Abstract
Optimization of process parameters for meeting the stringent quality requirements in injection molding has been studied via utilization of CAE simulations or design of experiments for many years. In this paper, a multi-objective optimization scheme for product quality control based upon quality engineering methodologies is presented. According to the theoretical analysis, the main advantages of the proposed scheme are the versatility on performance criteria and the flexibility on various quality requirements. In addition, the optimization goals can be achieved at near optimal process conditions implemented with Inverse Neural Optimal Control System method. The scheme has been carefully verified by test cases conducted with numerical simulations. Concluded from the process control simulations, the deviations on total-loss at the current process conditions can be compensated with new process parameters calculated based upon the scheme for meeting the optimization criteria. Finally, the proposed scheme would have to be tested on practical cases on the shop floor for applicability and performance evaluations in the future.