An effective dispatching rule for bi-objective job scheduling in a wafer fabrication factory-considering the average cycle time and the maximum lateness

This paper presents an effective dispatching rule to improve the scheduling of jobs in a wafer fabrication factory. Modified from two traditional dispatching rules, the new dispatching rule is aimed at the simultaneous optimization of the average cycle time and the maximum lateness; in practice, this means a promise of delivery to the customer as soon as possible and strict commitment to that promise. This simultaneous optimization has rarely been discussed in the past. The proposed methodology has the following innovative features. First, a highly effective fuzzy-neural approach is applied to estimate the remaining cycle time of a job. Second, the fluctuation smoothing rule for mean cycle time (FSMCT) and the earliest due date (EDD) rule are fused in a nonlinear way to generate the new rule. We also show that there is a contradiction between FSMCT and EDD and establish a certain-rule-first procedure to resolve the contradiction. To assess the effectiveness of the proposed methodology, production simulation is also applied in this study. The experimental results show the proposed methodology is better than some existing approaches at simultaneously reducing the average cycle time and the maximum lateness.