Papers
1
Total Citations
3
H-Index
1
About
Farooq Shaik is a forward-thinking researcher at the intersection of robotics, manufacturing automation, and artificial intelligence. His work centers on enhancing industrial robotic systems through intelligent control and optimization, with a particular focus on welding automation. Shaik’s most-cited study, "Optimizing ABB MIG welding robot through polynomial trajectory planning and artificial intelligence integration" (2025, 3 citations), tackles a critical bottleneck in advanced manufacturing: the mathematical complexity of robot trajectory planning. By integrating artificial neural networks (ANN) into the ABB MIG welding robot’s control framework, he demonstrates how AI can bypass cumbersome derivations to achieve smoother, more efficient motion paths. This contribution is especially notable for its practical impact—bridging theoretical optimization with real-world industrial application. Shaik’s approach offers a scalable blueprint for modernizing legacy robotic systems, reducing computational overhead while improving precision. His work signals a shift toward data-driven, AI-augmented manufacturing, making him a key voice in the ongoing evolution of smart factory technologies.
Research Focus
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Top Papers
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