Leveraging Digital Twins for Root Cause Analysis in Complex Medical Device Manufacturing

Abstract

Medical device manufacturing is a highly complex and regulated industry where product failures can directly impact patient safety and public health. Ensuring reliability requires effective quality management strategies, with root cause analysis (RCA) serving as a critical tool for identifying and eliminating sources of defects. However, conventional RCA approaches often depend on retrospective data reviews, manual inspections, and expert judgment, which can be slow, reactive, and prone to subjectivity. As medical devices grow more advanced and interconnected, these traditional methods are no longer sufficient to meet the increasing demands for efficiency, accuracy, and compliance.

Digital Twin (DT) technology has emerged as a promising solution by creating real-time virtual representations of physical devices, systems, and processes. By integrating IoT-enabled data streams, predictive simulations, and advanced analytics, DTs allow continuous monitoring, rapid anomaly detection, and predictive fault modeling. Unlike static approaches, digital twins support proactive RCA by simulating potential failure scenarios and enabling manufacturers to test corrective measures before implementation. This not only improves the speed and precision of problem-solving but also ensures alignment with stringent regulatory frameworks such as ISO 13485 and EN 62304.

This paper investigates how digital twins can be leveraged for RCA in complex medical device manufacturing. It compares traditional RCA methods with DT-driven approaches, highlights their impact on compliance and safety, and demonstrates how DT adoption reduces risks, improves traceability, and enhances operational resilience. The findings suggest that integrating DTs into RCA processes will transform quality management practices, providing a foundation for future AI-augmented models that advance predictive and prescriptive fault analysis. Ultimately, DT-enabled RCA has the potential to redefine reliability and patient safety in the medical device sector.