Simulation optimization-based decision support tool for steel manufacturing

To buffer against increasing global competition and variability in the price of raw materials, steel manufacturers continuously strive to improve operations and lower costs. In this research, we employ a simulation optimization approach to develop a decision support tool to aid in strategic and operational decision-making. Specifically, we investigate work-in-process inventory levels and potential manufacturing process modifications to reduce utilization costs. A simulation model captures the complex nature of the system while an optimizer searches the solution space and sends trial solutions to the simulation for evaluation. Experimentation suggests that significant daily cost savings are possible by modifying current inventory practices and production process capabilities. Overall, the work demonstrates the ability of the solution approach to analyze complex industrial systems and identify potential improvements in a short time frame.