This review draws on a systematic literature review and bibliometric analysis to examine how Digital Twins (DTs), Extended Reality (XR), and Artificial Intelligence (AI) support the reconfiguration of Cyber–Physical Systems (CPSs) in modern manufacturing. The review aims to provide an updated overview of these technologies’ roles in CPS reconfiguration, summarize best practices, and suggest future research directions. In a two-phase process, we first analyzed related work to assess the current state of assisted manufacturing reconfiguration and identify gaps in existing reviews. Based on these insights, an adapted PRISMA methodology was applied to screen 165 articles from the Scopus and Web of Science databases, focusing on those published between 2019 and 2025 addressing DT, XR, and AI integration in Reconfigurable Manufacturing Systems (RMSs). After applying the exclusion criteria, 38 articles were selected for final analysis. The findings highlight the individual and combined impact of DTs, XR, and AI on reconfiguration processes. DTs notably reduce reconfiguration time and improve system availability, AI enhances decision-making, and XR improves human–machine interactions. Despite these advancements, a research gap exists regarding the combined application of these technologies, indicating potential areas for future exploration. The reviewed studies recognized limitations, especially due to diverse study designs and methodologies that may introduce risks of bias, yet the review offers insight into the current DT, XR, and AI landscape in RMS and suggests areas for future research.

Digital Twins (DTs) as a disruptive technology of digital transformation are emerging as a true game changer in several application fields. Through digital representations of physical entities, vertical and horizontal integration can take place. This is the basis for comprehensive interoperability and accessibility between human and machine. This paper elaborates an application scenario bringing together DT in a collaborative environment with manifold devices like computers, tablets, or Extended Reality (XR) devices. Therefore, a DT has been developed which can describe and adapt itself according to the user requirements. This is complemented by a cross-compatible application that visualizes the sensor data in almost real-time and allows the user to interact with or control the DT from any location. In a first proof of concept, a seminar room has been equipped with interior air quality measurement devices which encapsulate several sensors within a 3D printed surrounding. The resulting data was then made available via the corresponding DTs of the measurement devices to the user on a HoloLens 2, Varjo XR-3, computer, or mobile device. The bidirectional flow of data and information between the physical and digital space enables to influence the physical devices through their DTs. The DT, combined with XR, can be used transdisciplinary in teaching or industrial environments.