Sustainable Maintenance 4.0 Enhanced by Digital Twins: A Systematic Literature Review and Conceptual Model Proposal

Industrial maintenance has increasingly evolved into a strategic function for improving asset reliability, extending asset lifecycle, and supporting sustainability objectives. However, the literature remains fragmented, with limited integration between digital twins, maintenance practices, and sustainability-oriented decision-making. To address this gap, the study performs a systematic review of 49 publications indexed in Scopus and Web of Science and introduces an integrative conceptual framework for Sustainable Maintenance 4.0. The analysis explores the role of digital twins, as a key enabling technology within the Industry 4.0 landscape, in supporting the shift from reactive and schedule-based maintenance toward predictive and prescriptive strategies. The findings suggest that digital twins can enhance maintenance decision-making, improve asset reliability, and contribute to lifecycle optimization. The reviewed studies also report improvements in operational and energy performance, although these effects vary according to digital maturity, system configuration, and implementation scope. In addition, digital twins may support safer operations and workforce development through data-driven and immersive environments. Despite these benefits, challenges remain, including high investment requirements, interoperability limitations, cybersecurity risks, and the need for interdisciplinary skills. The proposed framework positions digital twins as a mediating element between physical assets, data acquisition, advanced analytics, maintenance services, and sustainability outcomes.