Yanjie Su
Papers
1
Total Citations
4
H-Index
1
About
Yanjie Su is a researcher focused on advancing automation and quality control in semiconductor manufacturing. Their key research areas include robotic systems, defect detection technologies, and precision inspection for silicon wafer production. Su’s major contribution is the design of a compact, robot-based defect detection device for silicon wafers, addressing a critical challenge in chip manufacturing where manual inspection often falls short in accuracy and efficiency. This work, published in 2020, has garnered 4 citations, reflecting its relevance to improving automated quality assurance in the semiconductor industry. By integrating robotics with detection algorithms, Su’s design enhances the reliability and speed of identifying surface defects, a vital step for maintaining high chip quality. This innovation not only reduces human error but also supports the scalability of production processes. Su’s research is particularly notable for its practical engineering approach, offering a tangible solution to a pressing industrial problem. For students and researchers exploring automation in electronics manufacturing, Su’s work provides a clear example of how robotics can transform traditional inspection methods, paving the way for smarter, more efficient fabrication lines.
Research Focus
Key Achievements
Top Papers
- 1A compact Robot-based defect detection device design for silicon wafer4 citations · 2020