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

Sazid Rahman, Niamat Ullah Ibne Hossain, Kannan Govindan*, Farjana Nur, Mahathir Bappy

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review

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Abstract

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.

Original languageEnglish
JournalCIRP Journal of Manufacturing Science and Technology
Volume35
Pages (from-to)911-928
ISSN1755-5817
DOIs
Publication statusPublished - Nov 2021

Keywords

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

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