Link3D
Link3D Figure 1 AMRS
Link3D Material Recommendation System includes a database of +1000 materials across +500 3D Printers.
Link3D has announced the launch of its Additive Material Recommendation System (AMRS), which uses qualitative and quantitative production specification to suggest appropriate materials.
The AMRS, which is integrated into the existing Link3D Additive Manufacturing Execution System (AMES) software platform, has been developed to help users of the software better understand material performance, relative to their own properties and the printers they are to be processed on. By introducing intuitive material recommendation features, Link3D is aiming to combat the lack of design knowledge, that has been reported as one of the major technological limitations organisations face.
Engineers can narrow down material selections by key filtering qualitative characteristics and technical material property ranges. Qualitative characteristics include properties like rigidity, strength, durability, and rubber-like specifications for polymer materials; corrosion resistance, electrical conductivity, ductility, and thermal conductivity for metals; and biocompatibility and high-temperature resistance for both. Technical properties refer to tensile strength, elongation at break, density and hardness, while the AMRS also takes into account the material manufacturer, whether it’s EOS or HP, Concept Laser or Renishaw, and so on.
Link3D
Link 3D Figure 2 AMRS
Material Recommendation System for Polymer Materials.
Link3D’s motive for introducing the AMRS tool is to simplify additive manufacturing and help it on its way to becoming a volume production technology and ensure it is continued to be adopted in key industries.
“One of the major recurrent hurdles we’re hearing from our customers is how to accelerate the adoption of additive manufacturing within their own organisation,” commented Renaud Vasseur, VP of Business Development & Sales at Link3D. “We are thrilled that Link3D is introducing an additive manufacturing recommendation system that will not only help engineers achieve their design goals, but also increase overall understanding of the additive manufacturing capabilities and workflows.”
