Methodology for supply chain disruption analysis

Abstract

Given the size, complexity and dynamic nature of many supply chains, there is a need to understand the impact of disruptions on the operation of the system. This paper presents a network-based modelling methodology to determine how changes or disruptions propagate in supply chains and how those changes or disruptions affect the supply chain system. Understanding the propagation of disruptions and gaining insight into the operational performance of a supply chain system under the duress of an unexpected change can lead to a better understanding of supply chain disruptions and how to lessen their effects. The modelling approach presented, Disruption Analysis Network (DA_NET), models how changes disseminate through a supply chain system and calculates the impact of the attributes by determining the states that are reachable from a given initial marking in a supply chain network. This ability will permit better management of the supply chain and thus will allow an organization to offer quicker response times to the customer, lower costs throughout the chain, and to the end customer higher levels of flexibility and agility, lower inventories throughout the chain (both with work-in-process and inventories), lower levels of obsolescence and a reduced bullwhip effect throughout the chain. This is of particular benefit in large-scale systems, since it can give the user the ability to perform detailed analysis of a dynamic system without the computational burden of a full-scale execution of the model. Consequently, the model may then be segmented to evaluate only the portions or sub-networks that are affected by changes in an initial marking.

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