Materials Processing Institute leads £600K research project to develop AI tool for improving Additive Manufacturing efficiency

January 30, 2024

The Materials Processing Institute is leading a £600,000 research collaboration to develop an AI tool to improve efficiencies within the AM sector (Courtesy The Materials Processing Institute)
The Materials Processing Institute is leading a £600,000 research collaboration to develop an AI tool to improve efficiencies within the AM sector (Courtesy The Materials Processing Institute)

The Materials Processing Institute, headquartered in Middlesbrough, UK, is leading a £600,000 research collaboration project to develop an AI tool capable of improving efficiencies within the Additive Manufacturing sector. Working in partnership with Additive Manufacturing Solutions Ltd, Burscough, UK, and AMFG, headquartered in London and Austin, Texas, USA, SMART-APP is intended to enable cost savings via resource efficiency.

SMART-APP aims to predict the quality change of the powder after each process and propose alternative process parameters on used powder to extend its lifespan with a minimal or an in-specification impact on product quality.

The project is funded by Innovate UK, part of UK Research and Innovation (UKRI), the UK’s innovation agency, which drives productivity and economic growth by supporting businesses to develop and realise the potential of new ideas.

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The research will feature state-of-the-art materials characterisation, and mechanical testing, investigating shelf life and the processability envelope of environmentally affected common stainless steel, titanium and superalloy base feedstock. It will also examine methods of reclaiming the powders and the effect on the final product.

The resulting outputs will be fed into an advanced database linking powder input properties against AM part performance to provide a predictive tool that will be available for industry use.

“SMART-APP is the next logical step to continue the work the Institute has already undertaken in powder characterisation. By developing an artificial intelligence tool that can help AM users create faster and cheaper ways of maximising powder reuse, the AM industry, especially those needing to maximise the operational effectiveness of their machines,” stated Nick Parry, Industrial Digitalisation Group Manager at the Teesside-based Materials Processing Institute. “This predictive tool will develop and enable world class production of AM components, with smart solutions for resource efficiency and providing longer use of materials feedstock and reducing wastage.”

Rob Higham, CEO of Additive Manufacturing Solutions added, “AMS is delighted to have the support of Innovate UK to continue developing our portfolio of world leading powder and AM process optimisation capability. This marks our first step towards a ground-breaking approach for dynamic materials management. The potential of the AM process remains a potential in many people’s eyes. It could be realised with the development of a versatile and smart predictive tool for tracking powder quality after each reuse.”

Alexander Grimmer, Technical Consultant at London-headquartered AMFG, shared, “This initiative aims to transform Additive Manufacturing towards more resource-efficient methods.”

“SMART-APP aims to instil trust in the Additive Manufacturing realm by forecasting powder quality and recommending processes to restore desired powder properties for reuse. AMFG eagerly anticipates contributing to a cutting-edge material management system in this project, poised to deliver substantial environmental and economic benefits to the industry. This endeavour is set to expedite the widespread adoption of Additive Manufacturing,” Grimmer concluded.

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Extensive AM industry news coverage, as well as the following exclusive deep-dive articles:

  • Metal powders in Additive Manufacturing: An exploration of sustainable production, usage and recycling
  • Inside Wayland Additive: How innovation in electron beam PBF is opening new markets for AM
  • An end-to-end production case study: Leveraging data-driven machine learning and autonomous process control in AM
  • Consolidation, competition, and the cost of certification: Insight from New York’s AM Strategies 2024
  • Scandium’s impact on the Additive Manufacturing of aluminium alloys
  • AM for medical implants: An analysis of the impact of powder reuse in Powder Bed Fusion

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