Sculpteo utilises artificial intelligence to evaluate metal Additive Manufacturing

March 31, 2017

March 31, 2017

Sculpteo, a digital manufacturing company headquartered in Paris, France, with a facility in San Francisco, USA, has launched its Agile Metal Technology system to analyse and evaluate metal Additive Manufacturing projects. The online agent-based system is aimed at helping designers and manufacturers reduce lead time and project costs.

The company states that its new artificial intelligence is able to check the quality of CAD files, recommend materials and identify project risks. The Agile Metal Technology system is said to find and fix problems, automate complex procedures and find best fit processes and techniques. It can also offer predictions and recommendations on optimising design elements; including lattices, supports and post-processing workflows.

“As the complexity of Additive Manufacturing grows, it is difficult to get the necessary information to make the project go smoothly. Experts and specific software exist, but they are extremely expensive, and add to production time,” stated Clement Moreau, CEO of Sculpteo.

Sculpteo’s Agile Metal Technology is comprised of six modules:

  • Business Case – a self-learning AI that evaluates whether a CAD file is optimised for metal Additive Manufacturing, helps evaluate appropriate materials, and delivers an approach for cost and time budget for metal AM. Business Case is a decision support and planning tool that takes basic input from the user and provides an evaluation of whether AM is an appropriate process for producing the part
  • Design Optimiser – provides a deeper analysis of the design compatibility for metal AM and assesses the best way to handle thermic constraints. The tool detects possible issues, suggests design modifications and evaluates the best printing orientation for the part
  • Lattice Generator – helps meet cost and weight reduction goals by recommending the best structural configuration, while allowing the user the option to choose a preferred lattice cell design
  • Support Optimiser – displays the supports necessary to meet the requirement of the part (tolerance, yield assessment). Expert users will be able to add inputs and restrictions based on the support generated by the Agile Metal Technology platform
  • Post-Processor – analyses post-processing features and required metrology to meet the project requirements, and evaluate how timeline and budget can be met
  • Batch Controller – a replica of the Sculpteo batch control tool for metal AM technologies

March 31, 2017

In the latest issue of Metal AM magazine

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

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  • 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
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  • 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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