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About

Harry Bikas is a researcher specializing in robotic manufacturing, machining process optimization, and additive manufacturing, with a particular focus on bridging the gap between industrial robotics and advanced production systems. His work addresses one of the most pressing challenges in modern manufacturing: enabling industrial robots to perform high-precision machining operations that traditionally required rigid CNC infrastructure. Bikas has made significant contributions to simulation-driven process planning for robotic machining, developing methodologies that optimize robot posture, cutting forces, and path planning to overcome the inherent structural limitations of serial-chain industrial robots. His 2022 paper on multi-body dynamic simulation of CAM-driven machining robots (22 citations) and his 2024 optimization framework (20 citations) reflect his leadership in this rapidly evolving field. Notably, his development of cutting force estimation through joint current signals offers a practical, non-intrusive sensing approach that enhances real-time process monitoring. Beyond machining, Bikas has explored concrete-based additive manufacturing and hybrid manufacturing systems, advocating for portable, flexible robotic cells that integrate multiple production processes. His research on digital twins further demonstrates his commitment to embedding intelligent simulation tools early in the design lifecycle, making him a notable voice in the future of smart, robot-driven manufacturing.