Courtesy of Adrita Dass

The graduate student team won a NASA grant for their innovations in sensing defects in 3D-printed products. Pictured here are Siddharth Patel, previous member Benjamin Steeper, Adrita Dass and Chenxi Tian (left to right), while non-pictured members include Selina Kirubakar and Sai Pratyush Akula.

November 16, 2021

Student Team Awarded NASA Grant for 3D Printing Acoustic Sensor

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A Cornell team led by Adrita Dass grad, who studies mechanical and aerospace engineering, is developing technology that could revolutionize the manufacturing industry. 

The five-person team was awarded a grant of up to $80,000 through NASA’s University Student Research Challenge earlier this year for their proposed 3D printing sensor. The technology aims to make the 3D printing process more cost effective and robust.

Dass explained that additive manufacturing — a term often used interchangeably with 3D printing — is a method of production where parts are built in successive layers, from the bottom up. This method contrasts the more conventional approach of subtractive manufacturing, where material is shaved and cut from a starting block to create the final product. 

The team’s mentor, Prof. Atieh Moridi, mechanical and aerospace engineering, said additive manufacturing has a number of advantages over traditional subtractive methods, including the ability to create complex shapes, reduce material waste and simplify the supply chain.

Despite these advantages, many industries have been slow to adopt additive manufacturing. One major reason for this is that the process is prone to defects, according to Moridi.

Moridi explained that 3D printing relies on the melting and resolidification of a raw material, processes that involve many random and unpredictable interactions. These interactions can lead to defects in the final product that harm its mechanical performance, according to Moridi.

Chenxi Tian grad, who studies mechanical and aerospace engineering, explained that the team’s goal is to find a way to detect these manufacturing defects as they form.

“What we are proposing is basically a real-time forecasting system for additive manufacturing to detect defects happening during the 3D printing of metallic components,”  Tian said. “Currently, a lot of defects in the 3D printing process are only captured after the part is produced.”

Post-production correction of defects is difficult and cost intensive, whereas the team’s real-time sensor has the potential to allow manufacturers to correct defects as soon as they occur, streamlining the production process.

The team’s idea hinges on an acoustic sensor that detects signals emitted from the material during production.

“When defects or cracks form inside the material, they make a sound,” Moridi said. “It’s not something we can hear with our ears, but there are special sensors that can detect them.” 

Dass explained that acoustic sensing, in contrast to many imaging methods currently used in additive manufacturing, detects defects that form inside the material, rather than merely on the surface. This offers a much more powerful level of insight into where and how defects form, according to Dass.

“What’s interesting is these acoustic emission sensors have been used a lot in the past,” Moridi said. “But now we’re trying to use them to listen to the additive manufacturing process, and it’s a rich data intensive signal — just uncoding what that [data] means is an entertaining exercise.”

The team hopes to analyze this acoustic emission data to better understand the physical processes underlying defect-formation during 3D printing. To accomplish this, they will be using the Cornell High Energy Synchrotron Source — a high-intensity X-ray source — to acquire X-ray diffraction data of materials undergoing the 3D printing process. X-ray diffraction involves directing a beam of X-rays at a sample and measuring the outgoing signal. 

Dass explained that by analyzing how data from synchrotron X-ray diffraction and their acoustic sensor develop over time, the team can gain insight into the fundamental physics behind the acoustic signals they measure.

Using the X-ray diffraction data, the team will create a model correlating defects with different acoustic signals, so that manufacturers — such as those in the aerospace and medical industries — can use the cheaper and more accessible technology of acoustic sensing to detect and characterize defects, according to Dass.

In the long term, the team hopes to see their sensor integrated with technologies that correct defects during production, preventing the need for costly post-processing of the product after printing.

Winning the NASA challenge grant was a critical step in the team’s ongoing effort. In addition to the funding, the team has weekly meetings with NASA, which has allowed them to learn more about the additive manufacturing industry.

“Having a connection to NASA, which is one of the pioneer users of such technology, will help us overcome a lot of obstacles that you typically run into in development,” Tian said.

Dass added that the team’s connection to NASA will add credibility to potential future efforts toward commercialization.

As required by NASA, the team has also launched a crowdfunding campaign to cover a portion of their costs and raise awareness among the general public about their work. This requirement aims to encourage entrepreneurial action and public outreach, according to NASA.