Optimization and Effectiveness of a Production Smoothing Policy in SCM

Abstract

Kanban system has been known to be a superior tool to control complex production and inventory systems operating in the just-in-time (JIT) environment. The kanban system works more effectively at low inventory levels when the consumption rates of parts necessary to produce finished goods are leveled. The parts consumption leveling in JIT systems is called “Heijunka”. In this research, we investigate a multi-stage multi-product production and inventory system in which the production order quantity is exponentially smoothed. The paper presents an efficient algorithm based on simulation to determine the near optimal exponential smoothing factor and safety stock level at each workstation. We use numerical experiments to evaluate the performance of the exponentially smoothed ordering policy in a supply chain as compared to the original kanban system. And also the performance of the two types of optimization methods, global and local optimizations, in the supply chain are compared. We conclude that the locally optimized production smoothing is quite effective as a production and material replenishment ordering policy as an SCM.