Cognitive Supplier Risk Management Systems for Medical Device: AI Framework for Predictive Quality, Compliance, and Supply Chain Resilience

Abstract

Medical device manufacturers depend on complex supplier networks for critical components, materials, software, and production services. Failures within these networks can create serious quality defects, regulatory non-compliance, supply interruptions, delayed product availability, and potential risks to patient safety. Traditional supplier risk management approaches are often retrospective, fragmented across quality and procurement systems, and insufficiently responsive to emerging disruptions. This study develops a cognitive supplier risk management framework that applies artificial intelligence to integrate predictive quality monitoring, compliance intelligence, and supply chain resilience planning. The proposed framework combines supplier audit findings, non-conformance records, corrective and preventive action data, delivery performance, regulatory indicators, logistics signals, and external disruption data to generate dynamic supplier risk scores. It uses predictive analytics, anomaly detection, natural language processing, and decision-support dashboards to identify early warning signs of supplier instability and recommend targeted mitigation actions. The framework also incorporates digital supply chain twin capabilities to support scenario analysis, supplier substitution planning, and recovery decision-making during disruptions. The study contributes a structured model for linking AI-enabled supplier intelligence with medical device quality management and regulatory governance. It emphasizes that human oversight, data quality, explainability, validation, and accountability remain essential for responsible implementation. The framework offers practical value for procurement, quality assurance, regulatory affairs, and supply chain leadership seeking to improve supplier visibility, compliance readiness, and operational resilience.

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Cite this publication

Binitkumar M Vaghani (2026). Cognitive Supplier Risk Management Systems for Medical Device: AI Framework for Predictive Quality, Compliance, and Supply Chain Resilience. International Journal of Engineering and Computer Science, 15(07), 28678-28688. https://doi.org/10.18535/ijecs.v15i07.5585

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