AU Class
AU Class
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Linking DFAM, Design Optimization, and Generative Design

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    In this session, we’ll discuss how design for additive manufacture (DFAM) can influence the performance of additively manufactured parts. This session will focus primarily on laser powder-bed fusion, but concepts can be transferable to other additive techniques. We’ll explore lattices, hollow geometries, and thin walls as common features in lightweight designs, including the challenges that these can pose in design, post processing, and actual performance. Autodesk Research is currently undertaking research to characterize how as-built features perform (mechanically) compared to idealized conditions—generic bulk-material values found in literature. This will enable better representation of these features at the design stage to facilitate more accurate simulation and optimization. Attendees will leave more familiar with DFAM, considerations during the design process, and the impacts these have on overall part performance.

    Key Learnings

    • Learn about DFAM freedoms and constraints
    • Learn about material property variation within the meso scale
    • Learn about design impacts on material properties
    • Learn about mechanical fatigue as a design parameter