September 2009 Dinner and Education Meeting

Statistical Design of Experiments (DOE) is a powerful tool for researchers to use to better understand and optimize every aspect of their products – their ingredient types and levels, their process set points and their packaging characteristics. DOE can be used effectively at every stage of the product develop cycle. Early on it can be used to efficiently identify the ingredients, process parameters and packaging variables that impact the quality of the finished product. That allows researchers to focus on high-impact variables and to avoid wasting time on studying variables that have little or no impact on the quality of the product. Later in the development cycle, DOE can be used to understand on multiple variables work together to deliver synergistic benefits (or antagonistic detriments) to the product. A successful is more than the sum of its parts. Understanding how the product variables interact with each other is crucial to developing highly successful products. Ultimately , DOE can be used to identify the ingredient levels, process conditions and packaging characteristics that will deliver optimal product performance. DOE identifies the optimal conditions and the sensitivity of the product to deviations from the optimal conditions. This allows developers to understand how to achieve the best compromise, for example, of maximum consumer satisfaction with maximum efficacy and optimal stability while at the same time staying within the practical constraints imposed by regulatory and cost factors.

The talk will present practical examples of each of these applications of DOE. The examples will be used to illustrate the advantages DOE provides over other research approaches and will be used to dispel some of the myths about the weaknesses and disadvantages of DOE.
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