Design of experiments using the Taguchi approach : 16 steps to product and process improvement / Ranjit K. Roy.

Format:

Book

Author/Creator:

Roy, Ranjit K., 1947-

Contributor:

Alumni and Friends Memorial Book Fund.

Language:

English

Subjects (All):

Quality control--Statistical methods.

Quality control.

Taguchi methods (Quality control).

Experimental design.

Physical Description:

xv, 538 pages : illustrations ; 24 cm + 1 CD-ROM (4 3/4 in.)

Place of Publication:

New York : Wiley, [2001]

System Details:

System requirements for accompanying CD-ROM: Windows 3.1 or higher.

Summary:

Accompanying CD-ROM contains ... "Qualitek-4: automatic design & analysis of Taguchi experiments (full featured working model - demo); all the examples, exercise solutions, and case studies in the book."--CD-ROM label.

Contents:

DOE Application Skills 1

Quick Step Summary 3

Step 1. Design of Experiments and the Taguchi Approach 8

Overview of Design of Experiments and the Taguchi Approach 8

What Is Design of Experiments? 9

Who Is Taguchi? 9

Why Is Taguchi's Name Associated with DOE Today? 10

What's New? 10

New Philosophy and Attitude Toward Building Quality 10

New Way to Measure Cost of Quality 14

New Disciplines 15

Simpler and Standardized Experiment Design Technique 18

What Is DOE All About? 19

Where Should DOE Be Applied? 21

What Types of Industries Can Benefit from DOE? 21

Who Should Benefit Most from DOE? 21

Step 2. Definition and Measurement of Quality 25

Performance Evaluation and Measurement 25

Process View of System under Study 26

Types of Results 29

Evaluations for Comparison 30

Setting Up Qualitek-4 Software in Your Computer 33

Copying Example Experiment Files to the QT4 Program Directory 37

Running the QT4 Program 37

Comparison of Individual Performances 40

Comparison of Group Performances 40

Measuring Variations with Mean-Squared Deviation 41

Using QT4 for MSD Calculation 44

Results Comprising Multiple Criteria of Evaluation 50

OEC Formulation 53

Rationale for the OEC Formula 54

Calculating OEC Using QT4 55

Things to Remember When Using QT4 OEC Capabilities 57

Step 3. Common Experiments and Methods of Analysis 65

Why Experiment? 65

Language of Experiments 66

Investigating One Factor at a Time 70

Finding the Desirable Factor Level from Multilevel Experiments 74

Investigating Several Factors One at a Time 75

Lack of Reproducibility 78

Assessing the Status of Performance from Multiple Sample Tests 79

Step 4. Experimental Design Using Orthogonal Arrays 95

Experiments with Multiple Factors 95

Experiments That Look At All Possible Factor Combinations 96

Shortcuts to Design of Experiments 99

Properties of Orthogonal Arrays 99

Orthogonal Properties of Arrays 100

Common Orthogonal Arrays and Their Special Properties 102

Using Orthogonal Arrays to Design Experiments 103

Experiment Planning: First Step in DOE Application 110

Completing Experiments as Planned 115

Case Study 4.1: Part Strength Study 115

Step 5. Experimental Design with Two-Level Factors Only 136

Two Ways to Use an L-4 Orthogonal Array 136

Four Ways to Use an L-8 Orthogonal Array 143

Four Ways to Use an L-12 Orthogonal Array 157

Four Ways to Use an L-16 Orthogonal Array 159

Sixteen Ways to Use an L-32 Orthogonal Array 161

Improved Reproducibility with Orthogonal Array Experiments 162

Analytical Verification of Orthogonal Array Experiments 165

Step 6. Experimental Design With Three- and Four-Level Factors 172

Three Ways to use an L-9 Orthogonal Array 172

Over Six Ways to Use an L-18 Orthogonal Array 179

Six Ways to Use an L-27 Orthogonal Array 186

Four Ways to Use a Modified L-16 Orthogonal Array 193

Nine Ways to Use a Modified L-32 Orthogonal Array 198

Step 7. Analysis of Variance 207

Two Parts of the Analysis 207

Part I Simple Analysis 207

Part II Analysis of Variance 208

Why Perform ANOVA? 208

ANOVA Calculation Strategy 209

Degrees of Freedom 211

Confidence Level and Confidence Interval 223

ANOVA Utilities 224

Error Term 224

Test of Significance 226

Experimenters: Be Aware 233

Step 8. Experimental Design for Studying Factor Interaction 240

What Is Interaction, Anyway? 241

Forms of Interactions 244

Sorting Out Interactions between 2 Two-Level Factors 246

Interaction Design, Analysis, and Correction 249

Strategy for Experimental Study with Larger Number of Factors 275

Interactions between Three- and Four-Level Factors 276

Step 9. Experimental Design with Mixed-Level Factors 285

How to Determine Which Array to Modify 286

Review of Array Modification Techniques 301

Step 10. Combination Designs 319

Factor-Level Compatibilities 319

Combination Design Technique 321

Main Effects of Combined Factors 322

Step 11. Strategies for Robust Design 336

Driving Philosophy 337

Collecting Information about Variation 338

Experimental Strategy for Robust Design 339

Formalities of Combining Noise Factors 339

Preferred Ways to Treat Noise Factors 362

Step 12. Analysis Using Signal-to-Noise Ratios 369

Mean-Squared Deviation 370

Definition of MSD for the Three Quality Characteristics 371

Recommended Yardstick for Analysis 371

Benefits and Complexities of Analyses Using S/N Ratios 372

Calculation of ANOVA Terms 392

Alternative Form of "Nominal is Best" S/N Ratio 397

Step 13. Results Comprising Multiple Criteria of Evaluations 405

Overall Evaluation Criterion 406

Recommended Analysis Strategy for Multiple Objectives 406

Step 14. Quantification of Variation Reduction and Performance Improvement 433

How to Measure and Express Improvement 434

Interrelationships among Common Distribution Statistics 435

Expressing Improvements in Terms of Dollars 437

Estimation of Variation from Known S/N Ratios 444

Relationship between Gain in S/N and Standard Deviation 447

Relationship between Gain in S/N and Loss in Dollars 448

Relationship between Capability Indices and Standard Deviation 449

Step 15. Effective Experiment Preparation and Planning 465

Preparation for Experimentation 465

Project Selection 466

Team Selection 467

Planning and Execution of the Experiment 468

Application and Analysis Checklist 474

Case Study 16.1 Body Panel Thickness Variation Reduction Study 480

Case Study 16.2 Window-Cranking Effort Reduction Study 485

Case Study 16.3 Reduction of Hydrogen Embrittlement in Electroplating 488

Case Study 16.4 Water-Jet Cutting Process Study 490

Case Study 16.5 Performance Optimization of an Airbag Inflator 495

Case Study 16.6 Summary of Laser Welding Process Study 501

Case Study 16.7 Summary of Paint and Urethane Bond Strength Study 504

Case Study 16.8 Summary of Finish Turning Process Optimization Study 505

Case Study 16.9 Driver Comfort Simulation Study 507

Case Study 16.10 Optimization of Tensile Strength of an Airbag Stitch Seam 509

Case Study 16.11 Summary of Resistance Spot Welding Study 511

F-Tables 516

Common Orthogonal Arrays 518

Two-Level Orthogonal Arrays and Interactions (Linear Graphs) 518

Three-Level Orthogonal Arrays 522

Four-Level Orthogonal Arrays 524

Linear Graphs for Two-Level Orthogonal Arrays 526

Practice Session Using Qualitek-4 Software 527

Special Tasks: Capturing, Pasting, and Cropping QT4 Screens for Reports and Presentations 529

What's on the Disk 530.

Notes:

"A Wiley-Interscience publication."

Includes bibliographical references (pages 526-527) and index.

Local Notes:

Acquired for the Penn Libraries with assistance from the Alumni and Friends Memorial Book Fund.

ISBN:

0471361011

OCLC:

43894329

Online:

Contributor biographical information

Publisher description

Table of Contents