The Certified Six Sigma Green Belt Handbook, Second Edition

640 Pages·2015·13.932 MB·English

by  Munro, Roderick A., Ramu, Govindarajan, Zrymiak, Daniel J

The Certified Six Sigma
Green Belt Handbook
Second Edition
Roderick A. Munro, Govindarajan Ramu,
and Daniel J. Zrymiak
ASQ Quality Press
Milwaukee, Wisconsin
American Society for Quality, Quality Press, Milwaukee 53203
© 2015 by ASQ
All rights reserved. Published 2015
Printed in the United States of America
21 20 19 18 17 16 15 5 4 3 2 1
Library of Congress Cataloging-in-Publication Data
Munro, Roderick A.
The certified six sigma green belt handbook / Roderick A. Munro, Govindarajan Ramu,
and Daniel J. Zrymiak.—Second edition.
pages cm
Revised edition of: The certified six sigma green belt handbook / Roderick A. Munro . . .
[et al.]. c2008.
Includes bibliographical references and index.
ISBN 978-0-87389-891-1 (hard cover : alk. paper)
1. Six sigma (Quality control standard)—Handbooks, manuals, etc. 2. Production
management—Handbooks, manuals, etc. 3. Quality control—Statistical methods—
Handbooks, manuals, etc. I. Ramu, Govindarajan. II. Zrymiak, Daniel J. III. Title.

TS156.C4235 2015
658.5—dc23 2014046292
ISBN 978-0-87389-891-1
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: Lynelle Korte
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Managing Editor: Paul Daniel O’Mara
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ASQ Mission: The American Society for Quality advances individual, organizational, and
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Printed on acid-free paper
Michael J. cleary
Founder of PQ Systems, Inc.
Born June 3, 1939
Died suddenly on September 10, 2014
Dr. Cleary, a noted authority in the field of quality management and a charter
member of the Education Division of the American Society for Quality Control
(now ASQ), founded PQ Systems, Inc., in 1984, with headquarters in Dayton, Ohio,
later opening PQ Systems Europe Ltd., with sales in continental Europe and the
Middle East, and PQ Systems Pty Ltd. in Frankston, Australia, serving the Pacific
Rim. The company’s products help organizations demonstrate proof of the q uality
of their products and services using statistical methods and problem-solving tools.
PQ Systems was named among the top 25 best places to work in Dayton in 2014.
Cleary played a principal role in developing the Transformation of Ameri-
can Industry national training project, as well as the Total Quality Transforma-
tion training system. He served on the planning committee for the U.S.–Japanese
Business Conference in Tokyo, and presented papers on statistical process control
and the applications of quality management principles to a variety of audiences in
Korea, China, France, Great Britain, Australia, Singapore, and Japan. He was the
author of A Data Analysis Handbook: Using the SPSS System, as well as coeditor of
Practical Tools for Continuous Improvement, volumes 1 and 2.
As a professor of management science at Wright State University from 1971–
1996, Cleary was awarded the Business College Associates Alumni Teaching
Award. His 25-year professorship in management science enabled Cleary to con-
duct extensive research and garner valuable experience in expanding quality
management methods. He was a leader in bringing quality management into the
curriculum of the College of Business, and published articles and papers on issues
vi Dedication
related to quality management, statistical applications, and decision sciences in a
variety of academic and professional journals.
Cleary is survived by his wife of 50 years, Barbara A. Cleary, PhD, and their four
sons: Sean (Katherine St. John), Timothy (Laura Jackson), Matthew (Liz Hansen),
and Dennis (Karina Johansen), grandsons Michael Wyatt Cleary, Harmon Hemp-
stead Cleary, Daniel St. John Cleary, and Victor Thomas Cleary, granddaugh-
ter Johanna Sol Cleary, sister Joan Buckman, brother-in-law John Rathman, and
nieces and nephews.
list of Figures and Tables
Table 1.1 Some approaches to quality over the years. ........................... 5
Figure 1.1 Example of a process flowchart. ..................................... 16
Figure 1.2 Relationships between systems, processes, subprocesses, and steps. ..... 17
Figure 1.3 A feedback loop. .................................................. 17
Figure 1.4 Categories of inputs to a process step. ................................ 18
Figure 1.5 Traditional quality cost curves. ...................................... 24
Figure 1.6 Modern quality cost curves. ........................................ 25
Table 1.2 Risk analysis table. ................................................ 27
Figure 1.7 A format for SWOT analysis. ........................................ 27
Figure 2.1 TPS house. ........................................................ 32
Figure 2.2 7S adaptation (Hirano). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36
Figure 2.3 A sea of inventory often hides unresolved problems. ................... 42
Figure 2.4 C-shaped manufacturing cell. ....................................... 43
Figure 2.5 Common symbols used in value stream mapping. ..................... 46
Figure 2.6 Value stream map example. ......................................... 47
Table 3.1 Design objectives and outputs traceability matrix. ..................... 54
Figure 3.1 Simple risk matrix. ................................................ 57
Figure 3.2 Sample DFMEA headers. ........................................... 59
Figure 3.3 Sample PFMEA headers. ........................................... 60
Figure 3.4 FMEA flowchart. .................................................. 61
Figure 3.5 FMEA flowchart in line with common FMEA form. .................... 62
Table 3.2 Steps in performing a design or process FMEA. ....................... 63
Table 3.3 Possible severity evaluation criteria. ................................. 65
Table 3.4 Possible occurrence evaluation criteria. ............................... 65
Table 3.5 Possible detection evaluation criteria. ................................ 65
Figure 3.6 Example of RPN calculations. ....................................... 66
Figure 3.7 Example of FMEA reporting and RPN chart. .......................... 68
Figure 3.8 A typical risk action plan Gantt chart. ................................ 68
Figure 3.9 A typical top-level management review report for FMEA progress. ...... 69
Figure 3.10 An example of a partially filled-in FMEA. ............................ 70
Figure 3.11 This example of a tree diagram is a fault tree (used to study defects
and failures). ..................................................... 71
xvi
List of Figures and Tables xvii
Figure 3.12 Common types of FMEA. ........................................... 71
Figure 4.1 Process diagram/model. ........................................... 77
Table 4.1 Tips for benchmarking. ............................................ 80
Figure 4.2 Basic SIPOC diagram. .............................................. 82
Figure 5.1 Example of a QFD matrix for an animal trap. .......................... 89
Figure 5.2 Map to the entries of the QFD matrix illustrated in Figure 5.1. ........... 90
Figure 5.3 Sequence of QFD matrices for product, part, and process planning. ...... 90
Figure 5.4 Example of a completed QFD matrix. ................................ 92
Figure 5.5 QFD stage flow and relationships. ................................... 93
Figure 5.6 QFD input–output requirements matrix. ............................. 93
Table 5.1 QFD value characteristics. .......................................... 94
Figure 6.1 Risk assessment assignment matrix. ................................. 100
Figure 7.1 Example of an activity network diagram. ............................. 103
Figure 7.2 Example of an affinity diagram. ..................................... 104
Figure 7.3 Example of a cause-and-effect diagram. .............................. 108
Figure 7.4 Example of a check sheet. ........................................... 109
Figure 7.5 High-level flowchart for an order-filling process. ...................... 110
Figure 7.6 Detailed flowchart for the order-filling process. ....................... 111
Figure 7.7 Example of force-field analysis. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 112
Figure 7.8 Gantt chart example. ............................................... 112
Figure 7.9 Graphical representation of question responses. ....................... 114
Figure 7.10 Example interrelationship digraph. .................................. 116
Figure 7.11 Example matrix diagram. ........................................... 117
Figure 7.12 PDCA cycle. ...................................................... 118
Figure 7.13 Prioritization matrix example. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119
Figure 7.14 Example process decision program chart (PDPC). ..................... 121
Figure 7.15 PERT/critical path chart example. ................................... 122
Figure 7.16 SIPOC diagram with requirements capture. .......................... 124
Figure 7.17 This example of a tree diagram is a fault tree (used to study defects
and failures). ..................................................... 125
Table 9.1 Common negative team dynamics and potential countermeasures. ...... 136
Figure 9.1 Typical large Six Sigma organization. ................................ 140
Figure 9.2 Typical small Six Sigma organization. ................................ 141
Table 9.2 Typical Six Sigma roles. ............................................ 141
Figure 9.3 Multivoting ranked approach example. .............................. 151
Figure 9.4 Multivoting weighted approach example. ............................. 152
Figure 10.1 Symbols commonly used in flowcharts and process maps. .............. 155
Figure 10.2 Basic flowchart for warranty product replacement. .................... 156
Figure 10.3 Cross-functional or swim lane flowchart. ............................. 157
Figure 10.4 Empty cause-and-effect diagram. .................................... 161
xviii List of Figures and Tables
Figure 10.5 Cause-and-effect diagram after a few steps of a brainstorming session. ... 161
Figure 10.6 Pareto chart of final assembly inspection defect codes. ................. 163
Figure 10.7 Pareto chart of final assembly inspection defect codes (weighted). ....... 164
Figure 10.8 Example of a Pareto chart of a too-detailed defect summary. ............ 165
Figure 10.9 Example of a measles chart (pictorial check sheet). ..................... 166
Figure 10.10 Relationship matrix. ............................................... 167
Figure 11.1 Venn diagram. .................................................... 169
Figure 11.2 Mutually exclusive events. .......................................... 171
Figure 11.3 Various populations and sampling distributions of the mean for
selected sample sizes. .............................................. 175
Table 11.1 Descriptive versus analytical statistics. ............................... 177
Table 11.2 Sample versus population notations. ................................. 178
Table 12.1 Formula, mean, and variance of certain distributions. ................... 179
Figure 12.1 Binomial distribution. ............................................. 180
Figure 12.2 Binomial distribution using Microsoft Excel. .......................... 181
Figure 12.3 Poisson distribution. ............................................... 183
Figure 12.4 Poisson distribution using Microsoft Excel. ........................... 184
Figure 12.5 Normal distribution curve. ......................................... 185
Figure 12.6 Normal probability density function and cumulative density
function. ......................................................... 185
Figure 12.7 Chi-square distribution example. .................................... 188
Figure 12.8 F-distribution with varying degrees of freedom. . . . . . . . . . . . . . . . . . . . . . . . 191
Table 13.1 Measurement scales. ............................................... 193
Table 13.2 Coding–decoding. ................................................. 196
Figure 13.1 Example of a check sheet. ........................................... 197
Figure 13.2 Example of a data set as illustrated by a frequency distribution,
individual plot, histogram, and probability plot. ....................... 198
Figure 13.3 Cumulative frequency distribution in table and graph form. ............ 200
Table 13.3 Comparison of various graphical methods. ........................... 201
Figure 13.4 Histogram and stem-and-leaf plot comparison. ........................ 204
Figure 13.5 Box plot. .......................................................... 205
Figure 13.6 Example box plot. ................................................. 205
Figure 13.7 Box plots versus dot plots. .......................................... 206
Table 13.4 Example of yield data from three periods. ............................ 206
Figure 13.8 Box plot by period. ................................................ 207
Figure 13.9 Run chart analysis (using statistical software). ........................ 208
Figure 13.10 Scatter diagrams. .................................................. 209
Table 13.5 Mold process data. ................................................. 210
Figure 13.11 Examples of scatter diagrams (variables versus effects). ................ 210
Figure 13.12 Correlation between variables and effects (using statistical software). .... 211
Figure 13.13 Example scatter plots—exercise versus weight loss. .................... 212
List of Figures and Tables xix
Figure 13.14 Normal probability plot. ............................................ 214
Figure 13.15 Example of Weibull plot. ........................................... 216
Figure 14.1 Gage repeatability. ................................................. 218
Figure 14.2 Gage reproducibility. .............................................. 219
Figure 14.3 Gage R&R data collection sheet. ..................................... 220
Figure 14.4 Gage R&R data collection sheet with data entered and calculations
completed. ........................................................ 222
Figure 14.5 Gage repeatability and reproducibility report. . . . . . . . . . . . . . . . . . . . . . . . . . 223
Figure 14.6 Gage repeatability and reproducibility report with calculations. ......... 224
Figure 14.7 Example gage repeatability and reproducibility analysis. ............... 225
Figure 14.8 GR&R report using statistical software. .............................. 226
Figure 14.9 Sources of measurement variation. .................................. 227
Figure 14.10 Observed versus actual capability. ................................... 227
Figure 14.11 GR&R sample selection. ............................................ 228
Table 14.1 GR&R random Excel sheet example. ................................. 229
Table 14.2 Measurement test data for linearity and bias. ......................... 231
Figure 14.12 Linearity and bias analysis using statistical software. .................. 232
Figure 14.13 Minitab orthogonal regression example. .............................. 233
Figure 14.14 Attribute agreement analysis using statistical software. ................ 234
Figure 15.1 Control limit versus specification limit grid. .......................... 238
–
Figure 15.2 Example of X and R control chart. ................................... 238
Figure 15.3 Process capability report for shaft machining. ......................... 243
Figure 15.4 Types of sampling for SPC data collection. ............................ 244
Figure 15.5 Process capability scenarios. ........................................ 246
Figure 15.6 Process performance indices P , P , and C . ......................... 249
p pk pm
Figure 15.7 Process performance 1.5-sigma shift. ................................. 250
Figure 15.8 Short-term versus long-term performance with 1.5-sigma shift. .......... 251
Table 16.1 Types of variation. ................................................. 255
Figure 16.1 Variation within samples. .......................................... 255
Figure 16.2 Excessive variability (part is tapered). ................................ 256
Figure 16.3 Less variability (center is thicker). ................................... 256
Figure 16.4 Variability shift over time (part is getting larger). ...................... 256
Figure 16.5 Stainless steel casting with critical inner diameter. ..................... 257
Figure 16.6 Sectional views of stainless steel casting. ............................. 258
Figure 16.7 Data collection sheet. .............................................. 259
Table 16.2 Measurement data from five parts produced during one shift. .......... 259
Figure 16.8 Graph of data from Table 16.2. ....................................... 259
Figure 16.9 Part-to-part variation (graph of data from Table 16.2). .................. 260
Table 16.3 Data from five parts produced during one shift using precision
castings. .......................................................... 260
Figure 16.10 Graph of data from Table 16.3. ....................................... 261
xx List of Figures and Tables
Figure 16.11 Graph of data from Table 16.3 with orientation measurement
numbers. ......................................................... 262
Table 16.4 Data from five parts after pressure-washing. .......................... 262
Table 16.5 Examples of dependent and independent variables. .................... 263
Figure 16.12 The four types of correlation in scatter plots. .......................... 264
Table 16.6 Data table for correlation calculation. ................................ 267
Figure 16.13 CORREL function in Excel. ......................................... 269
Table 16.7 Least squares example. ............................................. 271
Figure 16.14 Regression dialog box. ............................................. 273
Figure 16.15 Regression data analysis. ........................................... 273
Figure 16.16 Simple regression results. ........................................... 274
Figure 16.17 A schematic showing variation in y as a function of x. .................. 277
Table 17.1 Error matrix. ...................................................... 280
Figure 17.1 One-tail test: (a) right-tailed test and (b) left-tailed test. ................. 281
Figure 17.2 Two-tail test. ...................................................... 282
Figure 17.3 Power curve. ...................................................... 285
Figure 17.4 Excel’s FINV function. ............................................. 306
Figure 17.5 Setting up a one-way ANOVA in Excel. ............................... 306
Figure 17.6 The ANOVA: Single Factor dialog box. ............................... 307
Figure 17.7 Final results of one-way ANOVA in Excel. ............................ 307
Figure 17.8 Expected versus observed chart (Minitab output). ..................... 309
Figure 17.9 Excel’s CHINV function. ........................................... 311
Figure 18.1 Main effects graphs. ............................................... 324
Table 18.1 A 23 full factorial design using + and – format. ........................ 325
Table 18.2 A 23 full factorial design showing interaction columns. ................. 326
Table 18.3 Half fraction of 23 (also called a 23–1 design). ........................... 327
Table 18.4 Half fraction of 23 design with interaction columns filled in. ............ 327
Table 18.5 Latin square design. ............................................... 329
Figure 18.2 Graph of temperature and moisture content. .......................... 330
Table 18.6 A 22 full factorial completely randomized experiment with results. ...... 330
Table 18.7 A 22 full factorial completely randomized experiment with main and
interaction effects. ................................................. 331
Table 18.8 ANOVA outcomes. ................................................ 337
Figure 19.1 Comparative analysis. .............................................. 345
Figure 19.2 Cause-and-effect relational matrix. .................................. 346
Figure 19.3 Root cause tree example. ........................................... 347
Figure 20.1 Project framework. ................................................ 350
Figure 20.2 Lean Six Sigma objectives. .......................................... 350
Figure 20.3 Poka-yoke example. ................................................ 353
Figure 21.1 Average shifting, variation stable. ................................... 378
Figure 21.2 Average stable, variation changing. .................................. 379
List of Figures and Tables xxi
Figure 21.3 Average shifting, variation changing. ................................ 379
Figure 21.4 Average stable, variation stable. ..................................... 380
Figure 21.5 An operating characteristic (OC) curve. .............................. 382
–
Figure 21.6 X and R control chart example with data plotted. ...................... 383
Figure 21.7 Rational subgrouping. ............................................. 387
Figure 21.8 Rational subgrouping with randomness. ............................. 388
–
Figure 21.9 Measurement data entered in an X and R control chart. ................ 391
–
Figure 21.10 Completed X and R control chart. ................................... 392
–
Figure 21.11 Example of an X and s control chart. ................................. 393
Figure 21.12 Example of an individuals and moving range control chart. ............. 394
Figure 21.13 Example of a median control chart with associated range gage. .......... 396
Figure 21.14 Example of a p-chart. .............................................. 398
Figure 21.15 Example of an np-chart. ............................................ 400
Figure 21.16 Example of a u-chart. .............................................. 401
Figure 21.17 Example of a c-chart. ............................................... 403
Figure 21.18 One point more than 3σ from the centerline (either side) ............... 406
Figure 21.19 Nine points in a row on the same side of the centerline ................. 406
Figure 21.20 Six points in a row all increasing or decreasing. ....................... 407
Figure 21.21 Fourteen points in a row alternating up and down. .................... 407
Figure 21.22 Two out of three points more than 2σ from the centerline (same side). .... 407
Figure 21.23 Four out of five points more than 1σ from the centerline (same side). ..... 408
Figure 21.24 Fifteen points in a row within 1σ of the centerline (either side). .......... 408
Figure 21.25 Eight points in a row more than 1σ from the centerline (either side). ..... 408
Figure 21.26 Points beyond the control limits. .................................... 409
Figure 21.27 Seven points in a row on one side of the average. ...................... 409
Figure 21.28 Seven points in a row that are consistently increasing or consistently
decreasing. ....................................................... 409
Figure 21.29 Over 90 percent of plotted points are in the middle third of the
control limit region (for 25 or more subgroups). ....................... 410
Figure 21.30 Fewer than 40 percent of the plotted points are in the middle third of
the control limit region (for 25 or more subgroups). .................... 410
Figure 21.31 Obvious nonrandom patterns such as cycles. .......................... 410
Figure 22.1 A sample control plan template. ..................................... 415
Figure 22.2 An example control plan—first page. ................................ 416
Figure 22.3 An example control plan—second page. .............................. 417
Table 22.1 Process FMEA and control plan. ..................................... 420
Figure 23.1 The house of lean. ................................................. 434
Table 23.1 Lean Six Sigma tools. .............................................. 435