An Intelligent Decision Support System for Part Launching in a Flexible Manufacturing System

The effective control of flexible manufacturing systems (FMS) poses a major challenge to designers and the research community. In this paper, the framework of a unique decision support system to assist in the control of a FMS through intelligent part-launching is introduced. The proposed system makes usr of a new heuristic method based on the pull concept, and a neural network trained with data from a system simulation model, which in turn provides a desision about choosing a part to be launched into the FMS. The performance of the proposed heuristic method was tested against another popular heuristic method normally used in existing FMS via discrete event simulation models. Data sets from the simulation program of the proposed system were used to train the neural network, which can be used on the shop floor for realtime decision support. The output from the trained neural network is based on the same principle as the proposed heuristic method used in the simulation program. Therefore, the descision support provided by the neural network can be used for improved shop floor control.