Product Management : Value, Quality, Cost, Price, Profit and Organization

In today's highly competive markets, companies must favourably differentiate their products by continually developing, testing and adopting fresh ideas. This book describes how to plan new products in terms of their forecasted profitability, how competing products influence the bottom-line, how to design and anlyze experiments to determine the best subsystem and component alternatives from a strategic perspective, and how to structure teams to manage the process.
This book is essential reading for involved in the design and manufacture of new products, including engineers, product designers and researchers in the manufacturing and management.

Preface
Acknowledgements

Chapter 1 : Product Realization in the Global Marketplace
Chapter 2 : Motivation and Consumer Behavior
Chapter 3 : Enterprise Model
Chapter 4 : Definition of Quality
Chapter 5 : Forecasting the Value of Future Products
Chapter 6 : Total Quality Management
Chapter 7 : Product Planning and Quality Deployment
Chapter 8 : Parameter and Tolerance Design
Chapter 9 : Significance of Results
Chapter 10 : Costs
Chapter 11 : Statistical Quality Control

Case Study 1. NIB1 Single-Attribute Thin Film
Case Study 2. NIB2 Problem
Case Study 3. LIB Problem
Case Study 4. Significance Testing a Multi Attribute Problem
Case Study 5. Error Analysis for Direct Value (DV) Method
Case Study 6. Use of the Direct Value (DV) Method When Considering Multiple Attributes Jointly

Appendix A : Probability and Statistics
A.1 : Concept of Probability
A.2 : Frequency Functions, Expectations, and the Normal Distribution
A.3 : Central Limit Theorem
A.4 : Normal Probability Plots
A.5 : Hypothesis Testing
A.6 : The Chi-Squared Distribution
A.7 : The F Distribution (Significance Between Two Measured Sample Variances)
A.8 : Selecting Points at Random From Distributions
A.9 : Significance of Coefficients
Appendix B : Design of Experiments
B.1 : Introduction
B.2 : The Lambda Set Point Series
B.3 : Comparison to Taylor’s Series
B.4 : The Phi Set Point Series
B.5 : Baseline Considerations
B.6 : [X] Array Construction Rules
B.7 : Comparisons With Full Factorial Arrays
B.8 : Designing an Experiment
B.9 : Student’s t for Coefficients
B.10 : [X] Versus [X] for Significance Testing

References
Index

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