Yoshit Tiwari

Central Mechanical Engineering Research Institute

Papers

Total Citations

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About

Yoshit Tiwari is a researcher at the forefront of advanced manufacturing and computational modeling, with a primary focus on robotic wire arc additive manufacturing (WAAM) and the integration of artificial neural networks (ANNs) into production processes. His most-cited work, "Artificial Neural Network-Based Approaches for Bi-directional Modelling of Robotic Wire Arc Additive Manufacturing" (2022), has garnered 9 citations, marking a significant contribution to the field. In this study, Tiwari pioneered the use of ANNs to predict and optimize the bidirectional deposition process in WAAM, addressing critical challenges in layer geometry, heat management, and material efficiency. By enabling real-time, data-driven adjustments, his research enhances the precision and reliability of large-scale metal additive manufacturing, reducing waste and production time. This work bridges the gap between machine learning and industrial robotics, offering a scalable solution for complex, custom components. Tiwari’s achievements underscore his role in advancing smart manufacturing, where AI-driven models transform traditional welding into a high-fidelity, automated process. His innovative approach not only improves part quality but also sets a foundation for future research in adaptive manufacturing systems, making him a key figure in the evolution of Industry 4.0 technologies.