Procedia Computer Science
3rd International Conference on Industry 4.0 and Smart Manufacturing
In addition to stresses induced by the Covid-19 pandemic, supply chains worldwide have been growing more complex while facing a continuous onslaught of disruptions. This paper presents an analysis and extension of a graph based model for modeling and simulating the effects of such disruptions. The graph based model combines a Bayesian network approach for simulating risks with a network dependency analysis approach for simulating the propagation of disruptions through the network over time. The initial analysis provides evidence supporting extension to for using a multi-layered approach allowing for the inclusion of cyclic features in supply chain models. Initial results for individual layers and the aggregate model are presented and discussed. The paper is concluded with a discussion and recommended directions for future work.
Original Publication Citation
Smith, K., Diaz, R., & Shen, Y. (2022). Development of a framework to support informed shipbuilding based on supply chain disruptions. Procedia Computer Science, 200, 1093-1102. https://doi.org/10.1016/j.procs.2022.01.309
0000-0002-5026-4501 (Smith), 0000-0002-8637-5967 (Diaz)
Smith, Katherine; Diaz, Rafael; and Shen, Yuzhong, "Development of a Framework to Support Informed Shipbuilding Based on Supply Chain Disruptions" (2022). VMASC Publications. 67.