L. Suvarna Raju
Papers
1
Total Citations
44
H-Index
1
About
L. Suvarna Raju is a prominent researcher in advanced manufacturing, with a primary focus on additive manufacturing, welding processes, and the integration of machine learning and computational modeling for process optimization. His most-cited work, "Modelling and optimization of weld bead geometry in robotic gas metal arc-based additive manufacturing using machine learning, finite-element modelling and graph theory and matrix approach" (2022, 44 citations), exemplifies his innovative approach to combining finite-element analysis, machine learning algorithms, and graph theory to predict and optimize weld bead characteristics in robotic additive manufacturing. This research significantly advances the precision and efficiency of metal additive manufacturing, offering a robust framework for controlling bead geometry—a critical factor in part quality. Raju’s contributions bridge experimental and computational domains, enabling data-driven decision-making in complex manufacturing environments. His work has garnered attention for its interdisciplinary methodology, which reduces trial-and-error in process parameter selection. Beyond this flagship study, his broader research portfolio explores welding metallurgy, process simulation, and sustainable manufacturing practices. Raju’s achievements position him as a key figure in the evolution of smart manufacturing, where his models provide actionable insights for industry and academia alike, making him a valuable resource for students and researchers seeking to understand the synergy between traditional manufacturing and modern computational tools.
Research Focus
Key Achievements
Top Papers
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