Rapid-Response AI/ML Software Platform for DoD-Compliant Electronics during the COVID-19 National Emergency: Minimizing Human Intervention, Maximizing Quality

Chode, Balaji (2025) Rapid-Response AI/ML Software Platform for DoD-Compliant Electronics during the COVID-19 National Emergency: Minimizing Human Intervention, Maximizing Quality. International Journal of Science and Research Archive, 15 (3). pp. 608-617. ISSN 2582-8185

During the COVID-19 national emergency, defense electronics manufacturers faced critical supply-chain disruptions and surging demand for DoD-compliant systems ranging from UV sterilizers to electric vehicle chargers under tight timelines and stringent quality require- ments. We present a Rapid-Response AI/ML Software Platform that automates end-to-end manufacturing operations—from lead capture and bill-of-materials proposal generation through reinforcement-learning-based production scheduling and three-dimensional PCB design automation, to AI-powered procurement, closed-loop quality assurance, and real- time billing. Deployed in a cloud-native microservices architecture with integrated De- vSecOps pipelines, the platform enforces DoD MIL-STD and DFARS compliance checks, achieves at least 99.9 percent uptime, and maintains 95th-percentile service latencies below 150 milliseconds. In production, it reduced time-to-first-unit by eighty-four percent, halved labor and rework costs, and kept defect rates under 0.3 percent, delivering more than four million dollars in cost savings during the peak COVID surge. By integrating tightly with ERP, PLM, and financial systems—and leveraging computer vision, reinforcement learn- ing, and predictive analytics—our solution provides a fully traceable, auditable, and cost- efficient manufacturing backbone. We supply architecture blueprints, model notebooks, and infrastructure-as-code templates to enable defense contractors and critical-infrastructure producers to replicate rapid-response, high-quality production under emergency conditions.