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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2601.00813 |
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| _version_ | 1866911350837477376 |
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| author | Shao, Longxiang Huesener, Dominik Schluse, Michael Rossmann, Juergen |
| author_facet | Shao, Longxiang Huesener, Dominik Schluse, Michael Rossmann, Juergen |
| contents | The principle of learning from errors is pedagogically powerful but often impractical in industrial settings due to risks to safety and equipment. This paper presents an integrated training approach specifically designed for tufting machine operators. It uses hybrid digital twins, augmented reality (AR), and Petri Net-based modelling to apply the learning from errors principle effectively. Operator actions and errors are simulated via experimentable digital twins (EDTs), and the consequences of errors are visualized in AR, enabling safe, experiential learning. A Petri Net model formally represents the process, including typical faults and recovery paths, and is implemented in VEROSIM using SOML++. This hybrid framework provides a scalable foundation for AR-guided training systems that reduce risk and accelerate skill acquisition. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2601_00813 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Application of the learning from errors principle in tufting machines Shao, Longxiang Huesener, Dominik Schluse, Michael Rossmann, Juergen Systems and Control The principle of learning from errors is pedagogically powerful but often impractical in industrial settings due to risks to safety and equipment. This paper presents an integrated training approach specifically designed for tufting machine operators. It uses hybrid digital twins, augmented reality (AR), and Petri Net-based modelling to apply the learning from errors principle effectively. Operator actions and errors are simulated via experimentable digital twins (EDTs), and the consequences of errors are visualized in AR, enabling safe, experiential learning. A Petri Net model formally represents the process, including typical faults and recovery paths, and is implemented in VEROSIM using SOML++. This hybrid framework provides a scalable foundation for AR-guided training systems that reduce risk and accelerate skill acquisition. |
| title | Application of the learning from errors principle in tufting machines |
| topic | Systems and Control |
| url | https://arxiv.org/abs/2601.00813 |