Modeling Risk Prioritization of a Manufacturing Supply Chain using Discrete Event Simulation.

Supply chains face a myriad of adverse risks that impact their daily operations and make them vulnerable. In addition, supply chains continue to grow in size and complexity which further sophisticates the problem. Lack of a structured approach and limitations in existing risk management methods contribute towards effective mitigation strategies not being properly developed. In this paper, we develop a discrete event simulation modelling approach to quantify the performance and risk assessment of a manufacturing supply chain in Sweden which is under the impact of risks. This approach could support decision makers by prioritizing risks according to their performance impact and facilitating the development of mitigation strategies to enhance the resilience of the supply chain. The conceptual digital model can also be used to generate synthetic data to build an artificial intelligence-enhanced predictive demonstrator model to showcase capabilities for building data-driven resilience of the supply chain.