In Industry 4.0 and 5.0 eras, Reconfigurable Manufacturing Systems (RMSs) rose as effective solution to meet the highly dynamic customers’ needs. RMSs deal with intelligent machines able to perform a large variety of tasks, by ‘reshaping’ themselves thanks to auxiliary modules which can be assembled and disassembled to/from their base structures. However, despite auxiliary modules increase reconfigurability level of these systems, their frequent assembly/disassembly and the highly different working parameters and conditions subject them to greater wear and tear risks. Hence, an appropriate maintenance policy must be planned to maximise the modules’ lifespan, reducing downtimes and costs. In this context, embracing the progress of digital technologies, Digital Twins (DTs) are becoming a widespread tool in smart manufacturing for performance analysis, process simulation and the development of what-if DfX analysis. This paper presents a dynamic DT modelling environment, based on a commercial 3D scale simulation platform, to integrate maintenance policy in RMS operations’ management. By focusing on the most relevant challenges posed by RMSs, the model allows simulating the impact of responsive and flexible maintenance alternatives, tracking their impact on the system uptime and productivity. The proposed DT modelling environment is preliminary tested through a simplified industrial case study inspired from the metalwork mechanical sector, showcasing its effectiveness in supporting operations’ activity planning and management within complex and adaptable production environments.