Statistical Quality Design and Control Contemporary Concepts and Methods

by DeVor, Richard E.; Chang, Tsong-how; Sutherland, John W.

• ISBN13: 9780130413444
• ISBN10: 0130413445
• Edition: 2nd
• Format: Paperback
• Copyright: 2006-07-25
• Publisher: Pearson

Summary

Features a blend of statistical process control (SPC) and design of experiments (DOE) concepts and methods for quality design and improvement. The book places particularly strong emphasis on proper methods for data collection, control chart construction and interpretation, and fault diagnosis for process improvement.

Table of Contents

Part I Fundamental Concepts and Methods	1	(134)
Evolution of Quality Design and Control	3	(31)
Introduction	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 1980s---The Institutionalization of Quality in the Organization	26	(8)
Chapter Summary	31	(1)
Exercises	31	(3)
Conceptual Framework for Quality: Design and Control	34	(30)
Introduction	34	(1)
Deming Philosophy of Never-Ending Improvement	35	(14)
Traditional View of Quality	49	(3)
Taguchi's Definition of Quality	52	(5)
Cost-of-Quality Issue	57	(7)
Exercises	62	(2)
Statistical Methods and Probability Concepts for Data Characterization	64	(42)
Introduction	64	(1)
Characterizations and Representations of Data	64	(7)
Some Important Concepts of Probability and Probability Distributions	71	(7)
Normal Distribution	78	(4)
Some Other Useful Graphical Representations of Data	82	(24)
Exercises	95	(11)
Sampling Distributions and Statistical Hypothesis Testing	106	(29)
Introduction	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)
Exercises	130	(5)
Part II Process Control and Improvement	135	(388)
Conceptual Framework for Statistical Process Control	137	(38)
Introduction	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)
Exercises	172	(3)
Shewhart Control Charts for Variable Data	175	(62)
Introduction	175	(1)
Statistical Basis for Shewhart Control Charts	175	(3)
Control Chart for Averages, X	178	(3)
Control Chart for Ranges	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 Study---Demonstrating the Process of SPC	200	(12)
A Note on Computer Software	212	(25)
Exercises	213	(24)
Importance of Rational Sampling	237	(23)
Introduction	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)
Exercises	254	(6)
Interpretation of X and R Control Charts: Use of Sampling Experiments	260	(29)
Introduction	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)
Introduction	289	(1)
X and Rm Control Charts	290	(2)
Case Study: White Millbase Dispersion Process	292	(9)
Exponentially Weighted Moving Average Control Charts	301	(26)
Exercises	313	(14)
Process Capability Assessment	327	(39)
Introduction	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)
Exercises	357	(9)
The Design and Analysis of Tolerances	366	(38)
Introduction	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)
Exercises	395	(9)
Statistical Thinking for Process Study: A Case Study	404	(41)
Introduction	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)
Chapter Summary	440	(1)
Exercises	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)
Variable-Sample-Size 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)
Exercises	483	(20)
Attribute Control Chart Implementation for Process Improvement: Two Case Studies	503	(20)
Introduction	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)
Introduction	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)
Exercises	558	(5)
Design and Analysis of Simple Comparative Experiments	563	(50)
Introduction	563	(1)
Comparing Two Alternatives Using an External Reference Distribution--Car 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 Variance---One-Way ANOVA	580	(12)
Comparison of Multiple Treatments Using a Blocked Design---Two-Way ANOVA	592	(21)
Chapter Summary	602	(1)
Exercises	603	(10)
Design and Interpretation of 2k Factorial Experiments	613	(52)
Introduction	613	(1)
Process Study Using a Two-Level 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)
Least-Squares Approach to Model Fitting	641	(24)
Exercises	651	(14)
Analysis of Two-Level Factorial Designs	665	(30)
Introduction	665	(1)
Analysis of Replicated 2k Experiments	666	(7)
Determination of Statistically Significant Effects	673	(7)
Analysis of the Results of Unreplicated Two-Level Factorials	680	(15)
Chapter Summary	684	(1)
Exercises	685	(10)
Model Building for Design and Improvement Using Two-Level Factorial Designs	695	(56)
Introduction	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 Two-Level Factorial Design Effect Evaluation	724	(7)
Use of Analysis of Variance on the Glove Box Door Alignment Study	731	(20)
Exercises	735	(14)
DOE Workshop #1: Turning Simulation, TURN5DOE	749	(2)
Two-Level Fractional Factorial Designs	751	(46)
Rationale for, and Consequences of, Fractionation of Two-Level Factorials	751	(4)
System to Define the Confounding Pattern of a Two-Level Fractional Factorial	755	(7)
Procedure for Design Characterization: Another Example	762	(3)
Concept of Resolution of Two-Level Fractional Factorial Designs	765	(3)
Case Study Application: The Sandmill Experiment Revisited	768	(7)
Orthogonal Arrays and Two-Level Fractional Factorial Designs	775	(22)
Exercises	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 Whipped-Topping Example: Summary and Interpretation	818	(14)
Exercises	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)
Introduction	858	(2)
Modeling the Response Surface	860	(1)
Response Surface Methodology---A Brief Description	861	(7)
RSM Example-A Pulp Whitening Process	868	(13)
Soldering Process Optimization---A Case Study	881	(25)
Exercises	895	(9)
DOE Workshop #3: Response Surface Methodology, RSMGAME	904	(2)
References and Further Readings	906	(9)
Appendix Tables	915	(12)
Index	927