In accordance with the College of Texas at Arlington (UTA), Chen Kan, an assistant professor within the Industrial, Manufacturing, and Techniques Engineering Division, has obtained a School Early Profession Growth Program award from the Nationwide Science Basis to advance his analysis and training initiatives.
The award, referred to as CAREER, is the NSF’s highest honor for junior college. It acknowledges excellent researchers who’re poised to grow to be leaders in each academic excellence and within the integration of training and analysis at their house establishments.
The $500,000 grant will allow Dr. Kan to combine superior sensing and synthetic intelligence to observe and optimize the additive manufacturing course of for metamaterials – engineered supplies with mechanical and different properties that aren’t present in nature.
Typically utilized in aerospace and well being care functions, metamaterials derive their distinctive properties from exactly fabricated geometries. Nonetheless, imperfections can happen in the course of the AM course of. A few of these flaws could render the ultimate product unusable, whereas others could have little impact. Kan goals to uncover the complicated relationship between imperfections and materials properties, enabling corporations to establish which defects considerably affect efficiency – finally enhancing manufacturing selections and outcomes.
To assist his analysis, Chen Kan will deploy a number of sensing gadgets to gather information on metamaterials all through the manufacturing course of. As fabrication progresses, he’ll use machine studying to investigate the info and detect imperfections. His purpose is to scale the algorithm to be used throughout a spread of processes and supplies.
“The algorithm shouldn’t be for one particular utility,” stated Kan. “It may be utilized to several types of metamaterials. It may actually assist small- to medium-sized corporations concerned in metamaterial manufacturing, as they gained’t have to coach an AI mannequin from scratch. They will simply deploy the mannequin and use it to enhance their merchandise and make their processes extra environment friendly.”
Kan’s analysis pursuits embrace superior manufacturing, high quality management, anomaly detection and machine studying.
“This recognition demonstrates his modern work in advancing additive manufacturing of property-certified metamaterials. His accomplishments deliver distinction to our division and exemplify the power and affect of our college at UTA,” stated Jeremy Agor, from the Faculty of Engineering at UTA.
