Design for Six Sigma Statistics

Andrew Sleeper

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Description

In today's competitive environment, companies can no longer produce goods and services that are merely good with low defect levels but they must be near-perfect. This rigorous mathematical roadmap provides sophisticated Six Sigma practitioners with the statistical tools necessary for rooting out and solving problems associated with product or service design.

Table of Contents

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