top of page
Image by JJ Ying


Automatic QUality Inspection using deep Learning and Answer set programming


NEED for AI:

The need for AI arises from the current manual process of quality inspection, which is time-consuming and prone to errors. Reducing inspection time and errors leads to cost reduction and higher revenues for manufacturing companies



Using computer vision techniques and AI to automate the compliance assessment of an electronic product. This involves comparing the design of the product in a CAD file with a real artifact, identifying the basic components in the real artifact using a trained neural network for object detection, and then comparing the identified components with the expected components in the CAD file using a logical program. The output is a compliance report that indicates if all the expected basic components in the CAD are present in the real implementation and whether they are in the correct position.



  • AQUILA system will increase digitalisation level of QI processes and reduce QI time by about 60%

  • enhancement of Deep Learning and ASP know-how

  • strengthens relationship with manufacturing players

  • results can be used in workplace security and AQUILA can acquire at least 5 QI and 3 workplace security prospects

Revelis will enhance its quality inspection process for industrial products, particularly electrical panels, by developing an AI-based system called AQUILA. By combining computer vision deep learning techniques with automatic reasoning and Answer Set Programming, the system aims to achieve a 30% increase in defect detection precision, resulting in cost reduction and higher revenues. The project is aligned with the Smart Manufacturing approach and will be implemented and tested within a total of 8 months.

bottom of page