Mohammad Vakilinejad
Papers
2
Total Citations
15
H-Index
2
About
Mohammad Vakilinejad is a researcher specializing in robotic machining and precision manufacturing, with a focus on enhancing the accuracy and reliability of industrial robots. His work addresses critical challenges in robotic manipulation, particularly the reduction of geometrical and transmission errors that limit robot applicability in high-precision tasks. In his most cited paper, "Geometrical error improvement of Aramid honeycomb workpieces in robot-based triangular knife ultrasonic cutting process" (2020, 10 citations), Vakilinejad developed methods to improve machining quality for advanced composite materials, demonstrating practical solutions for aerospace and lightweight manufacturing. His earlier study, "Identification and Compensation of periodic gear transmission errors in Robot Manipulators" (2019, 5 citations), tackled nonlinear joint errors that cause path inaccuracies in robotic machining—a key obstacle to broader industrial adoption. By identifying and compensating for periodic gear transmission errors, his work contributes to achieving higher positional accuracy in robot manipulators. Vakilinejad’s research bridges the gap between theoretical error modeling and real-world machining applications, offering valuable insights for students and engineers seeking to optimize robotic systems for complex manufacturing tasks.
Research Focus
Key Achievements
Top Papers
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