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About

P. Thamilarasi is a researcher specializing in robotic welding processes, manufacturing automation, and process optimization — fields that sit at the intersection of advanced manufacturing and intelligent systems. Their work has made meaningful contributions to the understanding and improvement of Gas Metal Arc Welding (GMAW) processes in robotic environments, with a particular focus on weld bead geometry modeling and process parameter optimization. Among their most notable contributions is the application of linear regression techniques and MATLAB-based modeling to establish relationships between critical welding parameters — including arc current, arc voltage, stick-out, and welding speed — and resulting weld bead characteristics. Complementing this, Thamilarasi has employed Taguchi parametric design methods to systematically optimize these parameters for IS 2062 E250 BR steel, enhancing both weld quality and process efficiency. Their empirical modeling work further supports predictive control in robotic welding applications. Thamilarasi's early review work on machine vision-assisted robotic welding demonstrated a forward-thinking perspective on automation's role in improving shop-floor productivity and product quality. With cumulative citations across multiple publications, their research has provided a useful foundation for engineers and academics working to advance intelligent, automated welding systems in modern manufacturing environments.