A multiobjective approach to manufacturing process optimization is described. This approach places no restriction on the type or number of performance criteria and no a priori weights need be chosen for it since performance criteria are not combined into a single objective function. An algorithm is implemented that runs in real-time and provides immediate feedback to a process operator about the current operating point. If the current operating point is not Pareto optimal, the algorithm automatically adjusts the parameters to achieve this. If it is Pareto optimal but not desirable, the algorithm can provide information on how tradeoffs can be made so that the desired operating point is achieved. The algorithm was applied to the tuning of process inputs for the plastication and injection phases of an injection molding process. The optimization took place with respect to three quality characteristics: cycle time, flashing, and underfill. Measurement of flashing and underfill was done by the operator and both binary and fuzzy techniques were used. The algorithm was used to tune the process online, and experimental results are presented.>
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Seaman et al. (1993) studied this question.
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