Machine learning based photonic dry/curing system ofindustrial coating deposition process’s images for its quality management.

• Elena Torralba-Calleja ^[1] ; Mónica Della Pirriera ^[1] ; Astrid Ribot ^[1] ; Aitor Jara ^[2] ; Antoni Climent ^[2] ; Sergio Martinez-Navas ^[2] ; David Cecilia ^[3] ; Aina Cabrer ^[4] ; Zeynep Beyazkilic ^[4] ; Lorenzo Bautista ^[4]
  1. [1] Photonics & Vision Area, Digital Industry Department, Leitat Technological Center, DFactory Barcelona
  2. [2] Artificial Intelligence Area, Digital Industry Department, Leitat Technological Center, DFactory Barcelona
  3. [3] Advanced Engineering Area, Digital Industry Department, Leitat Technological
  4. [4] Surface Chemistry Area, Applied Chemistry & Materials Department, Leitat Technological Center,

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• Localización: Conectando la academia y la industria: Libro de actas OPTOEL 2023 / coord. por Alejandro Carballar Rincón, María del Rosario Fernández Ruiz, 2024
• Idioma: inglés
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• Resumen

  • This study presents first result of NEW SKIN project about drying and curing photonic system looking for efficient and cost-effective processes to manufacture nano-enabled industrial and consumer products. Here, the design, development and first results about drying process of water-based nanocoating with vision monitoring system by machine learning assessment are reported. The pilot system is composed principally by a spray gun manage by a robotic arm that make the nanocoating, followed by a dedicated IR drying system adjusted to solvent (water in this case) and RBG vision monitoring system. First results indicate a reduction in 48 times in process time duration and a reduction 40 times in energy consumption in comparison with standard RT with air flux drying process.