Using simulation and hybrid sequencing optimization for makespan reduction at a wet tool

When rigid scheduling rules apply to wet tools, the development of Cycle Time (CT) optimization strategies becomes a relevant challenge. The impact of sequencing optimization on makespan performance at a wet tool is investigated here by means of a hybrid optimization model that combines an exact optimization approach, based on an efficient permutation concept, and a heuristics, based on Genetic Algorithms (GAs). The model also includes a scheduling module that reproduces the control logics governing wet tools operating in a real semiconductor manufacturing plant and proves effective in generating efficient and detailed schedules in short computational times. The realistic assumptions on which the scheduling module is based allow the simulation of different tool configurations. The results obtained show that significant makespan reductions can be achieved by means of a mere sequencing optimization as parallel processing within the wet tools is better exploited.