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Process Optimization for Multiple Responses Utilizing the Pareto Front Approach

ABSTRACT In many optimization situations, there are several responses associated with a product or process that need to be jointly considered. In this article we present Pareto front multiple objective optimization as an option to complement other statistical and mathematical methods in the response surface methodology toolkit. We demonstrate the Pareto front approach for multiple response process optimization based on evaluating a fine grid of input variable combinations within the range of operating conditions, as well as the use of a set of graphical tools to aid in decision making, with an example process involving two inputs and three responses of interest. We also discuss a simple way to examine the impact that variability in the responses can have on the solution by considering the estimated mean and worst-case response values. R code for implementing the methods discussed in this article is available upon request (jchapman@stlawu.edu).