Sisi Tian
Papers
5
Total Citations
178
H-Index
4
About
Dr. Sisi Tian is a leading researcher at the intersection of robotics, digital twin technology, and smart manufacturing. Her work focuses on developing intelligent frameworks for industrial cloud robotics, with a particular emphasis on enhancing the efficiency and adaptability of robotic assembly and disassembly processes. Dr. Tian’s most influential contribution is the "Digital twin-based industrial cloud robotics" framework, which has garnered 125 citations and provides a foundational approach for integrating real-time digital replicas with cloud-controlled robotic systems. She has further advanced the field by devising multi-level task rescheduling methods for robotic assembly lines, addressing critical challenges posed by dynamic disturbances such as processing time variations and advance deliveries. Her research also tackles the complexities of robotic disassembly sequence planning, specifically accounting for parts with uncertain failure features like wear and corrosion, which is vital for efficient remanufacturing. With a growing body of work that includes digital twin-enhanced optimization of manufacturing service scheduling and dynamic prediction methods for robotized production line performance, Dr. Tian is shaping the future of flexible, resilient, and data-driven manufacturing systems.
Research Focus
Key Achievements
Top Papers
- 1
- 2Digital twin-based multi-level task rescheduling for robotic assembly line28 citations · 2023
- 3Robotic disassembly sequence planning considering parts failure features18 citations · 2023
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- 5