An artificial neural network driven decision-making system for manufacturing disturbance mitigation in reconfigurable systems

Abstract

Reconfigurable manufacturing systems are susceptible to disturbances because of the characteristics associated with changeover of machine configuration and functionality. An Artificial Neural Network Driven Decision-Making System can mitigate these disturbances, if applied with extensive knowledge of the manufacturing system. This paper introduces a new concept into the paradigm of agile manufacturing that address live, autonomous, disturbance and underperformance mitigation. The mitigation system and its prerequisite research is described and a testing methodology is proposed.