Dynamic scheduling for complex engineer-to-order products

Abstract

The current paper considers dynamic production scheduling for manufacturing systems producing products with deep and complex product structures and complicated process routings. It is assumed that manufacturing and assembly processing times are deterministic. Dynamic scheduling problems may be either incremental (where the schedule for incoming orders does not affect the schedule for existing orders) or regenerative (where a new schedule is produced for both new and existing orders). In both situations, a common objective is to minimize total costs (the sum of work-in-progress holding costs, product earliness and tardiness costs). In this research, heuristic and evolutionary-strategy-based methods have been developed to solve incremental and regenerative scheduling problems. Case studies using industrial data from a company that produces complex products in low volume demonstrate the effectiveness of the methods. Evolution strategy (ES) provides better results than the heuristic method, but this is at the expense of significantly longer computation times. It was found that performing regenerative planning is better than incremental planning when there is high interaction between the new orders and the existing orders.