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The Development, Implementation, and Application of a Probabilistic Risk Assessment Framework to Evaluate Supply Chain Shortages

Author

Listed:
  • Priyanka Pandit

    (Department of Nuclear Engineering, North Carolina State University, Raleigh, NC 27695, USA)

  • Arjun Earthperson

    (Department of Nuclear Engineering, North Carolina State University, Raleigh, NC 27695, USA)

  • Mihai A. Diaconeasa

    (Department of Nuclear Engineering, North Carolina State University, Raleigh, NC 27695, USA)

Abstract

Background : Supply chain disruptions from natural hazards, geopolitical tensions, or global events, such as the COVID-19 pandemic, can trigger widespread shortages, with particularly severe consequences in healthcare through drug supply interruptions. Existing methods to assess shortage risks include scoring, simulation, and machine learning, but these approaches face limitations in interpretability, scalability, or computational cost. This study explores the application of probabilistic risk assessment (PRA), a method widely used in high-reliability industries, to evaluate pharmaceutical supply chain risks. Methods : We developed the supply chain probabilistic risk assessment framework and tool, which integrates facility-level failure probabilities and flow data to construct and quantify fault trees and network graphs. Using FDA inspection data from drug manufacturing facilities, the framework generates shortage risk profiles, performs uncertainty analysis, and computes importance measures to rank facilities by risk significance. Results : SUPRA quantified 7567 supply chain models in under eight seconds, producing facility-level importance measures and shortage risk profiles that highlight critical vulnerabilities. The tool demonstrated scalability, interpretability, and efficiency compared with traditional simulation-based methods. Conclusions : PRA offers a systematic, data-driven approach for shortage risk assessment in supply chains. SUPRA enables decision-makers to anticipate vulnerabilities, prioritize mitigation strategies, and strengthen resilience in critical sectors such as healthcare.

Suggested Citation

  • Priyanka Pandit & Arjun Earthperson & Mihai A. Diaconeasa, 2025. "The Development, Implementation, and Application of a Probabilistic Risk Assessment Framework to Evaluate Supply Chain Shortages," Logistics, MDPI, vol. 9(4), pages 1-20, October.
    • Handle: RePEc:gam:jlogis:v:9:y:2025:i:4:p:141-:d:1765643
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    References listed on IDEAS

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    1. Klibi, Walid & Martel, Alain, 2012. "Scenario-based Supply Chain Network risk modeling," European Journal of Operational Research, Elsevier, vol. 223(3), pages 644-658.
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