Recently, competing against universities nationwide, Bin Chen received two major grants from the Department of Energy for recycling research projects. The first is funding a two-year, $100,000 effort to help UHV Technologies Inc. create a machine to sort a variety of recyclable plastic bottles for conversion into chemicals and/or other usable materials. As the crushed bottles roll down a conveyor belt, an overhead camera system utilizing AI recognizes their types and sorts them rapidly into one of eight or more possible classifications. The development is in the prototype phase and has the potential of being a much more accurate and efficient process than was previously available. The goal is to drive production costs below $30 per ton.
Initial results were above the energy department鈥檚 requirements for accuracy and other measures, Chen said, which led to an approval for the product to remain in the research and development phase for two full years before moving to commercialization. 鈥淚 believe AI will be, or is increasingly being, integrated into manufacturing processes,鈥� Chen said. 鈥淭raditionally, many of these processes rely on human judgment and expertise. The latest advancements in AI鈥攆or example in computer vision鈥攃an improve productivity and automate many labor-intensive tasks. The manufacturing industry looks for new engineering graduates who have specific AI knowledge.鈥�
The second grant of $461,071 was submitted again with UHV Technologies and Penn State University to work on sorting batteries for recycling. This three-year project starts this month with the goal of increasing consumer participation in battery recycling programs, improving the economics of recycling, and establishing state and local collection programs. Chen鈥檚 areas of responsibility include designing and developing a sorting AI engine similar to the one for plastic bottles.