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With today‘s trend toward mass customization, fast and efficient reconfiguration of manufacturing systems is essential. New artificial intelligence and robotics developments play a key role in optimizing these processes. AI-driven reconfigurations are becoming increasingly effective because of real-time data from digital twins and intuitive interaction through extended reality. This article presents an approach that integrates digital twins and extended reality in a reconfigurable manufacturing use case, laying the foundation for AI-driven optimization. It highlights potential industrial benefits, such as increased flexibility and reduced downtime, and provides an outlook on future developments.
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Mayer et al. (2025) studied this question.
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