Conference Description:
This webinar will teach you a methodology to perform experiments in an optimal fashion and review the common types of experimental designs and techniques. You will learn to develop predictive models to describe the effects that variables have on one or more responses and utilize predictive models to develop optimal solutions.
Why Should You Attend:
Experimentation is frequently performed using trial and error approaches which are extremely inefficient and rarely lead to optimal solutions. Furthermore, when it’s desired to understand the effect of multiple variables on an outcome (response), “one-factor-at-a-time” trials are often performed. Not only is this approach inefficient, it inhibits the ability to understand and model how multiple variables interact to jointly affect a response. Statistically based Design of Experiments provides a methodology for optimally developing process understanding via experimentation.
This webinar will review the key concepts behind Design of Experiments. The speaker will present a strategy for utilizing sequential experiments to most efficiently understand and model a process. Many common types of experiments and their applications will be discussed. These include experiments appropriate for screening, optimization, mixtures/formulations, etc. We will introduce several important techniques in experimental design (such as replication, blocking, and randomization). A Case Study involving optimizing a manufacturing process with multiple responses will be presented.
Start Date: 2012-04-10
Last Day: 2012-04-10
Contact Person: Referral
Email: referral@complianceonline.com
Address:
2600 E. Bayshore Road, Palo Alto, California, 94303, United States
Tel: +1-650-620-3915
Fax: +1-650-963-2556
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