Integration of CAE Modeling and Artificial Intelligence Systems to Support Manufacturing of Plastic Microparts

Micrometer-scale parts requirements demand an improvement of the development of the micro-manufacturing industry. This fact is due to current technological advances which require small parts with more complex geometrical characteristics, microparts with more precise dimensional characteristics, microparts with better quality aspect and microparts with improved quality operating characteristics. Therefore, the manufacturing processes to obtain high quality microinjection parts is increasingly complicated, requiring much more time (a greater number of cycles) and knowledge from the expert operator, which makes the process unprofitable, as well as highly dependent of the operator and increasing the final costs of microinjection parts for the user. This paper presents the development of an artificial intelligence system based on the integration of CAE modeling, with fuzzy logic techniques and neural networks techniques to support the operator of the injection machine on the selection of optimal machine process parameters to produce good quality microparts in fewer process cycles. Tests performed with this intelligent integration system development have demonstrated 30% improvement in the efficiency of injection processes.