DfAM

The acronym DfAM – Design for Additive Manufacturing – has emerged in recent months to define all those practices and skills that enable a designer or an engineer to create objects which optimally leverage the geometric potential of additive manufacturing technologies.



These skills and practices include many software tools – often included in CAE (Computer Aided Engineering) programs as well as capabilities that are derived from personal experience. Next generation CAD and CAE software may provide support through a wide range of approaches. These include processes such as topology optimization – that is the ability to add material where it is needed and remove it where it is unnecessary – or the parametric generation of lattice and trabecular structures. There are highly intricate networks of structures that can confer a specific component the same or better mechanical properties than solid parts, using less material and thus reducing manufacturing costs. Furthermore, these types of structures can be produced only through layered additive manufacturing processes.


While these approaches are becoming adopted in advanced engineering, there were still largely unknown until just a few years ago, when only a handful of forward-looking creatives, artists and product designers began to experiment with them in combination with AM technologies. Today DfAM has grown to encompass concepts such as mass customization – the ability to serially manufacture custom products – as well as wearable technology and even personalized food manufacturing. These designers continue to show us the way products will be digitally and additively made in the future. Check out 3dpbm’s exclusive celebrity survey with some of the world’s greatest DfAM designers.

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  • Kennesaw State University researchers increase part strength by nearly three times with advanced simulations.

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  • MIT researchers improve reliability of complex 3D printed parts - enabling digital designs to incorporate the limitations of 3D printers.

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  • nTop acquires cloudfluid to advance computational design offering - expanding applications in aerospace, defense, and turbomachinery.

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  • Self-improving AI increases 3D printing efficiency. The Washington State University study could enable more complex and intricate designs.

    Self-improving AI increases 3D printing efficiency

    According to Washington State University, an artificial intelligence algorithm (AI) can allow researchers to more efficiently use 3D print intricate structures. The study, published in the journal Advanced Materials Technologies, could…

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