4.5 Article

Assessing cyber resilience of additive manufacturing supply chain leveraging data fusion technique: A model to generate cyber resilience index of a supply chain

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DOI: 10.1016/j.cirpj.2021.09.008

Keywords

Cyber resilience assessment; Cybersecurity; Additive manufacturing; Resilience index; Uncertainty; Dempster-Shafer theory; Yager's rule

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The increasing use of technology in manufacturing and supply chain sectors has made them more vulnerable to cyber threats. An assessment of cyber resilience in additive manufacturing (AM) supply chain is crucial, and a methodology based on hierarchical evidential reasoning and D-S theory has been proposed in this study for evaluation. A case study was conducted to validate the framework, showing reasonable results in assessing the cyber resilience state of an additive manufacturing organization.
The ever-increasing use of technology in manufacturing and other sections of a supply chain make it more susceptible to cyber threats. Perhaps additive manufacturing (AM) supply chains possess higher degrees of threats than other supply chains due to their heavy dependence on technology and information sharing. Therefore, an assessment of the cyber resilience of an additive manufacturing (AM) supply chain is a crucial task to make the AM supply chain safe from the cyber intrusion and to secure competitive business advantages. Consequently, it is essential to develop a strategic decision-making framework to address the vulnerabilities associated with the AM supply chain. The assessment process involves various information sources that are incomplete, subjective, and also uncertain in type. Therefore, to handle the incomplete, uncertain, and subjective nature of the data, in this study, a data fusion technique named hierarchical evidential reasoning-based approach has been adopted. This study proposes an integrated and comprehensive approach based on Dempster-Shafer (D-S) theory as a methodology of developing a framework for assessing the cyber resilience of an additive manufacturing supply chain. A case study involving an additive manufacturing organization was selected to test the proposed methodology. The output of the proposed framework shows reasonable results as an index of cyber resilience of additive manufacturing supply chain considering the amount of uncertainty or unassigned data associated with the measure of belief. Later, Yager's recursive rule of combination is applied to validate the output of the D-S theory. An index value was generated regarding the organization's cyber resilience state; it depicts a numerical measure of how resilient the organization is. The proposed methodology also can be adopted and materialized by the practitioners to assess the condition state of cyber resilience of the additive manufacturing supply chain. In addition, the proposed model can be extended to compare multiple organizations in terms of their condition state of cyber resilience through a unified model. (C) 2021 CIRP.

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