We investigate the value of various information exchange mechanisms in a four-echelon supply chain under a material requirements planning framework. In the absence of any information sharing, each echelon would develop its own forecasts and plan its inventories based on the history of actual demand from its downstream customer (or echelon). Through a simulation study, we compare this policy with policies where each echelon has access to (i) the end-user demand history and (ii) the planned order schedule of the downstream echelon. Among all the demand information exchange mechanisms, planning inventories based on the planned downstream order schedules resulted in the lowest average inventory level for the entire supply chain. However, use of end-user demand history to forecast and plan inventories at all echelons resulted in the lowest total cost. In addition to the information exchange mechanisms, a simple synchronized replenishment system was considered and evaluated in the study. In the synchronized system, the retailer determines a fixed order interval and the upper echelons replenish only at integer multiples of this interval. The study found that synchronized inventory replenishments among the echelons, even without any exchange of demand information, can bring about more benefits and cost reduction than any of the information exchange mechanisms.

In this paper we discuss a typical service network of a company providing repair and refurbishment services for its products. To optimise the network we propose a mixed-integer linear programming (MILP) model that minimises the total cost subject to flow balance and logical constraints. The solution of the model determines which facilities are to be used in the network and the associated flows. The model is validated against data obtained from a computer manufacturer and real-life sources. The optimal network configuration depends on several factors such as the number of products returned, percent of faulty products and warranty fraction of modules, which are uncertain in nature. We also address the issue of identifying these uncertain parameters, and their levels to be considered. A min-max robust optimisation model is then developed and solved to address these uncertainties.

Kanban control systems have been around for decades and have been used to control work-in-process of manufacturing systems. Lately many variations of the basic control system have been developed; however, much of the work in the development and comparison of control systems has focused on a single-stage manufacturing system producing a single product type. In this research, we present procedures for optimising multiple product kanban control systems, namely Base Stock, Traditional Kanban Control System and Extended Kanban Control System (both dedicated and shared type). We then conduct a detailed simulation study to compare the performance of the systems using a common total cost measure. Numerical results show that the dedicated and shared-extended kanban control systems outperform the other two systems. The study also shows that in spite of their different schematics and contrary to conventional wisdom, the performance of dedicated and shared-extended kanban control systems doesn’t differ much.