Analysis of Performance of Fuzzy Logic-Based Production Scheduling by Simulation

In this paper, a new fuzzy logic-based approach to production scheduling in the presence of uncertain disruptions is presented. The approach is applied to a real-life problem of a pottery company where the uncertain disruption considered is glaze shortage. This disruption is defined by two parameters that are specified imprecisely: number of glaze shortage occurrences and glaze delivery time. They are modelled and combined using standard fuzzy sets and level 2 fuzzy sets, respectively. A predictive schedule is generated in such a way as to absorb the impact of the fuzzy glaze shortage disruption. The schedule performance measure used is makespan. Two measures of predictability are defined: the average deviation and the standard deviation of the completion time of the last job produced on each machine. In order to analyse the performance of the predictive schedule, a new simulation tool FPSSIM is developed and implemented. Various tests carried out show that the predictive schedules have good performance in the presence of uncertain disruptions.