Automated Defect Detecion in Automotive Paint
In automotive industry, appearance is a predominant choice criterion, with paint quality being an essential element of a vehicle’s overall appearance. This is truly obvious for broad consumer goods, where visual appearance is a major differentiation and selling point among competitors. In vehicle production, painted bodies are inspected by operators relying on reflected light patterns, to visually identify defects that will be corrected in a later production step. The aim of this project is to introduce the process to industry 4.0 standards, through the combination of 3 innovative key-technology developments: 1) A new generation modular light inspection tunnel able to provide continuous & dynamic light patterns for optimal defect detection. 2) Deflectrometry-based defect detection, enabling computer-aided measurements. 3) Mixed-reality headset for defect visualization and detection. The aim is to improve detection precision and efficiency, thus reduce lead times and costs, while also improving operators' overall welfare in their task. The aim of project is to setup a part-scale R&D equipment, to create a proof-of-concept able to generate commercial interest among potential OEM's.