Digital Twins, Extended Reality, and Artificial Intelligence in Manufacturing Reconfiguration: A Systematic Literature Review

Anjela Mayer (), Lucas Greif, Tim Markus Häußermann, Simon Otto, Kevin Kastner, Sleiman El Bobbou, Jean-Rémy Chardonnet, Julian Reichwald, Jürgen Fleischer and Jivka Ovtcharova
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Anjela Mayer: Institute for Information Management in Engineering, Karlsruhe Institute of Technology, 76133 Karlsruhe, Germany
Lucas Greif: Institute for Information Management in Engineering, Karlsruhe Institute of Technology, 76133 Karlsruhe, Germany
Tim Markus Häußermann: Virtual Engineering Competence Center, Mannheim University of Applied Sciences, 68163 Mannheim, Germany
Simon Otto: Wbk Institute of Production Science, Karlsruhe Institute of Technology, 76131 Karlsruhe, Germany
Kevin Kastner: Virtual Engineering Competence Center, Mannheim University of Applied Sciences, 68163 Mannheim, Germany
Sleiman El Bobbou: Institute for Information Management in Engineering, Karlsruhe Institute of Technology, 76133 Karlsruhe, Germany
Jean-Rémy Chardonnet: Arts et Metiers Institute of Technology, LISPEN, 71100 Chalon-sur-Saône, France
Julian Reichwald: Virtual Engineering Competence Center, Mannheim University of Applied Sciences, 68163 Mannheim, Germany
Jürgen Fleischer: Wbk Institute of Production Science, Karlsruhe Institute of Technology, 76131 Karlsruhe, Germany
Jivka Ovtcharova: Institute for Information Management in Engineering, Karlsruhe Institute of Technology, 76133 Karlsruhe, Germany

Sustainability, 2025, vol. 17, issue 5, 1-39

Abstract: 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.

Keywords: reconfigurable manufacturing systems; digital twins; extended reality; artificial intelligence; human–machine interaction; cyber–physical systems (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
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