Abstract
With the advent of Industry 4.0, the creation of high-fidelity digital representations of physical assets have become central to modern manufacturing. Among the enabling technologies, the concept of the Digital Twin (DT) has emerged as a key paradigm, allowing continuous synchronization between physical and virtual entities through real time data exchange. The development of DTs, however, presents several challenges, for instance regarding the trade-off between model fidelity and computational feasibility, as well as communication and synchronization issues for real-time integration, aspects particularly critical for Cyber-Physical Systems (CPSs). Moreover, integrating energy consumption modeling into DT workflows is increasingly relevant in the context of green digitalization but remains a largely unexplored area in both academia and industry. This Ph.D. research addresses these challenges by proposing a structured framework to guide the evolution of Digital Models (DMs) into fully integrated DTs of mechatronic systems, with a particular focus on embedding energy modeling into the earliest stages of DT development. The framework is developed based on a systematic review of state-of-the-art tools, simulation environments, and synchronization practices, identifying gaps in current methodologies and highlighting open research questions. Based on these findings, the methodological developments are carried out within the industrial Physics (iPhysics) simulation environment. The choice of this platform is motivated by its technical suitability as well as its industrial relevance, being also adopted by the company Progress Group as industrial co-partner of this PhD research. The proposed framework, along with a set of enhanced modeling and simulation capabilities developed in iPhysics, is validated through a set of case studies in both laboratory and industrial contexts. Experimental tests are carried out to compare simulated and real data for kinematics, dynamics, and energy consumption, demonstrating the feasibility, repeatability, and scalability of the proposed methodology. By integrating energy-oriented modeling into DT workflows and validating the approach through relevant scenarios, this research aims at contributing to bridging the gap between academic advancements and industrial needs, paving the way for systematic research about the integration of kinematic, dynamic, and energy modeling into DT workflows of mechatronic systems.