The global landscape for industrial companies is increasingly shaped by new regulations promoting circular economy principles, necessitating the implementation of de-manufacturing processes to recover high-value components from end-of-life products. However, the intrinsic product variety and complexity of such items, coupled with the typically low-volume nature of these operations, render de-manufacturing tasks challenging and often confined to unstructured environments. Given the current limitations of automation in handling such variability, the unparalleled adaptability and flexibility of human operators make manual disassembly the most effective, and frequently the only feasible, approach. This critical reliance on skilled human intervention is exacerbated by a growing shortage of qualified labor. To address this pressing industrial need, and in alignment with Industry 5.0 principles, this research aims to develop an extended reality-driven platform for training operators in manual disassembly. The novelty of this work resides in its innovative application of extended reality technology to enhance human operator capabilities, specifically tailored for the intricate and unstructured demands of de-manufacturing. The efficacy of the proposed solution is demonstrated through a case study involving a kitchen hood for the recuperation of its key components. Practical outcomes include a reduction in operator errors, leading to demonstrable improvement in task completion times. Furthermore, the study confirms a faster and more efficient learning process compared to conventional training methodologies. Collectively, these findings substantiate the potential for extended reality tools to revolutionize training within the engineering industry, broadening their impact beyond repair actions to robust remanufacturing initiatives.
Rizzioli et al. (Thu,) studied this question.
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