Papers
2
Total Citations
10
H-Index
2
About
Shaowu Nie is a researcher focused on precision manufacturing and mechanical transmission systems, with particular expertise in gear grinding processes and robot reducer assembly. His work addresses critical challenges in high-accuracy mechanical components, where even minor errors can significantly impact performance. Nie’s most-cited paper, “Prediction and experimental study on thermal stress in multi-tooth form grinding of cycloid gear” (2021), has garnered 8 citations and provides essential insights into thermal deformation during gear manufacturing—a key factor affecting precision and durability. More recently, his 2024 study, “A prediction method for the backlash error of robot precision reducers based on optimal assembly,” introduces a novel approach to predicting and minimizing backlash, a critical performance indicator for robotic systems. This work directly supports the advancement of industrial robots by improving kinematic accuracy and service life through optimized assembly techniques. Nie’s contributions bridge theoretical modeling and experimental validation, offering practical solutions for enhancing the reliability of precision reducers used in robotics and automation. His research is valuable for engineers and researchers working to push the boundaries of mechanical precision in modern manufacturing.
Research Focus
Key Achievements
Top Papers
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