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Poreba TCG 160V-18m
Make: poreba
Type: heavy-duty-roll-lath
Model: TCG 160V 18m
Machine number: 1173-29
Centre dista
Make: poreba Type: heavy-duty-roll-lath Model: TCG 160V 18m Machine number: 1173-29 Centre dista...
Harry Vraets Machinery

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2020 Formnext Start-up Challenge winners announced

Posted on 10 Nov 2020 and read 902 times
2020 Formnext Start-up Challenge winners announcedFor the sixth time, the international Formnext Start-up Challenge has recognised young companies from the world of additive manufacturing (AM) for their ‘innovative business ideas and cutting-edge technical developments’.

The five start-ups that managed to win over this year’s jury were: Addiguru (the USA), AM Flow (the Netherlands), Molyworks (the USA), NematX (Switzerland), and TOffeeAM (UK). Molyworks also took home the AM Ventures Impact Award, which was conferred for the first time as part of the Formnext Start-up Challenge.

The winning submissions range from solutions for automated design and post-processing to production monitoring and new synthetic materials. For example, the ‘intelligent software’ TOffee is designed to make the process of implementing new AM designs ‘more potent’, resulting in better-performing components.

With a new high-performance polymer, NematX is hoping to facilitate the production of even more robust components, while Molyworks unveiled a combined mobile unit for melting down scrap metal and turning it into AM-ready powder on site.

Addiguru submitted an easy-to-use real-time monitoring system for additive manufacturing that it says “won’t break the bank” and integrates well into both established and newly developed AM units that work with metal. It involves a camera that connects to an external computer and looks down onto the powder bed from above, automatically recognising the relevant images and sending the photos taken to a self-learning algorithm for analysis. This then detects anomalies and informs the user accordingly.

AM Flow has developed Industry 4.0 technology for the AM sector with the aim of significantly reducing the labor costs involved in post-processing via a solution that covers everything from component recognition, handling, and sorting to packing and transport.

It uses a variety of technologies — including 3-D shape recognition, industrial image processing systems, and AI software — to automate products and processes once 3-D printing has already taken place.