Abstract

The supply chain networks could be very fragile in global environment due to unexpected events such as emergencies, normal disruptions and industrial accidents. The supply chain members may lose their production capacities temporarily, which might have significant impacts on the performance of the whole supply chain network. This article proposes a discrete time model to characterise the unreliable production capacity in serial supply chain networks. Based on the proposed model, the exact probability distributions are available for the performance analysis of a single-stage system in the lost sales scenario. The iterative methods are developed to derive the approximate performance measures for single-stage systems in the backorder scenario and multi-stage systems in both the lost sales and backorder scenarios. The proposed methods are verified through a series of numerical experiments. The analysis results suggest that the performance of the supply chain network suffers more from the downstream-stage unreliability than the upstream-stage unreliability. Furthermore, some application examples are illustrated to show the possible solutions for practical problems.

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