collection on WonderClub |