Design for Six SIGMA Statistics: 59 Tools for Diagnosing and Solving Problems in Dffs Initiatives - Andrew Sleeper
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This rigorous text provides the user with statistical tools for rooting out and solving problems in Design for Six Sigma initiatives
>In today's competitive environment, companies can no longer produce goods and services that are merely good with low defect levels, they have to be near-perfect. Design for Six Sigma Statistics is a rigorous mathematical roadmap to help companies reach this goal. As the sixth book in the Six Sigma operations series, this comprehensive book goes beyond an introduction to the statistical tools and methods found in most books but contains expert case studies, equations and step by step MINTAB instruction for performing: DFSS Design of Experiments, Measuring Process Capability, Statistical Tolerancing in DFSS and DFSS Techniques within the Supply Chain for Improved Results. The aim is to help you better diagnosis and root out potential problems before your product or service is even launched.
Biographie:
McGraw-Hill authors represent the leading experts in their fields and are dedicated to improving the lives, careers, and interests of readers worldwide
Sommaire:Part I: The Design for Six Sigma Process
Chapter 1: Developing of DFSS
Chapter 2: Implementing DFSS
Part II: Defining Product Requirements
Chapter 3: Processing the Voice of the Customer
Chapter 4: Quality Function Deployment
Chapter 5: Critical to Quality Requirements
Chapter 6: Design for Manufacturability and Assembly
Part III: Making Decisions With Data
Chapter 7: Selecting Product Concepts
Chapter 8: Visualizing Data
Chapter 9: Estimating Population Parameters
Chapter 10: Selecting Distribution Models
Chapter 11: Fitting Models to Data
Chapter 12: Tests for Changes in Variation
Chapter 13: Tests for Changes in Average
Chapter 14: Tests for Changes in Proportion
Chapter 15: Making Robust Decisions
Part IV: Controlling New Product Quality
Chapter 16: Designing Efficient Experiments in Five Minutes
Chapter 17: Two-Level Experiments
Chapter 18: Robust Experiments
Part V: Predicting New Product Quality
Chapter 19: Tolerance Design
Chapter 20: Measures of Process Capability
Chapter 21: Tolerance Analysis for Mechanical Engineers
Chapter 22: Tolerance Analysis for Electrical Engineers
Chapter 23: DFSS Scorecard
Part VI: Controlling New Product Quality
Chapter 24: Stabilizing Processes
Chapter 25: Measurement Systems Analysis
Chapter 26: Statistical Process Control
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