Y. Nukman
Papers
1
Total Citations
15
H-Index
1
About
Y. Nukman is a researcher whose work sits at the intersection of mechanical engineering, intelligent automation, and industrial safety. Their key research areas include non-destructive testing, image processing, and the application of fuzzy logic systems for defect detection. A major contribution is the development of an automatic visual inspection system for oil tank exterior surfaces, which integrates unmanned aerial vehicles (UAVs) with cascading fuzzy logic algorithms to identify critical defects like corrosion. This work, published in 2023, has already garnered 15 citations, reflecting its immediate relevance to the oil and gas industry’s need for safer, more efficient inspection methods. By combining UAV technology with advanced image processing, Nukman’s research addresses a pressing challenge: the early detection of surface defects that can compromise structural integrity and safety. Their approach not only reduces human risk in hazardous environments but also enhances the accuracy and speed of inspections. This notable achievement underscores Nukman’s role in advancing practical, AI-driven solutions for industrial maintenance, making their work a valuable reference for students and researchers exploring the convergence of robotics, computer vision, and fuzzy logic in real-world applications.
Research Focus
Key Achievements
Top Papers
- 1