Jokin Muñoa

Ideko (Spain), University of the Basque Country

Papers

Total Citations

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About

Jokin Muñoa is a leading researcher in the intersection of robotics and advanced manufacturing, with a primary focus on robotic assisted machining and chatter suppression. His work addresses critical challenges in machining light alloys and thin-walled structures, where vibration and deformation limit productivity. Muñoa’s major contribution lies in developing methods to enhance robotic stiffness and predict dynamic behavior, enabling more stable and efficient milling processes. His 2018 paper on robotic assisted milling for increased productivity, with 49 citations, is a cornerstone in the field, demonstrating how robots can locally stiffen parts to suppress regenerative vibrations. His 2019 work on frequency response prediction for robot assisted machining further advanced the simulation of dynamic interactions, while his 2025 paper on the directional factor as a key for chatter-free milling of light alloys introduces a novel framework for optimizing robotic operations. With a cumulative citation impact exceeding 60, Muñoa’s research bridges simulation and practical application, offering transformative solutions for high-precision manufacturing. His achievements underscore a commitment to pushing the boundaries of robotic machining, making him a pivotal figure for students and researchers exploring automation in production.