iDIGIT4L. Nuevos ecosistemas de digitalización y aprendizaje hombre-máquina para sistemas de fabricación industrial heredados
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arXiv
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| Autori principali: | , |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| _version_ | 1866914812983771136 |
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| author | García, Alvaro Cañibano, Esteban |
| author_facet | García, Alvaro Cañibano, Esteban |
| contents | The digitization of the productive ecosystem related to human-machine interaction has become a priority for small and medium-sized enterprises. Particularly to face the challenges of Industry 4.0 and advanced digital skills in the workplace. From the research point of view, digitization opens a global scenario for the generation of opportunities for learning in existing manufacturing systems. Mainly, traditional environments must deal with competitive pressures to incorporate new technologies and adapt the skills of workers. In this paper is presented the iDIGIT4L project, which was envisaged to research and develop a digitization ecosystem where people and systems interact in order to transform industrial processes in an intelligent and predictive way. The project contributes with a three-tier human-machine learning methodology that provides augmented and bi-directional interaction in a traditional manufacturing scenario. It is based on the implementation of a non-intrusively integrated digital twin, characterizing an old industrial milling machine for learning through knowledge models supported by the experience of skilled workers. As a result, it has been possible to simultaneously update the functionalities of the industrial system and the digital skills of the workers, becoming an integral part of the digital twin. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2405_16676 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | iDIGIT4L. Nuevos ecosistemas de digitalización y aprendizaje hombre-máquina para sistemas de fabricación industrial heredados García, Alvaro Cañibano, Esteban Human-Computer Interaction The digitization of the productive ecosystem related to human-machine interaction has become a priority for small and medium-sized enterprises. Particularly to face the challenges of Industry 4.0 and advanced digital skills in the workplace. From the research point of view, digitization opens a global scenario for the generation of opportunities for learning in existing manufacturing systems. Mainly, traditional environments must deal with competitive pressures to incorporate new technologies and adapt the skills of workers. In this paper is presented the iDIGIT4L project, which was envisaged to research and develop a digitization ecosystem where people and systems interact in order to transform industrial processes in an intelligent and predictive way. The project contributes with a three-tier human-machine learning methodology that provides augmented and bi-directional interaction in a traditional manufacturing scenario. It is based on the implementation of a non-intrusively integrated digital twin, characterizing an old industrial milling machine for learning through knowledge models supported by the experience of skilled workers. As a result, it has been possible to simultaneously update the functionalities of the industrial system and the digital skills of the workers, becoming an integral part of the digital twin. |
| title | iDIGIT4L. Nuevos ecosistemas de digitalización y aprendizaje hombre-máquina para sistemas de fabricación industrial heredados |
| topic | Human-Computer Interaction |
| url | https://arxiv.org/abs/2405.16676 |