Case Studies and White Papers

Published: November 2014
Author: Wilhelm Kleppman

Learn how DoE can help save time and money in process design and optimization with this primer.

Publication: Chemical Engineering

Published: June 2014
Author: OMG Borchers

OMG Borchers used the design of experiments method to develop a mixture experiment to screen the effects of four candidate additives. The challenge was to find a second source for an associative thickener used in a family of waterborne coatings that matched the properties of the incumbent thickener in three different classes of products with a different chemical composition than the incumbent.

Publication: Paint & Coatings Industry

Published: June 2014
Author: Ron Stites

An industrial equipment supplier wanted to find the best operating conditions, as well as determine what performance its product could deliver for ethanol producers, before putting the device on the market. A DOE was run to successfully identify and validate a measurement method that has enabled the supplier to accurately evaluate the performance of the new product in a large number of plants under a wide range of operating conditions.

Publication: Ethanol Producer Magazine

Employing Power to "Right-Size" Design of Experiments

Published: March 2014
Authors: Mark Anderson, Patrick Whitcomb

This article provides insights on how many runs are required to make it very likely that a test will reveal any important effects. Due to the mathematical complexities of multifactor design of experiments (DOE) matrices, the calculations for adequate power and precision are not practical to do by 'hand' so the focus is kept at a high level--scoping out the forest rather than detailing all the trees. By example, reader will learn the price that must be paid for an adequately-sized experiment and the penalty incurred by conveniently grouping hard-to-change factors.

Publication: The ITEA Journal

Published: March 2014
Authors: Mark Anderson, Patrick Whitcomb

Due to operational or physical considerations, standard factorial and response surface method (RSM) design of experiments (DOE) often prove to be unsuitable. In such cases a computer-generated statistically-optimal design fills the breech. This article explores vital mathematical properties for evaluating alternative designs with a focus on what is really important for industrial experimenters. To assess “goodness of design” such evaluations must consider the model choice, specific optimality criteria (in particular D and I), precision of estimation based on the fraction of design space (FDS), the number of runs to achieve required precision, lack-of-fit testing, and so forth. With a focus on RSM, all these issues are considered at a practical level, keeping engineers and scientists in mind. This brings to the forefront such considerations as subject-matter knowledge from first principles and experience, factor choice and the feasibility of the experiment design.

Publication: Journal of Statistical Science and Application

Improved Copper and Gold Recovery at KGHM International’s Robinson Mine

Published: January 2014
Authors: Lorin Redden, Chase Stevens, Mark O'Brien, Thomas Bender

In an effort to recover additional copper and gold at KGHM International's Robinson Mine located near Ruth, Nevada, an in-plant study was undertaken to quantify potential flotation recoveries from the concentrator's final tailings stream. Tests were conducted by passing a small continuous sample of final tailings through a single 1.5 m3 FLSmidth XCELL™ demonstration flotation machine. This paper reviews the results obtained from the in-plant testing with the single 1.5 m3 flotation cell and provides a comparison to the subsequent operational performance of multiple 160 m3 flotation machines

Published: August 2013
Authors: Yahya Kaya, Greg Piepel, Erdal Caniyilmaz

Experimental design, modeling, and data analysis methods for mixture experiments provide for efficiently determining the component proportions that will yield a product with desired properties. This article presents a case study of the work performed to develop a new rubber formulation for an o-ring (a circular gasket) with requirements specified on 10 product properties. Progress in Rubber, Plastics and Recycling Technology, Vol. 29, No. 3, 2013

Note: If interested, you may contact one of the authors, Greg Piepel, Ph.D., for a copy of the paper.

Publication: Progress in Rubber, Plastics and Recycling Technology

Published: July 2013
Author: Steve Collier

Researchers improved the performance of an isolated ketoreductase (KRED) enzyme using directed evolution, and also performed two stages of design of experiments (DOE) to identify and optimize key process variables.

Publication: Pharmaceutical Manufacturing

Published: June 2013
Author: Cheryl Scott

Design of experiments (DoE) incorporates statistical methods and multivariate analysis into microscale chemistry. Controlled experiments help analysts evaluate processes with that involve several variables, such as temperature and osmolality in cell culture processes. Often three variables are studied together, with the results expressed in a three-dimensional response-surface graphs.

Publication: BioProcess International

Published: February 2013
Author: Sara Black

Resin manufacturer Interplastic Corp. Thermoset Resins Div. (St. Paul, Minn.), a major gel coat producer, recently developed a new gel coat with the aid of Design-Expert design of experiments software from Stat-Ease Inc.

Publication: Composites Technology