Sustainable electronics: Youbiquo joins the group for a greener future
22 March 2023
QIMAL: a data-driven inspection system for the optimization of the visual inspection process in Metal Additive Manufacturing
24 July 2023
Youbiquo has been selected among the best 30 European startups that applied for the Reach call. Next May, we will participate in a demolition datathon, during which the top 10 startups will be selected.
REACH Incubator
REACH is a European-wide incubator that aims to promote the development of innovative, trustworthy, and secure solutions based on industrial and personal data for data-fueled startups and SMEs. Its main goal is to serve as a catalyst for experiments on secure data value chains across various sectors, with the aim of launching new data-driven products and services to the market. REACH leverages the capacities of the best data-driven DIHs in Europe to achieve this objective. It will support over 100 business ideas from SMEs over its lifetime, selecting 30 promising business cases through three open calls in the next three years and distributing a total amount of €3.5M. Ultimately, REACH seeks to prove that data silos can be overcome by enabling a multi-stakeholder cross-sectoral incubator to promote sustainable data-fueled solutions.
QIMAL
Within the REACH call, we have applied to the “Optimization of visual inspection process” challenge presenting QIMAL: an artificial intelligence platform for defect analysis in additive manufacturing machines.
Talking about Additive Manufacturing, the PROBLEM we have identified is related to the many technical challenges in ensuring repeatable production quality during the production of metal parts using SLM or PBF processes.
To identify defect on the flow, we have developed a SOLUTION based on computer vision algoritms to enable an high recognition rate and a fast detection speed, which can not only meet the forming efficiency, but it can also improve the quality of the formed parts through an effective real-time, closed-loop feedback.
QIMAL combines the analysis of finals product images with 3D CAD design and machine operating parameters to deduct the root causes of defects. This allows to quickly identify error sources and propose targeted solutions, improving product quality, reducing waste and increasing production efficiency.
