Document Type
Article
Publication Date
2022
DOI
10.1016/j.procs.2022.01.309
Publication Title
Procedia Computer Science
Volume
200
Pages
1093-1102
Conference Name
3rd International Conference on Industry 4.0 and Smart Manufacturing
Abstract
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
ORCID
0000-0002-5026-4501 (Smith), 0000-0002-8637-5967 (Diaz)
Repository Citation
Smith, Katherine; Diaz, Rafael; and Shen, Yuzhong, "Development of a Framework to Support Informed Shipbuilding Based on Supply Chain Disruptions" (2022). VMASC Publications. 67.
https://digitalcommons.odu.edu/vmasc_pubs/67
Included in
Operations and Supply Chain Management Commons, OS and Networks Commons, Risk Analysis Commons, Technology and Innovation Commons
Comments
© 2022 The Authors.
This is an open access article under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) License.