Abstract for: Simulation Framework to Quantify Supply Chain Resilience

There has been a recent focus on supply chain resilience due to various social/ technical/ political situations worldwide that have significantly disrupted supply chain operations. Supply chain resilience is defined as the ability of the supply chain to recover quickly from disruptions. This study uses cost, time, and quantity based metrics to quantify supply chain resilience. A generic two-level supply chain model is considered. A system dynamics model based on a generic two-echelon inventory-production supply chain is developed to simulate deterministic disruptions. The impact of supply, dispatch, production, and capacity reduction disruptions is analyzed. The effectiveness of backup suppliers and logistics strategies is modeled and evaluated in recovering from these disruptions. All resilience metrics deteriorate the supply chain performance during disruptions. However, implementing resilience strategies significantly improves the recovery and overall resilience of the supply chain. The upstream disruptions have more impact than downstream disruptions, indicating the need for robust supplier contingency planning. The findings suggest that timing to implement a resilient strategy is important, as delayed implementation but with short backup lead times results in better overall resilience. Although backup strategies increase resilience, they also bring about cost-based trade-offs that require a balanced approach to ensure an efficient and resilient supply chain.