Online multiobjective Pareto optimal dynamic scheduling of semiconductor back-end using conjunctive simulated scheduling

A discrete event simulation based "online near-real-time" dynamic multiobjective scheduling system has been conceptualized, designed, and developed to achieve Pareto optimal solutions in a complex manufacturing environment of semiconductor back-end. Our approach includes the use of linear weighted aggregation optimization approach for multiple objectives and auto simulation model generation for online simulation. Developed concepts are implemented at a semiconductor back-end site and are in use. The impact of the system includes a better customer delivery achievement, consistent cycle time with narrower distribution, improved machine utilization, reduction in the time that planners and manufacturing personnel spend on scheduling, and more predictable and repeatable manufacturing performance. In addition, it enables managers and senior planners to carry out "what now" analysis to make effective current decisions and "what if" analysis to plan for the future.