Monitoring solutions to optimise the process in furniture manufacturing
For the woodworking processes, the MULTIPLE project aims to implement the technologies to measure parameters such as humidity, density and the elasticity of the raw input material both before and during the processes as well as defect detection and colour inspection of the finished product.
MULTIPLE will implement its photonic-based process monitoring technologies in a woodworking process to manufacture furniture and to enable an early reaction to problems in specific parts, detecting defects as they appear and taking corrective measures (e.g. reworking, reclassification), before the component undergoes further processing. Parameters that will be monitored include humidity, density and the elasticity of the raw input material both before and during the processes as well as defect detection and colour inspection of the finished product. The system will collect data from different furniture components to build a reference bank using the Data Warehouse. An adaptive close-loop control will be implemented for adjusting the operation using the HSI vision system and estimated parameters (i.e. uniform glue distribution, localised defects, and wrong border colour) to automatically adjust the machine. The edge device will be integrated with PLC of the machine. As a result, the main optimisation goals in this wood working use case will be enabling one-size batch with zero defect, maximising the reuse of residue, and minimum delivering times, in order to minimise cost and meet the main trends of the market, driven by online retail channels and online exposure.
July 2020 – First trials with ROYO’s wooden boards samples
AIMEN has been performing the first tests using IMEC’s hyperspectral camera (Snapscan VNIR) with ROYO’s wooden boards samples to check if defects can be detected using this type of camera. Different set-ups were tested playing with camera position and lighting, and images for all the defects were taken evaluating afterwards, if it is easy, doubtful or improbable to detect these defects in an automated way.