The main objective of this project is the research, development and implementation of an innovative system for quality control in the furniture industry. Through the use of advanced computer vision, artificial intelligence (AI) and data management technologies, the system will be able to identify and classify with high accuracy the defects that can be found on the surface of boards in their raw state at laboratory scale. The integration of these technologies will facilitate a significant improvement in production processes, contributing to quality optimisation and reducing times.
Key Technologies:
Machine Vision : Use of cameras and sensors to capture high-resolution images of board surfaces, which will be processed by machine vision algorithms.
Deep Learning: AI models capable of identifying complex patterns in the images, allowing accurate classification of defects in real time.
Data Management: System to store, process and analyse large volumes of data generated during the inspection process, optimising decision making and enabling full product traceability.
Total Project Budget:
479.905€.
Grant awarded:
287.343€.
Project Partners:
NUTAI, Omnielectric, and Andreu Tops
This program is supported by the Valencian Institute of Competitiveness and Innovation (IVACE+i Innovation), with funding from European funds, under file number INNCAD-2024-112.
