Development of a rule-based inference- Oriented FMS dispatcher using the JESS platform

Along with the global changes in market conditions as well as the impact of competition, how to respond quickly to the fluctuations of market demand is an important task for commercial enterprises. A Flexible manufacturing system (FMS) is one efficient solution to solve this problem. FMS can provide the flexibility to change product mix or routes to ensure that results fit production demands. But, once the whole system has been built up, it is costly and difficult to change specialized, automated machines, tooling and software, retrain unskilled operators, stop a high-speed line for a few weeks to make changes. In this paper, the combination of the rule-based inference engine system and FMS is mainly aimed at addressing this problem by proposing a dynamic shop floor control and dispatching model. In the past, the analysis of dispatching rules was based on the experiences and skills of process or IE engineers. Now, The solution allows them to construct, manage and maintain rules easily and flexibly to adapt to ever-changing production requirements via the user-friendly interface and the inference mechanism. Hence, engineers do not need to rewrite the dispatching programs and thus they reduce their workloads. Through the rule base, process-related knowledge and experience can be created, accumulated, shared and reused. This solution can not only help production engineers plan jobs sequences based on the order requirement and equipment status, but it can also increase the speed and flexibility of arranging jobs when the production process changes. A FMS prototype is used as the test platform to demonstrate the feasibility and capability of this solution in supporting intelligent dispatching and production.