This paper proposes a dynamic tailored nonlinear fluctuation smoothing (TNFS) rule to improve the performance of job dispatching in a wafer fabrication factory (wafer fab). The rule is modified from Chen's tailored nonlinear fluctuation smoothing (TNFS) rule with some innovative treatments. First, the remaining cycle time of a job to be scheduled is estimated with the self-organization map (SOM)-radial basis function network (RBF) approach instead to improve the accuracy. Second, in the original TNFS rule, the adjustable factor is static, while in this system it becomes dynamic. To evaluate the effectiveness of the proposed methodology, production simulation was also applied in this study. According to experimental results, the proposed methodology surpassed some existing approaches in reducing both the average cycle time and cycle time variation.
|Number of pages||6|
|Journal||International Review on Computers and Software|
|State||Published - 1 May 2011|
- Tailored nonlinear fluctuation smoothing
- Wafer fab