Tomoya Nagatmi

Papers

Total Citations

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About

Tomoya Nagatmi is a researcher in advanced manufacturing and robotics, with a focus on intelligent control systems for machining processes. His work centers on integrating fuzzy reasoning and neural networks to enhance the precision and autonomy of industrial robots, particularly in material processing applications. Nagatmi's most cited paper, "Application of fuzzy reasoning and neural network to feed rate control of a machining robot" (2016, 4 citations), presents a novel approach to optimizing feed rate control for a machining robot designed to work with foamed polystyrene materials. By incorporating a robotic CAM system, he enabled teachingless operation, reducing manual programming effort. His key contribution lies in developing a fuzzy reasoning method that processes radius of curvature to skillfully adjust machining parameters, improving surface quality and operational efficiency. Though his citation count is modest, Nagatmi's work demonstrates a practical integration of AI-driven control in manufacturing, offering a foundation for adaptive robotic systems. His research is particularly relevant for students and engineers exploring intelligent automation in material processing, showcasing how fuzzy logic and neural networks can bridge the gap between human skill and robotic precision.