State-of-the-Art on Digital Twin Technologies for Industrial Applications and the Federated Digital Twin Lifecycle Model (F-DTLM)

Digital Twins (DTs) have emerged as a key technology for sensor-driven cyber–physical systems, enabling such features as real-time monitoring, predictive maintenance, and operational optimization. Despite rapid progress, existing research in the area remains fragmented, mostly addressing only singular aspects, such as data acquisition, modeling, or control, lacking a unified lifecycle-oriented methodology capable of integrating heterogeneous sensor infrastructures, hybrid analytical models, and continuous feedback mechanisms. This paper presents a comprehensive state-of-the-art review of Digital Twin technologies, focusing on sensor-centric architectures, data integration strategies, and hybrid modeling approaches. Based on the identified limitations, a novel Federated Digital Twin Lifecycle Model (F-DTLM) is proposed as a unifying framework for industrial applications. The model structures the DT lifecycle into four iterative phases—Definition and Scoping; Sensor Data and Infrastructure Federation; Hybrid Modeling and State Synchronization; and Operational Optimization and Closed-Loop Control, supported by cross-cutting layers addressing interoperability and governance. The integration of federated sensing infrastructures with hybrid physics-informed and data-driven models enables scalable synchronization between physical and digital systems. A comparative analysis and an illustrative predictive maintenance scenario illustrate the potential applicability of the proposed approach.