Systematic design an intelligent simulation training system: from learn-memorize perspective

Abstract

Intelligent manufacturing provides a wide range of benefits such as optimizing production system via the behavioral instructions of cyber-physical system (CPS). Yet successful intelligent manufacturing is confronted with various challenges, such as executing specific behaviors in right way and right time. The current research aims to prevent intelligent manufacturing from being affected by human factors. To this end, an innovative learn-memorize matrix model is proposed and the platform of “Ball Reposition” logic flow with “Machine 2C” in “Wire Bond process” (WB_2C_M1 Process) in IC assembly is applied for talent training. As revealed by experiment findings, although seniority does not impact the execution frequency of “decomposition of movements” in simulation learning, it does impact the operation duration of “full process” for learning this logic process, and the execution frequency of “decomposition of movements” impacts the operation duration of “full process” in low-seniority group. Moreover, for learners’ learning processes, individual customized follow-up learning programs can be offered based on control-charts evaluation and knowledge evaluation matrix. With the intelligent simulation training system, it helps to cultivate professional technicians in intelligent manufacturing.