Papers
2
Total Citations
7
H-Index
1
About
Xingtao Su is a leading researcher in advanced manufacturing and digital twin technology, with a specific focus on robotic assembly systems and quality optimization. His work centers on developing high-fidelity digital twin models that bridge the gap between virtual simulations and real-world production processes. Su’s most impactful contribution, "Digital twin modeling of the robotic gluing system for predicting the quality of glue lines and optimizing gluing parameters" (2025), has already garnered 6 citations, demonstrating its immediate relevance to the field. In this study, he introduced a novel approach to predict adhesive line quality and optimize gluing parameters in real time, significantly reducing waste and improving assembly precision. His subsequent work, "A unified V-shaped digital twin modeling paradigm of aircraft assembly systems for improving modeling accuracy and assembly quality" (2025), further advances the field by proposing a standardized framework that enhances both modeling accuracy and overall assembly quality. Su’s research is particularly notable for its practical applications in aerospace manufacturing, where precision and reliability are paramount. Through his innovative digital twin paradigms, he is shaping the future of smart manufacturing and quality control.
Research Focus
Key Achievements
Top Papers
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- 2