Process Quality Control

Dean V. Neubauer, Edward G. Schilling, Ellis R. Ott

Description

Ellis Ott taught generations of quality practitioners to be explorers of the truth through the collection and graphical portrayal of data. From a simple plea to "plot the data" to devising a graphical analytical tool called the analysis of means (ANOM), Ott demonstrated that process knowledge is to be gained by seeking the information contained within the data.In this newest version of Ott's classic text, the authors have strived to continue down the path that he created for others to follow. Additions to this revised edition include: the use of dot plots as an alternative to histograms; digidot plots; adding events to charts; emphasis on the role that acceptance control charts play in controlling risks and the computation of average run length (ARL); a new chapter devoted to process capability, process performance, and process improvement, including the use of confidence intervals for process capability metrics; narrow-limit gauging as another means of assessing the capability of a process; Six Sigma methodology; design resolution; scatter plot matrices as applied to datasets of higher dimensions; and a new chapter on measurement studies.

Sujets

• Business
• Qualité, hygiène, sécurité, environnement
• Techniques
• Automatisation et Contrôle
• Contrôle des processus
• Automatisation
• Automate
• SPC
• Six Sigma
• Engineering
• Technology
• Seis Sigma
• Sciences et techniques
• Quality Control

Informations

• Publié par: ASQ Quality Press
• Date de parution: 08 février 2005
• Nombre de lectures: 1
• EAN13: 9781953079855
• Langue: English
• Poids de l'ouvrage: 2 Mo

Extrait

Process Quality Control
Troubleshooting and
Interpretation of Data
Fourth EditionAlso available from ASQ Quality Press:
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Business Excellence
Charles G. Cobb
Applied Data Analysis for Process Improvement: A Practical Guide to
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The Desk Reference of Statistical Quality Methods
Mark L. Crossley
Root Cause Analysis: Simplified Tools and Techniques
Bjørn Andersen and Tom Fagerhaug
Applied Statistics for the Six Sigma Green Belt
Bhisham C. Gupta and H. Fred Walker
Statistical Quality Control Using Excel, Second Edition
Steven M. Zimmerman and Marjorie L. Icenogle
Office Kaizen: Transforming Office Operations into a Strategic
Competitive Advantage
William Lareau
Improving Performance Through Statistical Thinking
ASQ Statistics Division
Statistical Engineering: An Algorithm for Reducing Variation in
Manufacturing Processes
Stefan H. Steiner and R. Jock MacKay
To request a complimentary catalog of ASQ Quality Press publications,
call 800-248-1946, or visit our Web site at http://qualitypress.asq.org.Process Quality Control
Troubleshooting and
Interpretation of Data
Fourth Edition
Ellis R. Ott
Edward G. Schilling
Dean V. Neubauer
ASQ Quality Press
Milwaukee, WisconsinAmerican Society for Quality, Quality Press, Milwaukee 53203
© 2005 by ASQ
All rights reserved. Published 2005
Printed in the United States of America
12 11 10 09 08 07 06 05 54321
Library of Congress Cataloging-in-Publication Data
Ott, Ellis R. (Ellis Raymond), 1906–
Process quality control : troubleshooting and interpretation of data / Ellis R. Ott,
Edward G. Schilling, Dean V. Neubauer.—4th ed.
p. cm.
Includes bibliographical references and index.
ISBN 0-87389-655-6 (hard cover, case binding : alk. paper)
1. Process control—Statistical methods. 2. Quality control—Statistical methods.
I. Schilling, Edward G., 1931– II. Neubauer, Dean V. III. Title.
TS156.O86 2005
658.5'62—dc22 2005010988
ISBN 0-87389-655-6
No part of this book may be reproduced in any form or by any means, electronic, mechanical,
photocopying, recording, or otherwise, without the prior written permission of the publisher.
Publisher: William A. Tony
Acquisitions Editor: Annemieke Hytinen
Project Editor: Paul O’Mara
Production Administrator: Randall Benson
ASQ Mission: The American Society for Quality advances individual, organizational, and
community excellence worldwide through learning, quality improvement, and knowledge exchange.
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videotapes, audiotapes, and software are available at quantity discounts with bulk purchases for
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Printed on acid-free paperTo Virginia, Jean, and Kimberly with love and appreciation.Table of Contents
List of Figures and Tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . xiii
Case Histories . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xxvii
Preface to the Fourth Edition . . . . . . . . . . . . . . . . . . . . . . . . . . xxixto the Third Edition . . . . . . . . . . . . . . . . . . . . . . . . . . . xxxiii
Preface to the Second Edition xxxviito the First Edition xxxix
Part 1 Basics of Interpretation of Data
Chapter 1 Variables Data:An Introduction . . . . . . . . . . . . . . . . . 3
1.1 Introduction:An Experience with Data . . . . . . . . . . . . . . . 3
1.2 Variability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
1.3 Organizing Data . . . . . . . . . . . . . . . . . . . . . . . . . . . 8
1.4 Grouping Data When n Is Large . . . . . . . . . . . . . . . . . . . 9
1.5 The Arithmetic Average or Mean—Central Value . . . . . . . . . 12
1.6 Measures of Variation . . . . . . . . . . . . . . . . . . . . . . . . 13
1.7 Normal Probability Plots . . . . . . . . . . . . . . . . . . . . . . 18
1.8 Predictions Regarding Sampling Variation: The Normal Curve . . 20
1.9 Series of Small Samples from a Production Process . . . . . . . . 28
–
ˆ1.10 Change in Sample Size: Predictions about X ands . . . . . . . . . 29
1.11 How Large a Sample Is Needed to Estimate a Process Average? . . 31
ˆ1.12 Sampling and a Second Method of Computings . . . . . . . . . . 32
1.13 Some Important Remarks about the Two Estimates . . . . . . . . 35
1.14 Stem-and-Leaf . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37
1.15 Box Plots . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38
1.16 Dot Plot 41
viiviii Table of Contents
1.17 Tolerance Intervals for Populations . . . . . . . . . . . . . . . . . 42
1.18 A Note on Notation . . . . . . . . . . . . . . . . . . . . . . . . . 44
1.19 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46
1.20 Practice Exercises . . . . . . . . . . . . . . . . . . . . . . . . . . 47
Chapter 2 Ideas from Time Sequences of Observations . . . . . . . . . . . 51
2.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51
2.2 Data from a Scientific or Production Process . . . . . . . . . . . . 54
2.3 Signals and Risks 55
2.4 Run Criteria 56
2.5 Shewhart Control Charts for Variables . . . . . . . . . . . . . . . 62
–
2.6 Probabilities Associated with an X Control Chart:
Operating-Characteristic Curves . . . . . . . . . . . . . . . . . . . 71
2.7 Control Charts for Trends . . . . . . . . . . . . . . . . . . . . . . 88
2.8 Digidot Plot 95
2.9 Practice Exercises . . . . . . . . . . . . . . . . . . . . . . . . . . 96
Chapter 3 Ideas from Outliers—Variables Data . . . . . . . . . . . . . . . 99
3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99
3.2 Other Objective Tests for Outliers . . . . . . . . . . . . . . . . . . 103
3.3 Two Suspected Outliers on the Same End of a Sample
of n (Optional) . . . . . . . . . . . . . . . . . . . . . . . . . . . . 106
3.4 Practice Exercises . . . . . . . . . . . . . . . . . . . . . . . . . . 108
Chapter 4 Variability—Estimating and Comparing . . . . . . . . . . . . . 109
4.1 Introduction 109
4.2 Statistical Efficiency and Bias in Variability Estimates . . . . . . . 109
24.3 Estimating s and s from Data: One Sample of Size n . . . . . . 111
4.4 Data from n Observations Consisting of k Subsets of n = r:g
Two Procedures . . . . . . . . . . . . . . . . . . . . . . . . . . . 112
4.5 Comparing Variabilities of Two Populations . . . . . . . . . . . . 114
4.6 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 123
4.7 Practice Exercises . . . . . . . . . . . . . . . . . . . . . . . . . . 125
Chapter 5 Attributes or Go/No-Go Data . . . . . . . . . . . . . . . . . . . 127
5.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 127
5.2 Three Important Problems . . . . . . . . . . . . . . . . . . . . . . 127
5.3 On How to Sample 138
5.4 Attributes Data That Approximate a Poisson Distribution . . . . . 139
5.5 Notes on Control Charts . . . . . . . . . . . . . . . . . . . . . . . 146
5.6 Practice Exercises . . . . . . . . . . . . . . . . . . . . . . . . . . 149
Part 2 Statistical Process Control
Chapter 6 Sampling and Narrow-Limit Gauging . . . . . . . . . . . . . . 153
6.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 153Table of Contents ix
6.2 Scientific Sampling Plans . . . . . . . . . . . . . . . . . . . . . . 154
6.3 A Simple Probability . . . . . . . . . . . . . . . . . . . . . . . . 155
6.4 Operating-Characteristic Curves of a Single Sampling Plan . . . . 156
6.5 But Is It a Good Plan? 157
6.6 Average Outgoing Quality (AOQ) and Its Maximum
Limit (AOQL) . . . . . . . . . . . . . . . . . . . . . . . . . . . . 158
6.7 Computing the Average Outgoing Quality (AOQ) of Lots from
a Process Producing P Percent Defective . . . . . . . . . . . . . . 160
6.8 Other Important Concepts Associated with Sampling Plans . . . . 161
6.9 Risks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 162
6.10 Tabulated Sampling Plans . . . . . . . . . . . . . . . . . . . . . . 162
6.11 Feedback of Information . . . . . . . . . . . . . . . . . . . . . . . 163
6.12 Where Should Feedback Begin? . . . . . . . . . . . . . . . . . . . 166
6.13 Narrow-Limit Gauging 180
6.14 Outline of an NL-Gauging Plan 181
6.15 Selection of a Simple NL-Gauging Sampling Plan . . . . . . . . . 182
6.16 OC Curves of NL-Gauge Plans 187
6.17 Hazards . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 191
6.18 Selection of an NL-Gauging Plan . . . . . . . . . . . . . . . . . . 192
6.19 Optimal Narrow-Limit Plans . . . . . . . . . . . . . . . . . . . . 192
6.20 Practice Exercises . . . . . . . . . . . . . . . . . . . . . . . . . . 193
Chapter 7 Principles and Applications of Control Charts . . . . . . . . . . 195
7.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 195
7.2 Key Aspects of Process Quality Control . . . . . . . . . . . . . . 196
7.3 Process Control . . . . . . . . . . . . . . . . . . . . . . . . . . . 197
7.4 Uses of Control Charts . . . . . . . . . . . . . . . . . . . . . . . 199
7.5 Rational Subgroups . . . . . . . . . . . . . . . . . . . . . . . . . 199
7.6 Special Control Charts . . . . . . . . . . . . . . . . . . . . . . . . 200
7.7 Median Chart . . . . . . . . . . . . . . . . . . . . . . . . . . . . 200
7.8 Standard Deviation Chart . . . . . . . . . . . . . . . . . . . . . . 203
7.9 Acceptance Control Chart 204
7.10 Modified Limits . . . . . . . . . . . . . . . . . . . . . . . 211
7.11 Arithmetic and Exponentially Weighted Moving Average Charts . . 212
7.12 Cumulative Sum Charts 216
7.13 Precontrol . . . . . . . . . .