MIT CSAIL taps AI to reduce sheet metal waste

Researchers at MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) say they’ve created an AI-powered tool that provides feedback on how different parts of laser-cut designs should be placed onto metal sheets. By analyzing how much material is used in real time, they claim that their tool — called Fabricaide — allows users to better plan designs in the context of available materials.

Laser cutting is a core part of industries spanning from manufacturing to construction. However, the process isn’t always efficient. Cutting sheets of metal requires time and expertise, and even the most skillful users can produce leftovers that go to waste.

Fabricaide ostensibly solves this with a workflow that “significantly” shortens the feedback loop between design and fabrication. The tool keeps an archive of what a user has done, tracking how much of each material they have left and allowing the user to assign multiple materials to different parts of the design to be cut. This simplifies the process so that it’s less of a headache for multimaterial designs.

Fabricaide also features a custom 2D packing algorithm that can arrange parts onto sheets in an efficient way, in real time. As the user creates their design, Fabricaide optimizes the placement of parts onto existing sheets and provides warnings if there’s insufficient material, with suggestions for material substitutes.

Fabricaide acts as an interface that integrates with existing design tools and is compatible with computer-assisted design software like AutoCAD, SolidWorks, and Adobe Illustrator. In the future, the researchers hope to incorporate more sophisticated properties of materials, like how strong or flexible they need to be.

“By giving feedback on the feasibility of a design as it’s being created, Fabricaide allows users to better plan their designs in the context of available materials,” Ticha Sethapakdi, a Ph.D. student who led the development of Fabricaide alongside MIT professor Stefanie Mueller, said in a statement. “A lot of these materials are very scarce resources, and so a problem that often comes up is that a designer doesn’t realize that they’ve run out of a material until after they’ve already cut the design. With Fabricaide, they’d be able to know earlier so that they can proactively determine how to best allocate materials.”

The AI in manufacturing market is expected to be valued at $1.1 billion in 2020 and is likely to reach $16.7 billion by 2026, according to Markets and Markets. AI-based solutions like Fabricaide, if commercialized, could help manufacturers to transform their operations by playing a crucial role in automating stages of manufacturing and augmenting human work.