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Mech Solutions Showcases Novel AI Failure Detection Solution at NSERC HI-AM

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Mech Solutions’ research group recently presented their novel solution for AI failure detection in FDM printers at the NSERC HI-AM on June 22nd, hosted in Montreal, QC. NSERC HI-AM, known as Holistic Innovation in Additive Manufacturing, addresses the challenges that prevent the industrial adoption of metal additive manufacturing and helps Canadian businesses adapt for the era of Industry 4.0. The HI-AM is co-hosted by the University of Waterloo and McGill University.

At the conference, Mech Solutions discussed applying the latest computer vision model to analyze images captured in the 3D printing process to detect defects. This AI-powered approach to monitoring the 3D printing process is innovative and game-changing because it is easy to replicate and cost-efficient. We believe this technology can be applied in a few variations and real-world cases, reducing material waste, saving energy and broadening the scope of 3D printing.

The research is lead by Dr. XingChen liu, who is specialized in additive manufacturing and artificial intelligence, working under Dr. Yu Zou’s lab from University of Toronto’s department of Mechancial Engineering. This research is financially subsidized and supported by 3D printing specialists from Mech Solutions.

By sharing experimental results in this conference, Mech solution has been keeping up with creating a revolutionized AI-powered 3D printing project management platform. Connecting and exchanging knowledge with many industry leaders, such as Autodesk, AP&C and Flexcap, maintains Mech Solutions’ innovation and leading position in 3D printing.


Poster 4-14: Development of an In-situ Failure Detection System for Fused Deposition Modelling Process through the Object Detection Model and Nozzle Camera

Xingchen Liu*, Haoliang Zhou**, Sabir Hossain***, Jiachun Wang*, Zhibin Bao***, Yaohui Zou†, Xunchao Zhang†, Heng Xue*, Xianke Lin***, Yu Zou*

  • University of Toronto, Canada; **Mech Solutions Ltd. , Canada; ***Ontario Tech University, Canada; †University of Waterloo, Canada


Conference website:


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