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### Summary

### Summary

A systemic approach to continuous process improvement

Process improvement is rapidly becoming one of the most significantfactors in achieving organizational success. Nearly every aspect ofan organization can gain from process improvement andinnovation-leadership and management, visioning and planning,research and development, marketing and sales, manufacturing anddistribution. Emphasizing manufacturing process improvement butcovering the human side as well, Process Improvement in theElectronics Industry, Second Edition describes a systemic approachto continuous process improvement.

This book is based on the authors' experience in development andimplementation of a comprehensive system of continuous processimprovement and innovation at AMD. The Second Edition adds valuablenew insights and information on developments since the publicationof the highly successful previous edition. Written to serve equallywell as a comprehensive guide for engineers and technicians inprocess management, and as a reference for managers in industry andgraduate students, the book explains how to develop and implementsystems for continuous process improvement in all areas of anorganization, including:

* The concepts of process improvement, process management, andsystems thinking

* Probability and statistics basics

* How to control, measure, and report on high-qualityprocesses

* Zero defects and the six sigma methodology

* On-line and off-line design of experiments

* Managing sampling systems in a low ppm environment

Including numerous case studies and suggestions for implementing aprocess control program based on the actual experiences ofmanufacturers and suppliers, Process Improvement in the ElectronicsIndustry, Second Edition remains a compellingly useful referencefor anyone charged with or interested in achieving greaterefficiency in industry, manufacturing, leadership, and other areas.

### Author Notes

Yefim Fasser, PhD, is Director of Systems and Statistical Engineering at Advanced Micro Devices, Inc.

Donald Brettner is Group Vice President at Advanced Micro Devices, Inc.

### Table of Contents

Preface | p. xiii |

Acknowledgments | p. xv |

Part I The Human Side of Process Improvement | p. 1 |

1 The Concepts of Process Improvement | p. 3 |

1.1 Process Thinking | p. 4 |

1.2 The Typology of Improvement | p. 5 |

1.3 Creating Core Technological Capabilities | p. 10 |

References | p. 19 |

2 Improving the Management Process | p. 21 |

2.1 Seeing Management as a Discipline | p. 23 |

2.2 The Process of Visioning and Goal Setting | p. 26 |

2.3 The Concept and Application of Situational Leadership | p. 33 |

2.4 The Global Team Leader | p. 38 |

2.5 Managing the Process of Changing Mental Models | p. 39 |

References | p. 44 |

3 Systems and Systems Thinking | p. 47 |

3.1 What is a System? | p. 48 |

3.2 Analytical and Systems Thinking | p. 49 |

3.3 The Concept of Feedback | p. 52 |

3.4 A Systems View of an Organization | p. 59 |

3.5 Tomorrow's Organization | p. 64 |

References | p. 67 |

4 Creativity and Innovation | p. 69 |

4.1 Creating an Innovative Environment | p. 69 |

4.2 The Continual Process of Innovation | p. 72 |

4.3 Logical or Creative Problem Solving | p. 75 |

4.4 The Creative Problem Solving Process | p. 77 |

4.5 Overcoming the Barriers to Creativity | p. 80 |

4.6 How Innovative is Your Organization? | p. 81 |

References | p. 82 |

5 Some Basic Concepts of Variation | p. 85 |

5.1 Understanding the Major Principles of the Theory of Variation | p. 85 |

5.2 The Peculiarities of Managing Variation in a High Technology Enterprise | p. 87 |

5.3 Creating a Sense of Urgency | p. 88 |

5.4 Taguchi's Quality Philosophy | p. 90 |

5.5 Creating a Low ppm Environment | p. 94 |

5.6 Defining the Boundaries Between Low ppm and Perfectionism | p. 96 |

5.7 Do We Need Statistical Process Control for Automated Equipment? | p. 97 |

5.8 The Human Side of Variation | p. 98 |

References | p. 101 |

Part II Process Control and Capability Studies | p. 103 |

6 Some Important Probability Distributions | p. 105 |

6.1 The Normal Probability Distribution (Often Called the "Normal Curve") | p. 105 |

6.2 The Binomial Distribution | p. 110 |

6.3 The Poisson Distribution | p. 111 |

6.4 The Geometric Distribution | p. 117 |

6.5 The Normal Distribution as an Approximation of the Binomial Distribution | p. 118 |

6.6 The Poisson Distribution as an Approximation of the Binomial Distribution | p. 120 |

References | p. 122 |

7 Statistical Process Control | p. 123 |

7.1 What Is a Process? | p. 123 |

7.2 The Concept of Control | p. 124 |

7.3 Control Charts | p. 127 |

7.4 Understanding the Control Chart Signals | p. 161 |

7.5 Interpreting the Control Chart Patterns | p. 163 |

7.6 Subgroup Sample Size and Frequency of Sampling When Using Control Charts | p. 174 |

7.7 Some New and Forgotten Older Statistical Techniques | p. 180 |

References | p. 220 |

8 Measurement and Inspection Capability Studies | p. 221 |

8.1 Concepts and Terminology | p. 221 |

8.2 Measurement Process Capability Studies | p. 229 |

8.3 Inspection Capability Studies | p. 251 |

References | p. 269 |

9 Process Capability Study | p. 271 |

9.1 Process Capability | p. 271 |

9.2 The Measure of Process Capability | p. 273 |

9.3 Methods and Techniques for Continuous Process Improvement | p. 281 |

9.4 Mini Capability Check | p. 288 |

9.5 Using a Process Setting Chart | p. 291 |

9.6 Tentative Process Capability Study | p. 294 |

9.7 Formal Process Capability Studies | p. 306 |

9.8 Using Attribute Data to Determine the Process Capability | p. 322 |

9.9 The Seven Phases of Performing a Process Capability Study | p. 329 |

9.10 If the Process is Not in Control--Should We Make Capability Predictions? | p. 332 |

9.11 How Large Should the Sample Size Be to Determine the Process Average? | p. 334 |

References | p. 341 |

10 Working with Skewed Distributions | p. 343 |

10.1 Skewness | p. 344 |

10.2 Kurtosis as a Departure from Normality | p. 350 |

10.3 Achieving Symmetry by Transformation | p. 352 |

10.4 Mirror Image Transformation | p. 363 |

10.5 Application of the Second Application to the Normal Curve | p. 366 |

References | p. 370 |

11 Engineering Specifications | p. 373 |

11.1 The Arbitrary Approach of Tolerancing | p. 374 |

11.2 The Scientific Approach of Tolerancing | p. 374 |

11.3 Establishing Statistical Tolerance Limits | p. 380 |

References | p. 384 |

12 Zero Defects Process Capability | p. 385 |

12.1 What Went Wrong with the Zero Defects Program in the 1960s? | p. 385 |

12.2 Can We Have an Excellent Process? | p. 386 |

12.3 Motorola's Six Sigma Quality Program | p. 387 |

12.4 Six Sigma Quality: Attribute Data | p. 391 |

References | p. 394 |

13 Managing Sampling Systems in a Low ppm Environment | p. 397 |

13.1 Introduction | p. 397 |

13.2 A Glance at Various Sampling Systems for Low ppm | p. 399 |

13.3 A Fundamental of Sampling Systems | p. 401 |

13.4 The Importance of Using the c = 0 Sampling Plans | p. 407 |

13.5 Designing a Sampling Plan for Large Lots Based on the LTPD Requirement | p. 408 |

13.6 Reporting Process Quality Based on Sampling Results | p. 409 |

13.7 Moving from Sampling Inspection to Process Control | p. 417 |

13.8 The Poka-Yoke (Error Proofing) System | p. 418 |

References | p. 422 |

Part III Off-Line and On-Line Design of Experiments | p. 423 |

14 Off-Line Design of Experiments | p. 427 |

14.1 The Classical One-Factor-at-a-Time Experiment | p. 427 |

14.2 Introduction to Analysis of Variance | p. 431 |

14.3 Introduction to Factorial Experiments | p. 438 |

14.4 The Taguchi Approach to Quality Improvement | p. 449 |

14.5 Nested Design | p. 473 |

References | p. 483 |

15 On-Line Design of Experiments | p. 485 |

15.1 Evolutionary Operation (EVOP) | p. 488 |

15.2 Simplex EVOP | p. 520 |

15.3 Introducing an EVOP Program | p. 529 |

15.4 The EVOP Educational Program | p. 532 |

15.5 The Strategy Depends on the Objectives | p. 534 |

15.6 Other EVOP Techniques | p. 535 |

Appendix 15.1 Calculations for Two- and Three-Variable EVOP Programs | p. 538 |

Appendix 15.2 Procedure of Locating the Coordinates of a Simplex | p. 548 |

Appendix 15.3 EVOP Training Program | p. 551 |

Appendix 15.4 Number of Cycles Needed to Detect a Significant Effect | p. 551 |

References | p. 553 |

Appendixes | p. 555 |

A The Effect of Tampering with the Process | p. 555 |

B Factors for Constructing Control Charts | p. 559 |

C Area Under Normal Distribution (Z Table) | p. 561 |

D Tables for Testing Skewness and Kurtosis | p. 563 |

E Percentage Points of the F Distribution | p. 565 |

F Orthogonal Arrays | p. 571 |

G Omega Transformation Table | p. 575 |

H Percentage Points of the t Distribution | p. 579 |

I Percentage Points of the x[superscript 2] Distribution | p. 581 |

J Cumulative Poisson Distribution | p. 583 |

K Supporting Theory for the CCC Chart and the Process Rejection Sampling Plan | p. 587 |

L Values of e[superscript -x] | p. 589 |

M One-Sided and Two-Sided Statistical Tolerance Intervals | p. 591 |

N A Quick Method to Design the OC and AOQ Curves for c = 0 Sampling Plans | p. 595 |

O np Values for Various Confidence Intervals, Probabilities of Acceptance, and Numbers of Nonconforming Units | p. 599 |

Glossary | p. 603 |

Index | p. 627 |