Digital twins in quality systems: Predictive models for deviation and CAPA Management

The fast digitization of the manufacturing and life sciences sectors has introduced technologies bridging the realms of the physical and virtual worlds. Digital Twin technology is one of these innovations that has emerged as a revolution in Quality Management Systems (QMS), especially to deal with deviations and Corrective and Preventive Actions (CAPA). The article will discuss the application of digital twins in QMS platforms in terms of how predictive modeling, AI, and real-time data synchronization can be used to enhance root cause analysis, risk mitigation, and compliance efficiency. The argument on conceptual underpinnings, architecture, applications, and regulatory considerations covers a discussion and bases its arguments using verified research findings and industrial case studies. The paper ends by providing future trends of intelligent QMS driven by digital twins and advanced analytics.