A paper entitled “hybrid multi-task learning-based response surface modeling in manufacturing” is recently published in the Journal of Manufacturing Systems. The paper was co-authored by Yuhang Yang and Chenhui Shao. This paper developed a hybrid multi-task learning-based method tocost-effectively model the response surfaces of multiple similar-but-not-identical manufacturing processes. The method was evaluated using a simulation-based numerical […]
Publication
Review Paper on Data-Driven Intelligent 3D Surface Measurement Published in Machines
A feature article titled “data-driven intelligent 3D surface measurement in smart manufacturing: review and outlook” has been published in Machines recently. The paper was co-authored by Yuhang Yang, Zhiqiao Dong, Yuquan Meng and Chenhui Shao. This paper reviewed and summarized existing research in interpolation and sampling design techniques in various manufacturing scenarios, which can potentially […]
Paper on Multi-Task Learning of Spatiotemporal Processes Published in JMS
A paper entitled “multi-task learning for data-efficient spatiotemporal modeling of tool surface progression in ultrasonic welding” is recently published in the Journal of Manufacturing Systems. The paper was co-authored by Haotian Chen, Yuhang Yang, and Chenhui Shao. This paper developed a multi-task learning method to enable data-efficient spatiotemporal modeling. The method was evaluated using tool […]
Yuquan’s Work on Multi-Objective Optimization Published in AIMS MBE
Ultrasonic metal welding (UMW) is a solid-state joining method with various industrial applications including battery assembly, automotive body construction, and electronic packaging. Among the advantages of UMW over conventional fusion welding are the ability to join dissimilar metals, reduced energy consumption and short welding time. Despite of its numerous advantages, this technique has a relative […]
Siyuan and Yuquan’s Work on Fault Diagnosis Published in IEEE/ASME Transactions on Mechatronics
Fault diagnosis for rolling elements in rotating machinery persistently receives high research interest due to the said machinery’s prevalence in a broad range of applications. State-of-the-art methods in such setups focus on effective identification of faults that usually involve a single component while rejecting noise from limited sources. This paper studies the data-based diagnosis of […]
Boge and Siyuan’s Work on Human Action Detection and Monitoring Published in Computers in Industry
This paper presents a new approach for temporal detection of short human activities in untrimmed videos. Most present methods for temporal action detection, to our best knowledge, are trained on public action datasets that feature actions spanning up to tens and hundreds of seconds. However, it is often desired in manufacturing, transportation, and other safety-critical […]
Yuhang’s Work on Hierarchical Measurement Strategy Published in Journal of Manufacturing Systems
High-resolution spatiotemporal data is crucial for characterizing, modeling, and monitoring the space-time dynamics of complex systems in manufacturing. However, the acquisition of such data is generally expensive and time-consuming. Spatiotemporal interpolation aims to predict the values at unmeasured locations using measured data, and emerges as a promising solution to cost-effectively characterizing spatiotemporal processes. Since the […]
Kai, Zheng, and Hao’s Work on Rail Profile Design Published in Journal of Rail and Rapid Transit
High-speed electric multiple units have numerous advantages. However, a number of critical maintenance issues arise in the operation of high-speed electric multiple units. The previous researches about rail profile design usually take only a single type of wheel profile into account, which would cause some other problems such as severe increase of hollow wear on […]
Yuquan and Yuhang’s Review on Sustainability in Smart Manufacturing Published in MDPI Sustainability
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 […]
Yuhang’s Work on Big Data Analytics and Surface Finishing Process Presented in ASME MSEC 2018
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. […]