With the rapid development of sensing, communication, computing technologies, and analytics techniques, today’s manufacturing is marching towards a new generation of sustainability, digitalization, and intelligence. Even though the significance of both sustainability and intelligence is well recognized by academia, industry, as well as governments, and substantial efforts are devoted to both areas, the intersection of […]
A multi-object tracking algorithm developed by Siyuan Chen is ranked top in the tracking task leaderboard of the UA-DETRAC dataset. UA-DETRAC is a challenging real-world multi-object detection and multi-object tracking benchmark. The dataset consists of 10 hours of videos captured with a Cannon EOS 550D camera at 24 different locations at Beijing and Tianjin in China. […]
With the rapid development of sensing, communication, and computing technologies and infrastructure, today’s manufacturing industry is marching towards a big data era and a new generation of digitalization and intelligence. The availability of big data provides us with a golden opportunity to promote smart manufacturing. Nevertheless, the deployment and popularization of big data analytics in manufacturing are still at its nascent stage. […]
High-speed electric multiple units (EMUs) have been popularized rapidly all around the world and have become a major transportation method. The working mechanism of rail grinding has not been investigated theoretically. This study develops flexible car body and human body models based on the rigid-flexible coupled method to systematically study the effects of wheel-rail wear […]
We are pleased to announce that Qasim Nazir, Hao Wu and Lucy Sun join our ADM Lab in this semester. Mr. Qasim Nazir is a M.S. student in the Department of Mechanical Science and Engineering at UIUC. He received his B.S. degree in Mechanical Engineering from National University of Sciences & Technology, Pakistan in 2015. Mr. Hao Wu is a one […]
Our project “Roll-to-Roll Manufactured Hybrid Metal-Polymer Heat Exchangers with Anti-Fouling and Self-Monitoring for Waste Heat Recovery” is funded by the U.S. Department of Energy (DOE). We will collaborate with Prof. Sinha, Prof. Miljkovic, Prof. Ferreira and Prof. Salapaka to develop an innovative waste heat recovery method that aims to resolving the long-standing challenges of low-grade heat recovery through four instinctive […]
Prof. Chenhui Shao was named to SME’s 2018 class of 30 Under 30 honorees, a program that recognizes individuals who exemplify extraordinary promise in manufacturing and the STEM skills that support the discipline. The program is designed to recognize and encourage young people who can make a difference in manufacturing, whether on the shop floor, in an engineering or R&D […]
High-resolution spatial data are essential for characterizing and monitoring surface quality in manufacturing. However, the measurement of high-resolution spatial data is generally expensive and time-consuming. Interpolation based on spatial models is a typical approach to cost-effectively acquire high-resolution data. Conventional modeling methods fail to adequately model the spatial correlation induced by periodicity, and thus their […]