Designed Experiments (DOEs) are the most efficient way to learn about a system. So, why isn’t everybody using DOE? Common responses to this question are “I first want to get a feel for this system” or “it wouldn’t work in this situation”. If this is something that you have heard, or tell yourself, join the experts from JMP to learn how DOE has evolved to allow for custom experiments that can unlock insights into complex systems.

DOE is a structured approach to study the relationships between multiple input factors and key outputs. This sounds like something any scientist would want to use, but most experimental approaches explore one-factor-at-a-time. This method appears structured but often results in not finding true relations between variables or misleading results.

During the session, learn how DOE successfully overcame several diverse chemical industry situations that resulted in time and resource savings, scientific breakthroughs, and financial benefits.

Key Learning Objectives:

  • Screening designs for understanding complex polymerization kinetics
  • Specialized designs for evaluating raw materials used in consumer product formulations
  • DOEs that optimize pharmaceutical and resin formulations
  • A new class of Designs that can optimize chromatography method development

Designed Experiments (DOEs) are the most efficient way to learn about a system. So, why isn’t everybody using DOE? Common responses to this question are “I first want to get a feel for this system” or “it wouldn’t work in this situation”. If this is something that you have heard, or tell yourself, join the experts from JMP to learn how DOE has evolved to allow for custom experiments that can unlock insights into complex systems.

DOE is a structured approach to study the relationships between multiple input factors and key outputs. This sounds like something any scientist would want to use, but most experimental approaches explore one-factor-at-a-time. This method appears structured but often results in not finding true relations between variables or misleading results.

During the session, learn how DOE successfully overcame several diverse chemical industry situations that resulted in time and resource savings, scientific breakthroughs, and financial benefits.

Key Learning Objectives:

  • Screening designs for understanding complex polymerization kinetics
  • Specialized designs for evaluating raw materials used in consumer product formulations
  • DOEs that optimize pharmaceutical and resin formulations
  • A new class of Designs that can optimize chromatography method development

About the Presenters

Monique Roerdink Lander, JMP Statistical Discovery

Monique Roerdink Lander is a Systems Engineer for JMP. As such, she is the technical contact for users and prospective users, providing training on how to do things in JMP. Monique has a doctorate in materials science and technology of polymers from the University of Twente in the Netherlands. Prior to joining JMP, Monique spent more than a decade in product development in R&D for Ecolab, most recently as a Senior Staff Scientist. A JMP user for a decade, she has more than 20 peer-reviewed papers and patents.


Scott Allen, JMP Statistical Discovery

Scott Allen is a Senior Systems Engineer at JMP Statistical Discovery, supporting customers in the Ohio Valley region of the United States. Scott has more than 14 years of experience in product and process development for catalysis, chemistry, polymers, and sustainable technologies. Before joining JMP, in his role as an R&D and product development leader, he was a strong advocate for data-driven decision making and the use of statistics and design of experiments (DOE) to accelerate innovation and product development. In his current role, Scott enjoys helping customers explore their data and develop their capabilities in DOE and predictive modeling. He received his PhD in chemistry from Cornell University and a bachelor's in chemistry from Virginia Commonwealth University.


PRESENTED IN PARTNERSHIP WITH C&EN Media Group.

This virtual webinar was moderated by Melissa O'Meara, Forensic Science Consultant with C&EN Media Group. On-demand event now available courtesy of a joint partnership with C&EN Media Group.
Visit C&EN Media Group at https://cen.acs.org/index.html

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