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AON3D to Offer Sneak Peek of Latest Thermal Optimization Software at RAPID + TCT

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A Montreal-based high-temperature 3D printer manufacturer, AON3D, is preparing to showcase their new thermal optimization software at the RAPID + TCT 2023 event in Chicago.

The software uses machine learning technology to accurately predict heat flow behaviour within objects during printing.

This can help to reduce costs,

improve part reliability and consistency,

optimize performance, and make better technical decisions.

It can also be used throughout all build stages,

including pre-build QA/QC and post-build inspection.

Engineers can use the software to make educated decisions about design and process optimization because it is specifically made to work with Material Extrusion (MEX) technology.

Improved thermal and heat flow simulations

The software can assist in achieving a new level of consistency and part confidence across machines and production runs when used in conjunction with the AON M2+ High-Temperature 3D Printer and Readyprint filaments,

negating the need for time-consuming testing and quality management.

Traditional build preparation software or ‘slicer’ software is limited in simulating thermal and heat flow behaviour.

AON3D’s new tool provides a full visualization of heat flows and temperatures throughout a part,

with fully structured raw data outputted for use in other analytical software,

such as structural FEA or external post-processors.

This makes it easier to assess how process decisions impact specific outcomes, enabling the user to take corrective action before printing or determine inspection requirements after the print.

New software for optimized 3d printing

With spatial resolutions as low as 13 the width of an extruder polymer bead,

new software from AON3D is also said to be incredibly detailed.

This makes it possible to account for intricate part features and regions during the printing process, producing parts that are accurate and robust.

The new software from AON3D is one of many that aims to enhance the 3D printing user experience. Software with machine learning capabilities has also been made available by other businesses, including Hexagon AB and Materialise, to enhance 3D printing.

These technologies enable users to simulate and locate untested materials, analyze and correlate 3D printing layer data, and change build settings

, which affects print job speed and defines component attributes like density and surface quality.

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