Selection of process and design variable settings under multiple performance measures in injection molding

Injection molding (IM) is one of the most prominent processes for mass-producing plastic products. Selecting the proper settings for an IM process is crucial because the behavior of the polymeric material during shaping is highly influenced by the process variables. Consequently, the process variables govern the quality of the part produced. In order to obtain the variable settings that result in the best balances between key quality performance measures, Data Envelopment Analysis (DEA) was used to solve the respective multiple objective criteria problem using empirical models as surrogates. In addition, a DEA modification is explained here with the objective to further screen efficient solutions. Finally, practical cases containing only a subset of performance measures were analyzed to illustrate customized analysis and to illustrate how to identify robust process settings.