T A Thushar
Papers
1
Total Citations
5
H-Index
1
About
T. A. Thushar is a researcher focused on advanced manufacturing and surface engineering, with a particular emphasis on robotic spray painting and nano-coating technologies. Their work bridges the gap between traditional industrial processes and intelligent optimization methods. Thushar’s major contribution lies in the application of Taguchi-fuzzy logic-neural network hybrid approaches to systematically analyze and improve surface quality in automated painting systems. In their most cited study (2020, 5 citations), they employed a Taguchi L9 orthogonal array to investigate how robot parameters—distance, pressure, and speed—affect the surface roughness of Cold Rolled Close Annealed (CRCA) steel workpieces when using nano paint. This work demonstrates a practical, data-driven methodology for enhancing finish consistency in industrial robotics. While their citation count is modest, Thushar’s research is notable for integrating computational intelligence with real-world manufacturing challenges, offering a replicable framework for optimizing process parameters. Their findings are particularly relevant for industries seeking to reduce defects and improve efficiency in automated painting lines, making their work a valuable reference for students and engineers exploring smart manufacturing and surface quality control.
Research Focus
Key Achievements
Top Papers
- 1