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Topology-Aware Adaptive Inspection for Fraud in I4.0 Supply Chains

Welsh, T., Alrimawi, F., Farahani, A. , Hassett, D., Zisman, A. & Nuseibeh, B. ORCID: 0000-0002-3476-053X (2023). Topology-Aware Adaptive Inspection for Fraud in I4.0 Supply Chains. IEEE Transactions on Industrial Informatics, 19(4), pp. 5656-5666. doi: 10.1109/tii.2022.3205369

Abstract

Supply chain fraud involving counterfeit or adulterated products presents threats to human health and safety. Quality inspection is a key fraud mitigation tool where inspection planning involves allocating inspection resources across geographically dispersed assets considering both the cost and value of the inspection. I4.0 environments pose further challenges as their heterogeneous and dynamic cyber-physical environment creates a large inspection resource allocation solution space, causing the corresponding analysis to be computationally complex. In this article, we contribute to supporting optimal inspection decisions of dynamic cyber-physical supply chains through the use of structural representations - topologies of the supply chain, physical premises, and their production context. We present an approach for topology modeling of supply chains and illustrate its use within an adaptive inspection approach, showing that structural information can reduce malicious process discovery times by up to 90%.

Publication Type: Article
Additional Information: This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see http://creativecommons.org/licenses/by/4.0.
Publisher Keywords: Supply chains, Inspection, Fraud, Topology, Adaptation models, Costs, Manufacturing
Subjects: H Social Sciences > HD Industries. Land use. Labor
Departments: School of Science & Technology
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