Box on Quality and Discovery : With Design, Control, and Robustness

by Editor-in-Chief: George C. Tiao (Univ. of Chicago); Editor: Sø; ren Bisgaard (Univ. of St. Gallen, Switzerland); Editor: William J. Hill (Allied Signal Chemicals); Editor: Daniel Peña (Univ. Carlos III de Madrid, Spain); Editor: Stephen M.

• ISBN13: 9780471387688
• ISBN10: 0471387681
• Format: Hardcover
• Copyright: 2000-08-01
• Publisher: Wiley-Interscience

Summary

This is a special, one-time volume, commemorating the 80th birthday of George E. P. Box. It contains over 75 articles on quality and quality-related issues, written by Box himself since 1982. Previous to this book, the editors published a similar volume on Box' writings up to 1982; it has since become a standard and useful reference for students and practitioners alike in the field of statistics.

Author Biography

GEORGE C. TIAO, PhD, is Professor of Statistics at the University of Chicago. S+REN BISGAARD, PhD, is Professor at the University of St. Gallen in Switzerland. WILLIAM J. HILL, PhD, is Fellow at Honeywell International Inc., Buffalo, New York. DANIEL PE-A, PhD, is Professor of Statistics and Econometrics, University Carlos III, Madrid. STEPHEN M. STIGLER, PhD, is Professor of Statistics at the University of Chicago.

Table of Contents

Foreword	xiii
My Professional Life	xvii
Part A. Improving Almost Anything
Introduction	3	(1)
Good Quality Costs Less? How Come?	4	(6)
When Murphy Speaks--Listen	10	(11)
Changing Management Policy to Improve Quality and Productivity	21	(6)
Scientific Method: The Generation of Knowledge and Quality	27	(10)
Part B. Design of Experiments for Quality
Introduction	37	(2)
Do Interactions Matter?	39	(4)
Teaching Engineers Experimental Design with a Paper Helicopter	43	(7)
What Can You Find Out from Eight Experimental Runs?	50	(9)
What Can You Find Out from Sixteen Experimental Runs?	59	(11)
What Can You Find Out from Twelve Experimental Runs?	70	(5)
S. Bisgaard
Sequential Experimentation and Sequential Assembly of Designs	75	(9)
Must We Randomize Our Experiment?	84	(6)
A Simple Way to Deal with Missing Observations from Designed Experiments	90	(5)
Finding Bad Values in Factorial Designs	95	(5)
How to Get Lucky	100	(8)
Dispersion Effects from Fractional Designs	108	(18)
R. D. Meyer
The Importance of Practice in the Development of Statistics	126	(15)
Part C. Sequential Investigation and Discovery
Introduction	141	(5)
A Demonstration of Response Surface Methods	146	(24)
P. Y. T. Liu
Response Surface Methods: Some History	170	(4)
Statistics as a Catalyst to Learning	174	(8)
Experience as a Guide to Theoretical Development	182	(7)
The Invention of the Composite Design	189	(6)
Finding the Active Factors in Fractionated Screening Experiments	195	(19)
R. D. Meyer
Follow-up Designs to Resolve Confounding in Multifactor Experiments	214	(22)
R. D. Meyer
D. M. Steinberg
Projective Properties of Certain Orthogonal Arrays	236	(8)
J. Tyssedal
Choice of Response Surface Design and Alphabetic Optimality	244	(23)
An Apology for Ecumenism in Statistics	267	(24)
Part D. Control
Introduction	291	(3)
Six Sigma, Process Drift, Capability Indices, and Feedback Adjustment	294	(7)
A. Luceno
Understanding Exponential Smoothing: A Simple Way to Forecast Sales and Inventory	301	(7)
Feedback Control by Manual Adjustment	308	(10)
Bounded Adjustment Charts	318	(8)
Statistical Process Monitoring and Feedback Adjustment-A Discussion	326	(29)
T. Kramer
Discrete Proportional-Integral Control with Constrained Adjustment	355	(17)
A. Luceno
Discrete Proportional-Integral Adjustment and Statistical Process Control	372	(29)
A. Luceno
Selection of Sampling Interval and Action Limit for Discrete Feedback Adjustment	401	(17)
A. Luceno
Use of Cusum Statistics in the Analysis of Data and in Process Monitoring	418	(4)
Influence of the Sampling Interval, Decision Limit, and Autocorrelation on the Average Run Length in Cusum Charts	422	(7)
A. Luceno
Cumulative Score Charts	429	(10)
J. Ramirez
Part E. Variance Reduction and Robustness
Introduction	439	(3)
Multiple Sources of Variation: Variance Components	442	(8)
The Importance of Data Transformation in Designed Experiments for Life Testing	450	(13)
C. A. Fung
Is Your Robust Design Procedure Robust?	463	(11)
C. A. Fung
Split Plot Experiments	474	(8)
Robustness in Statistics	482	(6)
Split Plots for Robust Product and Process Experimentation	488	(12)
S. Jones
Designing Products that Are Robust to the Environment--A Response Surface Approach	500	(10)
S. Jones
An Investigation of the Method of Accumulation Analysis	510	(14)
S. Jones
Signal-to-Noise Ratios, Performance Criteria, and Transformations	524	(29)
Part F. Songs	553	(12)
There's No Theorem Like Bayes Theorem	555	(4)
It's Distribution Free	559	(3)
I Am the Very Model of a Profession Statistical	562	(3)
References	565	(20)
Biography	585	(2)
Books and Articles Written by George Box from 1982 to 1999	587	(5)
Index	592