Intelligent simulation-based lot scheduling of photolithography toolsets in a wafer fabrication facility

Scheduling of a semiconductor manufacturing facility is one of the most complex tasks encountered. Confronted with a high technology product market, semiconductor manufacturing is increasingly more dynamic and competitive in the introduction of new products in shorter time intervals. Photolithography, being one of the processes repeated often, is a fabrication bottleneck. Lot scheduling within photolithography is a challenging activity where substantial improvements in factory performance can be made. The proposed scheduling methodology integrates two common approaches, simulation and artificial intelligence. Using detailed simulation modeling within a structured modeling method, a comprehensive model to characterize the photolithography process was developed. An artificial intelligence scheduler was then developed and integrated with the model with the goal of reducing work-in-process (WIP), setup time, and throughput time. The results have shown a significant improvement in lot cycle time as well as tool utilization, improved the throughput time by an average of 15% and is currently in use for scheduling the photolithography process.