Human-Centered Solutions Based on Automated Visual Inspection System
[EN] Conventional painting inspections in the wind industry rely on human labour to visually inspect the parts, and the mental and physical fatigue of the operator influences the accuracy. The advances introduced on camera sensors, robots, and artificial intelligence algorithms can create a collabor...
| Autores: | , , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2024 |
| País: | España |
| Institución: | Universitat Politècnica de València (UPV) |
| Repositorio: | RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia |
| Idioma: | inglés |
| OAI Identifier: | oai:riunet.upv.es:10251/222473 |
| Acceso en línea: | https://riunet.upv.es/handle/10251/222473 |
| Access Level: | acceso abierto |
| Palabra clave: | Quality inspection Surface defects Non-destructive inspection Human-Robot Collaboration Zero Defect |
| Sumario: | [EN] Conventional painting inspections in the wind industry rely on human labour to visually inspect the parts, and the mental and physical fatigue of the operator influences the accuracy. The advances introduced on camera sensors, robots, and artificial intelligence algorithms can create a collaborative working environment between operators and automated visual inspection system. One of the main challenges for the automatic painting inspection system is the integration with autonomous guided vehicle to perform the inspection routes, and the communication of the data generated during the inspection (defect detection, location, etc.) to the augmented reality platform to send the specific information to the operator to perform the painting repairing operation. Current research aims to define a framework where integrating non-destructive inspection technologies, autonomous guided vehicles, and augmented reality will allow a symbiotic collaboration between humans and robots. The interoperability between these three solutions will increase the Human-Robot Collaboration in a wind tower painting process, improving product quality assurance. |
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