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ETH Zurich demonstrates automated DfAM framework with custom nozzles

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There is no question about additive manufacturing’s ability to produce complex, highly integrated geometries: in fact, this capability is one of the technology’s main advantages. Despite this, one of the hurdles to the broad implementation of AM has been actually creating these complex designs in the first place. That is, many parts with complex 3D printed structures are realized thanks to the deep application-specific knowledge of engineers and entail a fairly time-consuming modeling process. In recent years, we’ve seen the emergence of topology optimization software, which generates structures based on the requirements input by the user. However, even this approach often requires some degree of manual interpretation.

Recently, a team of researchers from ETH Zurich set out to address this challenge with the goal of creating an automated design approach that could enable the rapid generation of design concepts as well as iteration changes and customization with minimal effort. In a new study published in the journal Additive Manufacturing, the team presents a “computational design synthesis framework to automate the design of complex-shaped multi-flow nozzles.”

ETH Zurich automated design
(Image: ETH Zürich)

The innovative framework devised by the researchers provides AM users with an array of design tools, which are used as building blocks to generate finished structures for 3D printed parts. Each design element is organized within a hierarchical architecture and is implemented using object-oriented programming—all presented within a visual interface that is accessible to non-expert users.

In a proof of concept, the ETH Zurich team successfully generated designs for a range of customized AM nozzles used for clay extrusion using the framework. It writes: “Given the concept of a nozzle including inlets and outlets, a user specifies the layout design of a part meaning the arrangement of design elements. The layout serves as an input for the toolbox that automatically translates it into the corresponding 3D nozzle geometry. To analyze manufacturing restrictions of AM, the toolbox provides functions to check wall thickness values and critical overhang angles. These allow detecting and excluding non-manufacturable AM designs. Furthermore, a nozzle can be evaluated for its performance using computational fluid dynamics (CFD) analysis.”

Ultimately, the case study demonstrates the viability of the group’s high-level, object-oriented building block framework, which enables AM users to efficiently translate a layout design into a 3D geometry—in this case, for a series of custom co-extrusion nozzles. Going forward, the Zurich-based team will integrate design elements that “dynamically adapt themselves for AM restrictions instead of being excluded during a parametric optimization” and seek to adapt the design framework to other AM application areas. The full study can be found here.

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Tess Boissonneault

Tess Boissonneault is a Montreal-based content writer and editor with five years of experience covering the additive manufacturing world. She has a particular interest in amplifying the voices of women working within the industry and is an avid follower of the ever-evolving AM sector. Tess holds a master's degree in Media Studies from the University of Amsterdam.

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