Design for Six Sigma Statistics: 59 Tools for Diagnosing and Solving Problems in DFFS Initiatives by Andrew SleeperDesign for Six Sigma Statistics: 59 Tools for Diagnosing and Solving Problems in DFFS Initiatives by Andrew Sleeper

Design for Six Sigma Statistics: 59 Tools for Diagnosing and Solving Problems in DFFS Initiatives

byAndrew Sleeper

Hardcover | December 26, 2005

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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.
Andrew Sleeper is a DFSS expert and General Manager of Successful Statistics, LLC. He has worked with product development teams for 22 years as an engineer, statistician, project manager, Six Sigma Black Belt, and consultant. Mr. Sleeper holds degrees in electrical engineering and statistics, and is a licensed Professional Engineer. A ...
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Title:Design for Six Sigma Statistics: 59 Tools for Diagnosing and Solving Problems in DFFS InitiativesFormat:HardcoverDimensions:854 pages, 9.1 × 6.5 × 2.6 inPublished:December 26, 2005Publisher:McGraw-Hill EducationLanguage:English

The following ISBNs are associated with this title:

ISBN - 10:0071451625

ISBN - 13:9780071451628

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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