
Part I Fundamental Concepts and Methods 


1  (134) 

Evolution of Quality Design and Control 


3  (31) 


3  (1) 

Quality Revolution of the 1980s 


4  (2) 

Historical Perspective of the Management of Quality 


6  (7) 

Quality and the Engineering Design Process 


13  (4) 

Strategic View of Quality Design and Improvement 


17  (9) 

Beyond the 1980sThe Institutionalization of Quality in the Organization 


26  (8) 


31  (1) 


31  (3) 

Conceptual Framework for Quality: Design and Control 


34  (30) 


34  (1) 

Deming Philosophy of NeverEnding Improvement 


35  (14) 

Traditional View of Quality 


49  (3) 

Taguchi's Definition of Quality 


52  (5) 


57  (7) 


62  (2) 

Statistical Methods and Probability Concepts for Data Characterization 


64  (42) 


64  (1) 

Characterizations and Representations of Data 


64  (7) 

Some Important Concepts of Probability and Probability Distributions 


71  (7) 


78  (4) 

Some Other Useful Graphical Representations of Data 


82  (24) 


95  (11) 

Sampling Distributions and Statistical Hypothesis Testing 


106  (29) 


106  (1) 

Purpose and Nature of Sampling 


107  (3) 

Sampling Distribution of X 


110  (5) 

Hypothesis Testing of a Population Mean 


115  (11) 

Confidence Interval Estimation of the mean 


126  (9) 


130  (5) 

Part II Process Control and Improvement 


135  (388) 

Conceptual Framework for Statistical Process Control 


137  (38) 


137  (1) 

Origins and Characteristic Behavior of Variability 


138  (4) 

Process Behavior Over Time 


142  (5) 

Shewhart's Concept of Statistical Control 


147  (4) 

Control Chart Approach to the Management of Process Variation 


151  (7) 

The Process of Statistical Process Control 


158  (3) 

Deming's Famous Red Bead Experiment 


161  (9) 

The Debilitating Effects of Tampering 


170  (5) 


172  (3) 

Shewhart Control Charts for Variable Data 


175  (62) 


175  (1) 

Statistical Basis for Shewhart Control Charts 


175  (3) 

Control Chart for Averages, X 


178  (3) 


181  (2) 

Setting Up X and R Control Charts 


183  (2) 

Interpretation of Shewhart Control Chart Patterns 


185  (8) 

Closing the Loop Using the Process of SPC 


193  (7) 

Cylinder Liner Boring Case StudyDemonstrating the Process of SPC 


200  (12) 

A Note on Computer Software 


212  (25) 


213  (24) 

Importance of Rational Sampling 


237  (23) 


237  (1) 

Concept of Rational Sampling 


237  (3) 

Merits of Consecutive Versus Distributed Sampling 


240  (1) 

Some Common Pitfalls in Subgroup Selection 


241  (6) 

Examples of the Stratification Phenomenon 


247  (13) 


254  (6) 

Interpretation of X and R Control Charts: Use of Sampling Experiments 


260  (29) 


260  (1) 

Analysis of Control Chart Patterns: A Sampling Experiment 


261  (13) 

Illustration of Stratification of Subgroups 


274  (15) 

SPC Workshop #1: Process Simulation, PROSIM 


287  (2) 

Some Control Chart Methods for Individual Measurements 


289  (38) 


289  (1) 


290  (2) 

Case Study: White Millbase Dispersion Process 


292  (9) 

Exponentially Weighted Moving Average Control Charts 


301  (26) 


313  (14) 

Process Capability Assessment 


327  (39) 


327  (1) 

Process Capability Versus Process Control 


327  (3) 

Statistical Assessment of Process Capability: A Case Study Revisited 


330  (6) 

Some Common Indices of Process Capability 


336  (3) 

Loss Function Approach to Capability Assessment 


339  (9) 

The Dilemma of Cpk: A Case Study 


348  (18) 


357  (9) 

The Design and Analysis of Tolerances 


366  (38) 


366  (1) 

Tolerancing and Competitiveness 


367  (5) 

Statistical Interpretation of Six Sigma Quality 


372  (5) 

Tolerance Design and Analysis 


377  (6) 

Statistical Assessment and Assignment of Tolerances 


383  (8) 

Statistical Process Control and the Statistical Tolerance Model 


391  (13) 


395  (9) 

Statistical Thinking for Process Study: A Case Study 


404  (41) 


404  (1) 

Overview of the Case Study 


405  (2) 

Product Versus Process Control: Management Strategy 


407  (7) 

Finding Improvement Opportunities Through Charting 


414  (10) 

Process Capability Versus Process Control 


424  (8) 

Seeking Further Improvement Through Design of Experiments 


432  (13) 


440  (1) 


441  (2) 

SPC Workshop #2: Turning Simulation, TURNSIM 


443  (2) 

Shewhart Control Charts for Attribute Data 


445  (58) 

Data Characterization by Attributes 


445  (4) 

Control Chart for Fraction Defective 


449  (14) 

VariableSampleSize Considerations for the p Chart 


463  (6) 

Control Chart for Number of Defectives 


469  (2) 

Control Chart for Number of Defects 


471  (8) 

Control Chart for Number of Defects per Unit 


479  (24) 


483  (20) 

Attribute Control Chart Implementation for Process Improvement: Two Case Studies 


503  (20) 


503  (1) 

Implementation of SPC Methods: A Case Study on ``Press 120''Visual Defects in a Molding Process 


503  (9) 

Improvement of an Accounts Payable Process 


512  (11) 

Part III Product/Process Design and Imoprovement 


523  (383) 

Conceptual Framework for Planned Experimentation 


525  (38) 


525  (1) 

Role of Experimentation in Quality Design and Improvement 


525  (3) 

Some Important Issues in Planned Experimentation 


528  (9) 

Dealing with Noise in the Experimental Environment 


537  (8) 

Role of Planned Experimentation in Taguchi Methods 


545  (11) 

Contrasting Philosophies for Dealing with Nuisance or Noise Factors 


556  (7) 


558  (5) 

Design and Analysis of Simple Comparative Experiments 


563  (50) 


563  (1) 

Comparing Two Alternatives Using an External Reference DistributionCar Mileage Example 


563  (4) 

Comparing Two Alternatives via an Internal Reference Distribution 


567  (6) 

Comparing Two Alternatives Using a Blocked Design 


573  (7) 

Comparison of k Treatments Using Analysis of VarianceOneWay ANOVA 


580  (12) 

Comparison of Multiple Treatments Using a Blocked DesignTwoWay ANOVA 


592  (21) 


602  (1) 


603  (10) 

Design and Interpretation of 2k Factorial Experiments 


613  (52) 


613  (1) 

Process Study Using a TwoLevel Factorial Design: Chemical Calibration for the Foam Molding Process 


614  (2) 

Construction of the 23 Factorial Design 


616  (2) 

Calculation and Interpretation of Main Effects 


618  (6) 

Calculation and Interpretation of Interaction Effects 


624  (9) 

Generalized Method for the Calculation of Effects 


633  (2) 

Mathematical Model of the Response 


635  (6) 

LeastSquares Approach to Model Fitting 


641  (24) 


651  (14) 

Analysis of TwoLevel Factorial Designs 


665  (30) 


665  (1) 

Analysis of Replicated 2k Experiments 


666  (7) 

Determination of Statistically Significant Effects 


673  (7) 

Analysis of the Results of Unreplicated TwoLevel Factorials 


680  (15) 


684  (1) 


685  (10) 

Model Building for Design and Improvement Using TwoLevel Factorial Designs 


695  (56) 


695  (1) 

Glove Box Door Alignment Study Revisited 


696  (5) 

Diagnostic Checking of the Fitted Model 


701  (8) 

Checking the Assumption of Common Variance of the Responses 


709  (3) 

Using the Fitted Model for Quality Improvement 


712  (4) 

Another Case Study: Surface Finish of a Machined Part 


716  (8) 

Use of Analysis of Variance for TwoLevel Factorial Design Effect Evaluation 


724  (7) 

Use of Analysis of Variance on the Glove Box Door Alignment Study 


731  (20) 


735  (14) 

DOE Workshop #1: Turning Simulation, TURN5DOE 


749  (2) 

TwoLevel Fractional Factorial Designs 


751  (46) 

Rationale for, and Consequences of, Fractionation of TwoLevel Factorials 


751  (4) 

System to Define the Confounding Pattern of a TwoLevel Fractional Factorial 


755  (7) 

Procedure for Design Characterization: Another Example 


762  (3) 

Concept of Resolution of TwoLevel Fractional Factorial Designs 


765  (3) 

Case Study Application: The Sandmill Experiment Revisited 


768  (7) 

Orthogonal Arrays and TwoLevel Fractional Factorial Designs 


775  (22) 


784  (13) 

Sequential and Iterative Nature of Experimentation 


797  (35) 

Value of Sequential Experimentation: A Case Study 


797  (13) 

Sequential Assembly of Fractional Factorials 


810  (8) 

Soybean WhippedTopping Example: Summary and Interpretation 


818  (14) 


821  (9) 

DOE Workshop #2: Turning Simulation, TURN9DOE 


830  (2) 

Robust Design Case Studies 


832  (26) 

Taguchi's Approach to Robust Design 


832  (1) 

Overview of Approaches to Robust Design 


832  (2) 

Case Study 1: Fuel Gage Calibration 


834  (5) 

Case Study 2: Glove Box Closing Effort Analysis 


839  (5) 

Case Study 3: Automobile Door Closing Effort 


844  (2) 

Case Study 4: Simultaneous Engineering of a Product and Its Manufacturing Process 


846  (12) 

Modeling of Response Surfaces and Response Optimization 


858  (48) 


858  (2) 

Modeling the Response Surface 


860  (1) 

Response Surface MethodologyA Brief Description 


861  (7) 

RSM ExampleA Pulp Whitening Process 


868  (13) 

Soldering Process OptimizationA Case Study 


881  (25) 


895  (9) 

DOE Workshop #3: Response Surface Methodology, RSMGAME 


904  (2) 
References and Further Readings 

906  (9) 
Appendix Tables 

915  (12) 
Index 

927  