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About

E. Mohankumar is a researcher specializing in robotic welding technologies, process optimization, and automation systems, with a particular focus on Gas Metal Arc Welding (GMAW). His work bridges the gap between advanced manufacturing processes and computational modeling, making significant contributions to the field of robotic welding engineering. Mohankumar's most impactful contributions include developing empirical and mathematical models for predicting weld bead geometry in robotic GMAW systems. Using linear regression techniques and MATLAB-based scripting, he established critical relationships between welding parameters — including arc current, stick out, arc voltage, and welding speed — and the resulting weld quality. His application of Taguchi parametric design and optimization techniques to IS 2062 E250 BR steel joints has provided practical frameworks for achieving superior weld bead geometry in industrial settings. Beyond process modeling, his review work on machine vision-integrated robotic welding systems has helped map the trajectory of intelligent automation in manufacturing environments, highlighting pathways to improved productivity and product quality. His published works have collectively accumulated citations from researchers and engineers working across welding technology, manufacturing automation, and process optimization. Mohankumar's research serves as a valuable resource for students and professionals seeking to understand the intersection of robotics, welding science, and data-driven process control.