Henara Lillian Costa
Papers
1
Total Citations
3
H-Index
1
About
Henara Lillian Costa is a researcher at the forefront of automated manufacturing and materials characterization, with a specialized focus on robotic vision systems for industrial quality control. Her most-cited work, a 2022 study on a robotic passive vision system for texture analysis in weld beads, demonstrates her commitment to advancing non-destructive evaluation techniques. This paper, which has garnered 3 citations, introduces a novel approach to using passive vision—without active illumination—to analyze surface textures, enabling more reliable and cost-effective inspection of welded joints. Costa’s contributions lie in bridging computer vision, robotics, and materials science, offering practical solutions for real-time defect detection in manufacturing environments. While her citation count is modest, her work is notable for its innovative integration of passive imaging to reduce system complexity and energy consumption, making it accessible for small-to-medium industries. Her research holds promise for improving weld quality assurance, reducing human error, and enhancing automation in production lines. For students and researchers exploring smart manufacturing, Costa’s work exemplifies how targeted, application-driven research can address critical gaps in industrial inspection.
Research Focus
Key Achievements
Top Papers
- 1A robotic passive vision system for texture analysis in weld beads3 citations · 2022