Case Studies and White Papers


Published: May 2012
Author: Wilson Collier

Researchers at Codexis Laboratories Singapore performed a full-factorial designed experiment with 20 runs to determine the impact of four independent variables on product selectivity during a silylation reaction. The result was a process that delivered 95% selectivity along with an 88% yield.

Publication: Pharmaceutical Manufacturing

Published: March 2012
Authors: Patrick Whitcomb, Mark Anderson

Given the push for Quality by Design (QbD) by the US FDA and equivalent agencies worldwide, statistical methods are becoming increasingly vital for pharmaceutical manufacturers. Design of experiments (DOE) is a primary tool because “it provides structured, organized method for determining the relationship between factors affecting a process and the response of that process." Tolerance intervals (TI) verify that the design space will be robust for meeting the manufacturing specifications on every individual unit, not just on average.

Publication: Special Issue Article featuring a paper presented at 11th Annual ENBIS Conference

Published: March 2012
Authors: Zhou Jiang, Kurt Droms, Zhaohui Geng, Susan Casnocha, Zhihua Xiao, Steve Gorfien, Scott Jacobia

Researchers aiming to upgrade a fed-batch process observed that basal and feed media have interrelated impacts on process outcomes (a pairing effect). They did a DOE enabled by Design-Expert software for fed-batch cell culture process optimization.

Publication: BioProcess International

Published: January 2012
Authors: David Stiles, Zhiming Zhang, Pei Ge, Brian Nelson, Richard Grondin, Yi Ai, Peter Hardy, Peter Nelson, Andrei Guzaev, Mark Butt, Klaus Charisse, Verbena Kosovrasti, Lubomir Tchangov, Michael Meys, Martin Maier, Lubomir Nechev, Muthiah Manoharan, William Kaemmerer, Douglas Gwost, Gregory Stewart, Don Gash, Dinah Sah

This article explores a therapeutic strategy for treating Huntington's disease.

Publication: Pharma Qbd

Design of Experiments for Non-Manufacturing Processes: Benefits, Challenges, and Some Examples

Published: November 2011
Authors: Mark Anderson, Jiju Antony, Shirley Coleman, Rachel Johnson, Douglas Montgomery

Design of experiments (DOE) is a powerful technique for process optimization that has been widely deployed in almost all types of manufacturing processes and is used extensively in product process design and development. There have not been as many efforts to apply powerful quality improvement techniques such as DOE to improve non-manufacturing processes. Factor levels often involve changing the way people work and so have to be handled carefully. It is even more important to get everyone working as a team. This paper explores the benefits and challenges in the application of DOE in non-manufacturing arena.

Publication: Journal of Engineering Manufacture

Design-Expert Diagnostics Saves Experiment (and Post-Grad Student)

Published: August 2011
Author: Paul Mullenix

See how the diagnostic features of Design-Expert enabled a post-doctoral researcher to achieve a valid analysis, and graduate on time. Lesson learned: Checking diagnostics just might save your next experiment.

Published: July 2011
Author: DE Editors

The TRW team used a combination of DOE (response surface methodology RSM) and Monte Carlo analysis to optimize a braking system where one of the objectives was to quickly generate pressure when demanded by the vehicle stability control system.

Publication: Digital Engineering

Published: April 2011
Author: F.L. Smidth

FLSmidth recently installed two turnkey SuperCell flotation machines the world's largest flotation cells at Rio Tinto's Kennecott Utah Copper concentrator near Salt Lake City, Utah. They used DOE to substantially reduce the amount of testing and fine-tuning required after installation.

Publication: E&MJ Engineering & Mining Journal

Published: March 2011
Author: Jerry Fireman

RTP Company, which compounds custom engineered thermoplastics, used Design-Expert software to determine which injection molding process conditions would optimize conductive properties for a particular material. Their DOE made it possible to explore the complete processing space and provided users with a formula to calculate the conditions that would deliver the required resistivity levels.

Publication: Injection Molding/Plastics Today

Published: March 2011
Authors: Francesco Tinazzi, Giuseppe Guercio

In this presentation design of experiments (DOE) was applied to a chemical process. DOE together with computer modeling lead to a better understanding of the process and the defining of new conditions.

Publication: ENBIS-11