On October 29-30, the final of the 17th “IE Liangjian” National Industrial Engineering Application Case Competition was held. The graduate and undergraduate group from the Department of Industrial Engineering and Management of the School of Mechanical Engineering both won the grand prize awards.

Introduction to the Grand Prize Project of the Graduate Group

Project name: Remote intelligent monitoring and diagnosis platform based on big data and industrial Internet for the world's first 300MVar dual water internal condenser

Project members: Tongtong Yan, Yu Wang, Yuting Wang, Yikai Chen, Yanqing Deng

Instructors: Dong Wang, Tangbin Xia, Jian Dai, Zhike Peng

To help achieve carbon peaking and carbon neutrality goals and meet the urgent needs of the intelligent operation and maintenance of the condenser, this study proposed three advanced methodologies and developed three key technologies for condenser health monitoring, including anomaly monitoring technology based on a digital twin model and statistical process control, performance degradation trend prediction technology based on convex optimization, data fusion and Bayesian theory and fault diagnosis technology based on binary tree. Afterward, three key technologies were integrated to develop a remote intelligent monitoring and fault diagnosis platform for the world's first 300MVar dual water internal condenser, which realizes intelligent monitoring and diagnosis, data visualization, analysis, and interaction. Moreover, the proposed remote intelligent monitoring and diagnosis platform of the condenser based on big data and industrial Internet has been stably applied in many power plants.

Introduction to the Grand Prize Project of the Undergraduate Group

Project name: Logistics network design based on cross-regional transportation strategy

Project members: Rui Guan, Ziyu Mao, Xinyu Jiang, Ziang Xu, Jing Qi

Instructors: Yaoming Zhou, Wei Qin

This project proposed a logistics network design scheme based on a cross-region transportation strategy to cope with the improved transportation cost by third-party logistics companies. The complexity of the model is reduced by setting up a dummy warehouse, making it possible to solve the problem quickly. In addition, a simulation tool of the supply chain network system was developed to enhance the dynamics and visibility of the results. Moreover, a generalized program software was built for sensitivity analysis to cope with unstable situations in future operations. This work provides a method to effectively handle the logistics planning challenges facing cost fluctuations and has a good promotion value for similar enterprises.

This competition was organized and co-organized by the Department of Industrial Engineering of Tsinghua University, the General Office of the Chinese Association of Science and Technology, the Industrial Engineering Branch of the Chinese Mechanical Engineering Society, Dongfeng Nissan Passenger Vehicle Company, etc. In the track for university graduate students and enterprises, 12 teams advanced to the finals, respectively, while in the track for undergraduate students, the top 30 teams in the national industrial engineering professional course design exhibition were selected for the finals. The competition promoted the exchange of experience in cultivating talents in industrial engineering, improved the quality of cultivating talents in industrial engineering, and enhanced the students' ability to analyze and solve problems systematically with their professional knowledge.