P. P. Murugan
Papers
2
Total Citations
110
H-Index
2
About
P. P. Murugan is a leading researcher at the intersection of advanced manufacturing, robotics, and deep learning. His work focuses on integrating artificial intelligence into industrial processes, particularly in robotic abrasive belt grinding and automated quality control. Murugan’s most impactful contribution is the development of an in-process virtual verification system for weld seam removal, which uses deep learning to monitor and validate grinding operations in real time—a breakthrough that enhances precision and reduces waste in manufacturing. This seminal paper has garnered 97 citations, reflecting its influence on both academia and industry. He has also advanced the field of computer vision by implementing deep convolutional neural networks for multi-class categorical image classification, demonstrating how ConvNet architectures can be optimized for complex tasks such as robotic vision and autonomous systems. Murugan’s work bridges the gap between theoretical machine learning and practical engineering, offering scalable solutions for smart factories. His research is essential reading for students and engineers interested in the future of intelligent automation, where AI-driven systems ensure quality and efficiency in real-world production environments.
Research Focus
Key Achievements
Top Papers
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