Digital Twin technologies for process mechanical systems: Physics-based integration, degradation modeling, and lifecycle-oriented research framework

While Digital Twin (DT) technology has proliferated in industries and Cyber-Physical Systems (CPS), the application of DT technology to process mechanical systems remains fragmented. Existing reviews have primarily concentrated on discrete manufacturing, machining, or general Industry 4.0 concepts, with little emphasis on the multiphysics, degradation, and integrity needs of pumps, compressors, turbines, heat exchangers, or pressure vessels. This review collates recent advancements in physics-based, hybrid physics-AI, and data-centric DT techs, particularly for process mechanical systems. New contributions of the paper include: a unified treatment of thermo-mechanical, fluid-structure interaction (FSI), rotor system, and physics-of-failure aspects within DTs; comparison with existing manufacturing-centric DTs; and the explicit connection of degradation-aware prognostics to asset integrity and maintenance optimization. By identifying the outstanding issues in realizing real-time multiphysics coupling, uncertainty quantification, validation, and scalability, the paper outlines a domain-specific research roadmap that will enable the transition of DTs from descriptive models to decision support tools that can be trusted for process industries.