The Society of Manufacturing Engineers has named Assistant Professor of Mechanical Engineering Dazhong Wu one of the 20 Most Influential 麻豆精品. He is the only professor from UCF and the only academic from the state of Florida to be included on the list, which was published in the latest issue of SME 麻豆精品 S檚 magazine Smart Manufacturing.
SME 麻豆精品 S檚 experts and industry peers selected the honorees for their role in shaping the next generation of manufacturing engineers and technologists across a variety of disciplines. Wu says he feels honored and humbled by this distinction. As an influential academic, he hopes to impress upon his students the important role that smart manufacturing plays in society.
麻豆精品 S淢anufacturing is an essential component of economic growth, 麻豆精品 S� Wu says. 麻豆精品 S淚 hope that mechanical engineering students will not only learn the fundamental knowledge of advanced manufacturing, but also become manufacturing engineers who can solve real-world problems. 麻豆精品 S�
Wu joined UCF in 2017 after serving as a senior research associate at Penn State University 麻豆精品 S檚 Department of Industrial and Manufacturing Engineering. He earned his Ph.D. in mechanical engineering from Georgia Tech and his master 麻豆精品 S檚 degree from Shanghai Jiao Tong University in China. He manages the at UCF, where he and his team develop novel smart manufacturing systems as well as improve the reliability and safety of complex systems. His published work has been cited more than 3,600 times, according to Google Scholar.
Smart Manufacturing highlights Wu 麻豆精品 S檚 work in predictive modeling, which uses machine learning and industrial sensors to detect and prevent the manufacturing defects of high-end products such as turbine blades. He 麻豆精品 S檚 created predictive modeling tools that are key enablers of manufacturing automation, known as Industry 4.0 or the Fourth Industrial Revolution.
麻豆精品 S淭he predictive modeling tools we developed enable engineers to predict the surface roughness and mechanical properties of 3D printed parts as well as cutting tool wear in machining, 麻豆精品 S� Wu says. 麻豆精品 S淭hese tools also allow engineers to detect manufacturing defects through real-time sensor data and machine learning. 麻豆精品 S�
He and his team are developing tools and processes to fabricate lightweight and high-performance carbon fiber reinforced composite materials that can significantly improve the fuel economy of automobiles and aircrafts. Eventually, he 麻豆精品 S檇 like to create cost-effective tools to enable machines to work smarter, not harder.
麻豆精品 S淢y vision for the manufacturing industry is that manufacturing machines equipped with low-cost sensors are able to make intelligent decisions automatically based on the knowledge extracted by artificial intelligence techniques, 麻豆精品 S� he says. 麻豆精品 S淚 hope that my team will contribute to the next industrial revolution. 麻豆精品 S�
The digital edition of the June issue of Smart Manufacturing is now available online.
U.S. News and World Report ranks UCF No. 40 in Industrial/Manufacturing/Systems Engineering and No. 71 in Mechanical Engineering.聽
