Abstract
A discrete event simulation-based 'on-line near-real-time' dynamic multiobjective scheduling system has been conceptualized, designed, and developed to achieve Pareto optimal solutions in a complex manufacturing environment. Our approach includes the use of a linear optimization algorithm with multiple objectives and auto simulation model generation. Manufacturing is one of the most complex elements of the supply chain and we focus on manufacturing to demonstrate the capability that may be extended in future to the entire supply chain. We have implemented the system at a semiconductor back-end site to test our solutions. The impact of the system includes the achievement of world class cycle time, improved machine utilization, reduction in the time that planners and manufacturing personnel spend on scheduling, and more predictable and highly repeatable manufacturing performance. In addition, it enables managers and senior planners to carry out 'what if' analysis to plan for the future.
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