Case Studies and White Papers

Published: October 2006
Authors: Patrick Whitcomb, Mark Anderson

This mini-paper, provided on pages 5-8 in the publication via the link above*, addresses concerns about mixture designs coming up short on power. *(Manuscript available under Download link below.)

Publication: ASQ Statistics Division Newsletter

DOE for Coatings

Published: August 2006
Authors: Mark Anderson, Patrick Whitcomb

This article provides an introduction to design of experiments (DOE) for improvement of coatings processes and formulations. It includes a case study on a spin-coater.

Publication: Coatings Technology Handbook, 3rd Edition

Trimming the FAT: Part II

Published: September 2005
Author: Mark Anderson

The first article, "Trimming the FAT out of Experimental Methods," presented arguments against one-factor-at-a-time (OFAT) techniques in favor of multifactor DOE. This follow-up article offers a case study that illustrates how a two-level factorial DOE can reveal a breakthrough interaction. A similar article appeared in OE (Optical Engineering) magazine.

Publication: Optical Engineering

Trimming the FAT out of Experimental Methods

Published: June 2005
Author: Mark Anderson

This introductory article provides compelling reasons to abandon traditional scientific methods that deploy only one factor at a time (OFAT) in favor of multifactor testing techniques known as design of experiments (DOE). Only via DOE can experimenters detect interactions, which often prove to be the key to success.

Publication: Optical Engineering

Screening Process Factors In The Presence of Interactions

Published: May 2004
Authors: Mark Anderson, Patrick Whitcomb

This article introduces a new, more efficient type of fractional two-level factorial design of experiments (DOE) tailored for the screening of process factors. These designs are referred to as Min Res IV.

Publication: AQC 2004 Toronto

Success with DOE

Published: April 2004
Author: Mark Anderson

A basic primer, taken from "DOE Simplified" text, on underlying statistics and simple forms of DOE.

Publication: Quality

Practical versus Statistical Aspects of Altering Central Composite Designs

Published: July 2003
Author: Mark Anderson

For many central composite designs (CCDs), particularly large ones, the usual alphas put the axial points outside the region of operability. A CCD with an alpha of one, known as a "face centered design" (FCD), avoids this problem by drawing the axial point back onto the face of the hyper cube. However, as the number of FCD factors increase, the correlation among the squared terms in the quadratic in the face-centered cube also increases. For k>5 this causes the variance inflation factors (VIFs) associated with the squared terms to become quite high. As a compromise between FCD and standard CCD, this white paper provides the case for a "practical" alpha of the fourth root of the number of factors (k). For k of 5 or more, this practical alpha balances statistical properties with operational necessities.

Publication: 2003 Joint Statistical Meetings Roundtable Luncheon

How to Use Graphs to Diagnose and Deal with Bad Experimental Data

Published: May 2003
Authors: Mark Anderson, Patrick Whitcomb

This article deals with thorny issues that confront every experimenter how to handle individual results that do not appear to fit with the rest of the data. (A somewhat modified version of this article was published in Quality Engineering. April 2007.)

Publication: ASQ Kansas City Annual Quality Congress

Augmented Ruggedness Testing to Prevent Failures

Published: May 2003
Author: Mark Anderson

Failures in the processing and use of products can often be prevented by applying a form of DOE called ruggedness testing. Check out this article to see how it's done for machine-made bread.

Publication: Quality Progress

Published: February 2003
Authors: Mark Anderson, Shari Kraber

This article explains why standard factorial designs (one array) offer a cost-effective alternative to parameter designs (two array) made popular by Taguchi. It then discusses advanced tools for robust design that involve application of response surface methods (RSM) and measurement of propagation of error (POE).

Publication: Paint & Coatings Industry