Researchers at the University of Pittsburgh are using multi-wavelength lights and neural networks to improve the finishing process of photopolymer additive manufacturing (PAM). Xiayun Zhao, an assistant professor of mechanical engineering and materials science at the institute, received a $657,610 award for faculty early professional development from the National Science Foundation for her research. Read on for more information.
Zhao’s research aims to develop a novel and intelligent digital light processing (DLP) method that takes advantage of photoinhibition induced by a second wavelength light to slow down the curing of parts. This process has been called DLP.2curb.
There are three main phases in the investigation. In the first, Zhao’s team will try to understand how DLP works.2curb the process works and how different materials behave under these conditions. This work will involve creating a digital twin, a complex computer model that will simulate how adjustments made to the process or material will change the outcome.
In the second part, the team will use tools such as ultrasonic and interferometric monitoring systems to observe the materials in real time.
In the third and final part, Zhao will develop a way to control the process in real time, using deep reinforcement learning from model predictions and on-site measurements to guide the printing process.
“Using a single wavelength to cure polymers during printing is already complex. Adding a second increases that complexity, but we can use machine learning to improve our accuracy and speed up our progress,” Zhao said.
“Conventional machine learning calculations take time and are not yet fast enough for real-time control, but the digital twin we will develop as part of this project based on next-generation physically informed neural networks will help. us in that effort.”
Zhao’s CAREER Award will also offer educational opportunities to prepare and encourage the next generation of leaders to pursue manufacturing-related careers and promote diversity in the STEM field. One of their outreach initiatives will be a collaboration with the Carnegie Science Center to host summer camps that will introduce students to AI-assisted additive manufacturing and metrology and give them hands-on experience with 3D printing in the manufacturing industry.
If successful, this research will have a significant impact on a number of applications, including biochips, electrodes, soft robots, and metamaterials.
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