Authors : Arnab Sen

Volume/Issue : Volume 10 - 2025, Issue 11 - November

Google Scholar : https://tinyurl.com/pzty7p3r

Scribd : https://tinyurl.com/2pzr7ha3

DOI : https://doi.org/10.38124/ijisrt/25nov1522

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Abstract : Introduction The contemporary aerospace and defense sector operates within a paradox of hyper-efficiency and systemic fragility, where tightly coupled global supply chains (G-SCMs) are increasingly vulnerable to high-velocity disruptions. Traditional procedural risk management models (SCRM-P) have proven insufficient for mitigating "fat-tailed" geopolitical and regulatory risks.  Methods This study operationalizes an Integrated Resilience-Agility Framework (IRAF) utilizing a mixed-methods approach. It combines a theoretical critique of catastrophe economics with a quantitative Monte Carlo simulation (N=10,000 iterations) modeling a disruption in a Tier-2 supplier for a US-India defense Joint Venture (JD-P).  Results The simulation results demonstrate that the IRAF, by leveraging predictive AI and blockchain-based verified agility, reduces the Mean Time to Recovery (TTR) by 42% and decreases the Value-at-Risk (VaR) by approximately 58% compared to traditional procedural models.  Conclusion The study empirically validates that shifting from a cost-minimization to a capability-based resilience model is not merely an operational enhancement but a fiduciary necessity for preserving firm value in highly regulated environments.

Keywords : Supply Chain Risk Management (SCRM); Resilience; Agility; Aerospace Defense; Monte Carlo Simulation; Enterprise Risk Management (ERM).

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