Six Sigma and Beyond: Design of Experiments, Volume V, 1st Edition (Hardback) book cover

Six Sigma and Beyond

Design of Experiments, Volume V, 1st Edition

By D.H. Stamatis

CRC Press

656 pages | 322 B/W Illus.

Purchasing Options:$ = USD
Hardback: 9781574443141
pub: 2002-10-29
SAVE ~$48.00
$240.00
$192.00
x


FREE Standard Shipping!

Description

I In this volume, the author demystifies the Design of Experiments (DOE). He begins with a clear explanation of the traditional experimentation process. He then covers the concept of variation and the importance of experimentation and follows through with applications. Stamatis also discusses full and fractional factorials. The strength of this volume lies in the fact that not only does it introduce the concept of robustness, it also addresses "Robust Designs" with discussions on the Taguchi methodology of experimentation. And throughout the author ties these concepts into the Six Sigma philosophy and shows readers how they use those concepts in their organizations.

Reviews

"The text is … well written, and the author's enthusiasm and extensive design expertise shines through. … This book is a worthwhile addition to the bookshelf of engineers or quality professionals who use or intend to use experimental design."

- Technometrics, Vol. 46, No. 4, November 2004

Promo Copy

Table of Contents

TRADITIONAL EXPERIMENTAL DESIGN

Introduction

Fundamental concepts

Anatomy of an experiment

Principles of conduct

Variation

General types of designs

Logic of hypothesis testing

Experimental error

Expected values

Degrees of freedom

Coding and data analysis

Interaction

Fixed, Random, Mixed designs

EMS rules

Example

References

Selected bibliography

The planning and managing the "process" of experimentation

Plan

Do

Study

Act

Getting started with experimental design

Considerations of experimental designs

Statistical fundamentals

Measures of location

Measures of dispersion

Shape of distributions

Structure and form of experimental designs

Validity of experimentation

Design types

References

Selected bibliography

Analysis of existing data

Variance and covariance

Simple regression

Test for significance

Multiple regression

Calculating of the squared multiple correlation coefficient

References

Selected bibliography

Analysis of means

Statistical hypothesis/null hypothesis

Sample size considerations

Analysis of "means" (ANOM)

Sources of variation analysis (SVA)

Other "means" tests

Estimation error and confidence intervals

Independent samples

Dependent samples

Selected bibliography

Analysis of variance (ANOVA)

Assumptions of analysis of variance

Common designs for experiments

Complete randomization for background conditions

The one way analysis of variance

Two way analysis

Randomization block design for background conditions

Latin square design for background condition

Other designs

Types of ANOVA

After ANOVA, What?

Means effects

After ANOVA, What?

Homogeneity test

Recommendations

Examples

References

Selected bibliography

Factorial designs

Special vocabulary

A factorial experiment model

Factorial experiment assumptions

The nature of factorial analysis of variance

Advantages of factorial analysis of variance

Fractional factorial designs

References

Selected bibliography

Full factorial Experiments

Key vocabulary of terms

Notation

One factor situation

Two level factorial designs

Two factor situation

Three factor situation

Generalized 2k designs

Conduct experiments

Analysis of 2k factorials

Example

Run

Graphical aids for analysis

Judging the importance of location effects

Graphical assessment of effects

Judging the importance of variance effects

Judging the importance of differences of proportions

Selected bibliography

Model Building - Utility of models with experimental design

Single factor model

Two factor models

Generalized interactive models

Model checking

Residuals

Curvature checking with 2k designs

Selected bibliography

Fractional factorial experiments

Confounding and resolution

Catalog of fractional factorial designs

Randomization, replication and repetition

Analysis of fractional factorial designs

Worksheets for different designs

Two level fractional factorial screening designs

Eight run Plackett-Burman Designs

Interpretation

Combining designs

Worksheets for screening designs

Missing data

Revealing the confounding of fractional factorial experiments

Setting preferred designs

References

Selected Bibliography

Three level designs

3k factorial experiments

Examples of complexity for 32 and 33 designs

3k designs

The 33 design

Analysis of 3k designs

Yate's algorithm for the 3k design

Central composite design

Key items in factorial designs

References

Selected bibliography

Special topics in design of experiments

Covariance analysis

Evolutionary operation (EVOP)

Response surface methodology

Sequential on line optimization

Analysis of attribute data

Randomized Incomplete block designs - restriction on experimentation

References

Selected bibliography

ROBUST PARAMETER DESIGN

Introduction to Taguchi and Parameter Design

Introduction

Taguchi Design

The research process

A comparison between the typical steps in industrial experimentation and the Taguchi approach

References

Selected Bibliography

A new attitude and Approach

Orthogonal arrays

Average quality function

Quality characteristics and the loss function

Selected bibliography

Orthogonal arrays and linear graphs

The 23 layout

Definition of orthogonality

Weighing problem

Orthogonal array L8

Reasons for using Orthogonal arrays

Three level orthogonal arrays

The L9 orthogonal array

Linear graphs

Multilevel arrangements in 2 level series Orthogonal arrays

Preparation for a 4 level columns

Discussion

Warning about the L8, L18 and L27 OAs

References

Selected bibliography

Parameter design

The signal to noise ratio

Strategies dealing with noise factors

Behavior of the signal to noise ratio

Classified attribute analysis

Comparing mean analysis and signal to noise analysis

Robustness and the ideal function

Dynamic characteristics and ideal function

What are dynamic characteristics?

Ideal function

References

Selected bibliography

Taguchi and ANOVA

The role of ANOVA

ANOVA terms, notations and development

Definitions

Tolerance design

The relationship between tolerance design and loss function

Tolerance design process

Selected bibliography

Case studies

Parameter design - Die casting process

Process optimization - Clutch plate rust inhibition

Appendix A: Orthogonal Arrays and linear graphs

Appendix B: Technical discussions

Appendix C: Annotated computer program

Appendix E: Forms

Glossary

Selected Bibliography

Subject Categories

BISAC Subject Codes/Headings:
BUS053000
BUSINESS & ECONOMICS / Quality Control
TEC032000
TECHNOLOGY & ENGINEERING / Quality Control