Qibo Yang

University of Cincinnati

Papers

2

Total Citations

70

H-Index

2

About

Qibo Yang is a leading researcher in intelligent manufacturing and industrial robotics, with a primary focus on fault diagnosis and prognosis for critical robotic components. His work addresses the challenge of maintaining reliability in complex automated systems, particularly in high-stakes environments like liquid crystal display (LCD) production lines. Yang’s major contributions include pioneering the use of non-stationary motor current signals for fault diagnosis of ball screws in industrial robots, a method that enables early detection of degradation without additional sensors. His 2020 paper on this topic has garnered 36 citations, underscoring its influence. Additionally, his research on fault prognosis in dynamic working regimes—captured in a 2020 work with 34 citations—provides frameworks for identifying degradation amid operational variations, a critical advancement for real-world applications. Yang’s work is notable for bridging theoretical signal processing with practical industrial needs, offering cost-effective solutions that enhance robot uptime and safety. His achievements position him as a key contributor to the reliability and intelligence of modern manufacturing systems, making his research essential for engineers and scholars advancing Industry 4.0.

Research Focus

Key Achievements

2
H-Index
2
Papers
70
Total Citations
35
Avg Citations/Paper
🏆 Most Cited Paper
Fault Diagnosis of Ball Screw in Industrial Robots Using Non-Stationary Motor Current Signals
36 citations · 2020
📈 Most Prolific Year: 2020 (2 Papers)
🤝 Key Collaborators: 9
🏛 Institutions: University of Cincinnati

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago