Souvik Bose

National Institute of Technology Durgapur

Papers

Total Citations

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About

Souvik Bose is a researcher at the forefront of advanced manufacturing and computational modeling, with a primary focus on robotic wire arc additive manufacturing (WAAM). His work bridges the gap between traditional fabrication and intelligent automation, leveraging artificial neural networks to enhance process control and material deposition. Bose’s most-cited paper, "Artificial neural Network-Based approaches for Bi-directional modelling of robotic wire arc additive manufacturing" (2022), has garnered 9 citations, reflecting its growing influence in the field. This study introduces a novel bi-directional modeling framework that optimizes both the prediction and control of WAAM processes, enabling more precise and efficient additive manufacturing. By integrating machine learning with robotic systems, Bose addresses critical challenges in thermal management and geometric accuracy, paving the way for scalable, high-quality production of complex metal components. His work is particularly relevant for industries seeking to reduce waste and improve repeatability in large-scale 3D printing. As a rising voice in manufacturing research, Bose’s contributions are shaping the next generation of smart, adaptive fabrication technologies, making him a key figure to watch in the evolution of additive manufacturing.