Recent research efforts have focused on the method of order release as an effective operations management tool. This research indicates that it is possible to design a robust Kanban-Like PCS for multi-product manufacturing systems with erratic demand. It is shown that BK- CONWIP operating S-KAP will outperform both Kanban and CONWIP, which both operate D-KAP. We then explore how the line performs under these settings to changing demand profiles. Simulation based optimisation has been utilised to determine the optimal control parameters for BK-CONWIP. This paper is aimed to test this strategy by application to a real manufacturing case study of a four-product system with erratic demand. Recently, we proposed a new PCS called Basestock Kanban-CONWIP (BK-CONWIP) Control Strategy (BK-CONWIP) that has the capability to operate S-KAP in a multi-product environment, minimising inventory and backlog while maintaining volume flexibility. Kanban, CONWIP and Basestock cannot operate S-KAP naturally, owing to tight coupling between the work authorisation cards and the demand information. However, many Kanban-Like PCS that have been shown to be successful in single product environments e.g. Rather, when demand/production volume shifts away from one product to another then the line can begin allocating Kanbans accordingly and therefore maintain volume flexibility. The benefit of this shared policy is that it is not necessary to maintain semi-finished and finished inventories of every product in the line. Recently, a Kanban Allocation Policy that allows product types to share Kanbans has been proposed in the literature. This can result in line congestion, long lead times and low throughput rate. Organisations that adopt Pull-type Production Control Strategies, such as Kanban, for multi-product lines find that is necessary to plan high Kanban Card allocations in order to maintain volume flexibility to manage uncertainty in demand. Managing uncertainties in demand variability in a multi-product manufacturing environment is difficult and complex in nature.
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