Fast Approximations for Dynamic Behavior in Manufacturing Systems With Regular Orders: An Aggregation Method

Abstract

Both manufacturing systems and inventory models have received substantial research attention, but they are mainly investigated independently without considering their interactions. In fact, from the supply chain network perspective, manufacturing systems and warehouses may interact. This article considers the manufacturing systems with regular orders. In addition to machines and work-in-process buffers usually considered in current literature, a finished goods buffer is added to the manufacturing system to store the final products. For a fixed shipping period, a certain amount of products are shipped to the customers. For these systems, the production process and inventory level may fluctuate when goods are shipped. As a result, they are in dynamic modes in part or all the processing cycles, and an unacceptable error occurs when employing the steady-state analysis algorithm. Therefore, this article develops effective algorithms for analyzing the dynamic behavior in manufacturing systems with regular orders. Specifically, the system with one machine and finished goods buffer isolated from the manufacturing system is first modeled and estimated. Then, based on it, we proposed an aggregation method, which can be employed in larger systems. The approach substantially decreases the state space of the problem and leads to the modeling and estimation of the system solvable. Numerical experiments show that the proposed methods maintain high accuracy.