Alok Kumar Das
Papers
6
Total Citations
85
H-Index
5
About
Alok Kumar Das is an emerging researcher specializing in Wire Arc Additive Manufacturing (WAAM), a cutting-edge metal additive manufacturing technique that has gained significant industrial relevance in recent years. His work sits at the intersection of advanced manufacturing, materials science, and artificial intelligence, with a particular focus on optimizing process parameters to enhance the quality and performance of metal components produced through robotic WAAM systems. Das has made notable contributions to understanding how process variables influence bead geometry, microstructure, mechanical properties, and surface characteristics in aluminum and copper-silicon alloys. His pioneering integration of machine learning into WAAM workflows — aimed at minimizing surface roughness and estimating deposition rates — represents a forward-thinking approach to intelligent manufacturing. His 2024 paper on machine learning-driven surface roughness optimization has already garnered 28 citations, reflecting strong community interest in this direction. Beyond material characterization, his investigations into path planning strategies demonstrate a holistic understanding of robotic WAAM systems. With a growing citation record across multiple high-impact studies, Das is establishing himself as a promising voice in the field of smart, process-optimized metal additive manufacturing.
Research Focus
Key Achievements
Top Papers
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