R. Santhosh

Papers

Total Citations

H-Index

About

R. Santhosh is a researcher advancing the intersection of industrial automation and intelligent manufacturing. His primary research areas include robotic process optimization, fuzzy logic systems, and machine learning integration for manufacturing efficiency. Santhosh’s most notable contribution is his 2024 study on optimizing the IRB1410 industrial robot painting process, where he pioneered the combination of the Taguchi method with fuzzy logic and machine learning to enhance precision and reduce waste. This work, already garnering 9 citations, demonstrates a practical approach to improving robotic applications in real-world production environments. His research stands out for its interdisciplinary methodology, bridging traditional statistical quality control with modern AI techniques. Santhosh’s achievements reflect a commitment to making industrial robotics more adaptive and efficient, offering valuable insights for both academic researchers and industry practitioners seeking to leverage data-driven decision-making in automation.