Researchers Add Printer Limitation Context to the 3D Printing Process to Boost Reliability

New algorithm takes into account exactly how a printer works to design more reliable 3D-printed parts — and possibly unlock new materials.

ghalfacree
about 20 hours ago 3D Printing

Researchers from the Massachusetts Institute of Technology have come up with a way to create more reliable 3D-printed parts — and hope it could be used to unlock new materials, as well as improve the performance of existing materials where it matters.

"If you don’t account for [inherent] limitations, printers can either over- or under-deposit material by quite a lot, so your part becomes heavier or lighter than intended. It can also over- or underestimate the material performance significantly," explains associate professor of civil and environmental engineering Josephine Carstensen, co-author on the team's paper. "With our technique, you know what you're getting in terms of performance because the numerical model and experimental results align very well."

Researchers have detailed a new algorithm that takes printer limitations into account to deliver more reliable 3D-printed parts. (📷: Kim-Tackowiak)

That technique: topology optimization, the process of tweaking the shape of an object, using context including nozzle constraints and material bead size, the strength of layer bonds, and the path the extruder takes during the printing process. "We thought, 'We know these limitations in the beginning, and the field has gotten better at quantifying these limitations, so we might as well design from the get-go with that in mind,'" explains first and corresponding author Hajin Kim-Tackowiak.

An algorithm which takes into account the context of the printer being used, along with delivering specific control of the print-head's path, was developed that, the researchers say, is able to boost the reliability of printed parts at a range of material densities. "It was rewarding to see that putting more context into the design process makes your final materials more accurate," says Kim-Tackowiak. "It means there are fewer surprises. Especially when we're putting so much more computational resources into these designs, it's nice to see we can correlate what comes out of the computer with what comes out of the production process."

Tests showed that the optimization algorithm delivered prints which more reliably matched their designs across a range of densities. (📷: Kim-Tackowiak)

“We'd like to see this enable the use of materials that people have disregarded because printing with them has led to issues," Kim-Tackowiak adds of future directions for the team's work. "Now we can leverage those properties or work with those quirks as opposed to just not using all the material options we have at our disposal."

The project is detailed in a paper published in the journal Materials & Design under open-access terms.

ghalfacree

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