Self-service systems, such as electrical vehicle charging piles, are often deployed in a fleet at a designated location. These systems may fail either while idle or during customer use. If the system initially chosen by a customer is nonfunctional or fails during service, the customer may switch to another available system for service. This phenomenon is called failure-induced demand switching (FDS). To maximize the long-run profit of the fleet, the operator must balance revenue with operation and maintenance costs, by conducting appropriate maintenance actions. However, it is challenging to develop an optimal maintenance policy due to FDS. This talk defines and assesses the service level of such systems in terms of the proportion of demands being completed in the long run, and proposes a three-dimensional maintenance policy to maximize the fleet’s long-run profit rate. The insights are expected to guide the operators of such systems in enhancing their profitability.
Professor Cheng’s research mainly lies in reliability and resilience modeling and optimization of both generic systems and engineered systems in the new energy sector. Her research has been published in leading journals in the reliability and IE field such as IISE Transaction, Reliability Engineering and System Safety, IEEE Transactions on Industrial Informatics, IEEE Transactions on Reliability, International Journal of Production Research, and Transportation Science. Her research also has been funded by the Research Grant Council, University Research Council, and Industry.
Clean water and clean air are vital for public health. This project focuses on developing high-efficiency and environmentally sustainable filters for removing harmful air/water pollutants. The team has developed novel architectures and functionalities for the filters to achieve high permeance, high removal efficiency, and excellent reusability.
