Tahvilian Masoud Amir
Papers
1
Total Citations
3
H-Index
1
About
Masoud Amir Tahvilian’s research lies at the intersection of robotics, manufacturing, and dynamic systems, with a particular focus on improving precision in industrial robotic processes. His most-cited work, "Identification of frequency response functions of a flexible robot as tool-holder for robotic grinding process" (2016), addresses a critical challenge in automated machining: the vibration and deflection of flexible robot arms during grinding operations. By comparing three identification approaches—spectral method, ARX model, and State Space model—Tahvilian provided a systematic framework for characterizing a robot’s dynamic behavior under real-world loads. This contribution is essential for enhancing the accuracy and surface quality of robotic grinding, a key process in aerospace and automotive manufacturing. With 3 citations, his work has informed subsequent studies on robot stiffness and chatter mitigation. Tahvilian’s research bridges theoretical system identification with practical industrial applications, offering tools that help engineers design more reliable and precise robotic tool-holders. His efforts underscore the importance of dynamic modeling in advancing flexible automation for high-tolerance tasks.
Research Focus
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Top Papers
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