IMPLEMENTING SIX SIGMA

Transcription

1 IMPLEMENTING SIX SIGMA Smarter Solutions Using Statistical Methods Second Edition FORREST W. BREYFOGLE III Founder and President Smarter Solutions, Inc. Austin, Texas JOHN WILEY & SONS, INC.

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3 IMPLEMENTING SIX SIGMA

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5 IMPLEMENTING SIX SIGMA Smarter Solutions Using Statistical Methods Second Edition FORREST W. BREYFOGLE III Founder and President Smarter Solutions, Inc. Austin, Texas JOHN WILEY & SONS, INC.

6 This book is printed on acid-free paper. Copyright 2003 by Forrest W. Breyfogle III. All rights reserved. Published by John Wiley & Sons, Inc., Hoboken, New Jersey Published simultaneously in Canada. No part of this publication may be reproduced, stored in a retrieval system or transmitted in any form or by any means, electronic, mechanical, photocopying, recording, scanning or otherwise, except as permitted under Section 107 or 108 of the 1976 United States Copyright Act, without either the prior written permission of the Publisher, or authorization through payment of the appropriate per-copy fee to the Copyright Clearance Center, Inc., 222 Rosewood Drive, Danvers, MA 01923, (978) , fax (978) , or on the web at Requests to the Publisher for permission should be addressed to the Permissions Department, John Wiley & Sons, Inc., 111 River Street, Hoboken, NJ 07030, (201) , fax (201) , permcoordinator@wiley.com. Limit of Liability/ Disclaimer of Warranty: While the publisher and author have used their best efforts in preparing this book, they make no representations or warranties with respect to the accuracy or completeness of the contents of this book and specifically disclaim any implied warranties of merchantability or fitness for a particular purpose. No warranty may be created or extended by sales representatives or written sales materials. The advice and strategies contained herein may not be suitable for your situation. You should consult with a professional where appropriate. Neither the publisher nor author shall be liable for any loss of profit or any other commercial damages, including but not limited to special, incidental, consequential, or other damages. For general information on our other products and services or for technical support, please contact our Customer Care Department within the United States at (800) , outside the United States at (317) or fax (316) Wiley also publishes its books in a variety of electronic formats. Some content that appears in print may not be available in electronic books. For more information about Wiley products, visit our web site at Library of Congress Cataloging-in-Publication Data: Breyfogle, Forrest W., 1946 Implementing Six Sigma: smarter solutions using statistical methods/ Forrest W. Breyfogle III. 2nd ed. p. cm. Includes bibliographical references and index. ISBN (cloth) 1. Quality control Statistical methods. 2. Production management Statistical methods. I. Title. TS156.B dc Printed in the United States of America

7 To a great team at Smarter Solutions, Inc., which is helping organizations improve their customer satisfaction and bottom line!

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9 CONTENTS PREFACE xxxi PART I S 4 /IEE DEPLOYMENT AND DEFINE PHASE FROM DMAIC 1 1 Six Sigma Overview and S 4 /IEE Implementaton Background of Six Sigma, General Electric s Experiences with Six Sigma, Additional Experiences with Six Sigma, What Is Six Sigma and S 4 /IEE?, The Six Sigma Metric, Traditional Approach to the Deployment of Statistical Methods, Six Sigma Benchmarking Study, S 4 /IEE Business Strategy Implementation, Six Sigma as an S 4 /IEE Business Strategy, Creating an S 4 /IEE Business Strategy with Roles and Responsibilities, Integration of Six Sigma with Lean, Day-to-Day Business Management Using S 4 /IEE, S 4 /IEE Project Initiation and Execution Roadmap, Project Benefit Analysis, Examples in This Book That Describe the Benefits and Strategies of S 4 /IEE, Effective Six Sigma Training and Implementation, Computer Software, 43 vii

10 viii CONTENTS 1.18 Selling the Benefits of Six Sigma, S 4 /IEE Difference, S 4 /IEE Assessment, Exercises, 51 2 Voice of the Customer and the S 4 /IEE Define Phase Voice of the Customer, A Survey Methodology to Identify Customer Needs, Goal Setting and Measurements, Scorecard, Problem Solving and Decision Making, Answering the Right Question, S 4 /IEE DMAIC Define Phase Execution, S 4 /IEE Assessment, Exercises, 64 PART II S 4 /IEE MEASURE PHASE FROM DMAIC 65 3 Measurements and the S 4 /IEE Measure Phase Voice of the Customer, Variability and Process Improvements, Common Causes versus Special Causes and Chronic versus Sporadic Problems, Example 3.1: Reacting to Data, Sampling, Simple Graphic Presentations, Example 3.2: Histogram and Dot Plot, Sample Statistics (Mean, Range, Standard Deviation, and Median), Attribute versus Continuous Data Response, Visual Inspections, Hypothesis Testing and the Interpretation of Analysis of Variance Computer Outputs, Experimentation Traps, Example 3.3: Experimentation Trap Measurement Error and Other Sources of Variability, Example 3.4: Experimentation Trap Lack of Randomization, Example 3.5: Experimentation Trap Confused Effects, Example 3.6: Experimentation Trap Independently Designing and Conducting an Experiment, Some Sampling Considerations, DMAIC Measure Phase, 96

11 CONTENTS ix 3.19 S 4 /IEE Assessment, Exercises, 99 4 Process Flowcharting/Process Mapping S 4 /IEE Application Examples: Flowchart, Description, Defining a Process and Determining Key Process Input/ Output Variables, Example 4.1: Defining a Development Process, Focusing Efforts after Process Documentation, S 4 /IEE Assessment, Exercises, Basic Tools Descriptive Statistics, Run Chart (Time Series Plot), Control Chart, Probability Plot, Check Sheets, Pareto Chart, Benchmarking, Brainstorming, Nominal Group Technique (NGT), Force-Field Analysis, Cause-and-Effect Diagram, Affinity Diagram, Interrelationship Digraph (ID), Tree Diagram, Why-Why Diagram, Matrix Diagram and Prioritization Matrices, Process Decision Program Chart (PDPC), Activity Network Diagram or Arrow Diagram, Scatter Diagram (Plot of Two Variables), Example 5.1: Improving a Process That Has Defects, Example 5.2: Reducing the Total Cycle Time of a Process, Example 5.3: Improving a Service Process, Exercises, Probability Description, Multiple Events, Multiple-Event Relationships, 143

12 x CONTENTS 6.4 Bayes Theorem, S 4 /IEE Assessment, Exercises, Overview of Distributions and Statistical Processes An Overview of the Application of Distributions, Normal Distribution, Example 7.1: Normal Distribution, Binomial Distribution, Example 7.2: Binomial Distribution Number of Combinations and Rolls of Die, Example 7.3: Binomial Probability of Failure, Hypergeometric Distribution, Poisson Distribution, Example 7.4: Poisson Distribution, Exponential Distribution, Example 7.5: Exponential Distribution, Weibull Distribution, Example 7.6: Weibull Distribution, Lognormal Distribution, Tabulated Probability Distribution: Chi-Square Distribution, Tabulated Probability Distribution: t Distribution, Tabulated Probability Distribution: F Distribution, Hazard Rate, Nonhomogeneous Poisson Process (NHPP), Homogeneous Poisson Process (HPP), Applications for Various Types of Distributions and Processes, S 4 /IEE Assessment, Exercises, Probability and Hazard Plotting S 4 /IEE Application Examples: Probability Plotting, Description, Probability Plotting, Example 8.1: PDF, CDF, and Then a Probability Plot, Probability Plot Positions and Interpretation of Plots, Hazard Plots, Example 8.2: Hazard Plotting, Summarizing the Creation of Probability and Hazard Plots, 183

13 CONTENTS xi 8.9 Percentage of Population Statement Considerations, S 4 /IEE Assessment, Exercises, Six Sigma Measurements Converting Defect Rates (DPMO or PPM) to Sigma Quality Level Units, Six Sigma Relationships, Process Cycle Time, Yield, Example 9.1: Yield, Z Variable Equivalent, Example 9.2: Z Variable Equivalent, Defects per Million Opportunities (DPMO), Example 9.3: Defects per Million Opportunities (DPMO), Rolled Throughput Yield, Example 9.4: Rolled Throughput Yield, Example 9.5: Rolled Throughput Yield, Yield Calculation, Example 9.6: Yield Calculation, Example 9.7: Normal Transformation (Z Value), Normalized Yield and Z Value for Benchmarking, Example 9.8: Normalized Yield and Z Value for Benchmarking, Six Sigma Assumptions, S 4 /IEE Assessment, Exercises, Basic Control Charts S 4 /IEE Application Examples: Control Charts, Satellite-Level View of the Organization, A 30,000-Foot-Level View of Operational and Project Metrics, AQL (Acceptable Quality Level) Sampling Can Be Deceptive, Example 10.1: Acceptable Quality Level, Monitoring Processes, Rational Sampling and Rational Subgrouping, Statistical Process Control Charts, Interpretation of Control Chart Patterns, x and R and x and s Charts: Mean and Variability Measurements, Example 10.2: x and R Chart, 223

14 xii CONTENTS XmR Charts: Individual Measurements, Example 10.3: XmR Charts, x and r versus XmR Charts, Attribute Control Charts, p Chart: Fraction Nonconforming Measurements, Example 10.4: p Chart, np Chart: Number of Nonconforming Items, c Chart: Number of Nonconformities, u Chart: Nonconformities per Unit, Median Charts, Example 10.5: Alternatives to p-chart, np-chart, c-chart, and u-chart Analyses, Charts for Rare Events, Example 10.6: Charts for Rare Events, Discussion of Process Control Charting at the Satellite Level and 30,000-Foot Level, Control Charts at the 30,000-Foot Level: Attribute Response, XmR Chart of Subgroup Means and Standard Deviation: An Alternative to Traditional x and R Charting, Notes on the Shewhart Control Chart, S 4 /IEE Assessment, Exercises, Process Capability and Process Performance Metrics S 4 /IEE Application Examples: Process Capability/ Performance Metrics, Definitions, Misunderstandings, Confusion: Short-Term versus Long-Term Variability, Calculating Standard Deviation, Process Capability Indices: C p and C pk, Process Capability/Performance Indices: P p and P pk, Process Capability and the Z Distribution, Capability Ratios, C pm Index, Example 11.1: Process Capability/ Performance Indices, Example 11.2: Process Capability/ Performance Indices Study, Example 11.3: Process Capability/ Performance Index Needs, Process Capability Confidence Interval, 282

15 CONTENTS xiii Example 11.4: Confidence Interval for Process Capability, Process Capability/Performance for Attribute Data, Describing a Predictable Process Output When No Specification Exists, Example 11.5: Describing a Predictable Process Output When No Specification Exists, Process Capability/Performance Metrics from XmR Chart of Subgroup Means and Standard Deviation, Process Capability/Performance Metric for Nonnormal Distribution, Example 11.6: Process Capability/Performance Metric for Nonnormal Distributions: Box-Cox Transformation, Implementation Comments, The S 4 /IEE Difference, S 4 /IEE Assessment, Exercises, Measurement Systems Analysis MSA Philosophy, Variability Sources in a 30,000-Foot-Level Metric, S 4 /IEE Application Examples: MSA, Terminology, Gage R&R Considerations, Gage R&R Relationships, Additional Ways to Express Gage R&R Relationships, Preparation for a Measurement System Study, Example 12.1: Gage R&R, Linearity, Example 12.2: Linearity, Attribute Gage Study, Example 12.3: Attribute Gage Study, Gage Study of Destructive Testing, Example 12.4: Gage Study of Destructive Testing, A 5-Step Measurement Improvement Process, Example 12.5: A 5-Step Measurement Improvement Process, S 4 /IEE Assessment, Exercises, Cause-and-Effect Matrix and Quality Function Deployment S 4 /IEE Application Examples: Cause-and-Effect Matrix, 348