Multifactor Experiment-Design for Process Development | AIChE

Multifactor Experiment-Design for Process Development

Make the most of every experiment. In this webinar, you’ll learn how to catalyze research and development via powerful statistical tools for design of experiment (DOE). Whether you’re a new or experienced experimenter, if you have a basic knowledge of statistics—such as p-values, r-squared and regression modeling—this webinar is for you. Tune in now.

In one hour, you’ll see a demonstration of multifactor DOE testing tools for process development that will accelerate your research and make it a success. Through a series of interactive case studies, you’ll learn how strategically deploying DOE enables you to rapidly screen factors down to a vital few, characterize their main effects and interactions and achieve optimal settings for peak process performance. 

You’ll discover tried-and-true statistical methods, made easy by software, that will empower you to quickly converge on the “sweet” spot—factor settings that meet all product specifications at maximum yield and minimal cost. Learn about response surface methods, RSM, statistical methods and more as you focus on the practical aspects of DOE and how to apply them to get breakthrough results. 

You’ll learn:

     • How to quickly screen down many factors to the vital few

     • How to characterize how factors interact and optimize them

     • How to achieve optimal settings for peak process performance 

     • See what you learn in action in the real world through insightful case studies


Webinar content is available with the kind permission of the author(s) solely for the purpose of furthering AIChE’s & IChemE’s mission to educate, inform and improve the practice of professional chemical engineering. The content reflects the views, opinions, and recommendations of the presenters. AIChE does not warrant or represent, expressly or by implication, the correctness or accuracy of the content of the information presented. All other uses are forbidden without the express consent of the author(s). For permission to re-use, please contact Attendee contact information, including email addresses, will be shared with AIChE and IChemE, with the option to unsubscribe from future communications.

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