Wang Li-Qiang

Papers

1

Total Citations

6

H-Index

1

About

Wang Li-Qiang is a researcher whose work centers on the modeling and optimization of robotic spray painting processes, with a particular focus on coating thickness distribution and automation precision. His most-cited paper, "Multivariable coating thickness distribution model for robotic spray painting" (2017), has garnered 6 citations, establishing a foundational contribution to the field of industrial robotics and surface finishing. This work introduces a multivariable model that accounts for key parameters such as spray gun distance, angle, and motion speed, enabling more accurate and uniform coating application—a critical advancement for manufacturing sectors like automotive and aerospace. By addressing the complexities of thickness variation, Li-Qiang’s model provides a systematic framework for improving quality control and reducing material waste in automated painting systems. Though his citation count is modest, the practical relevance of his research is underscored by its direct applicability in optimizing robotic trajectories and process parameters. Li-Qiang’s contributions represent a valuable step toward smarter, more efficient manufacturing, offering a data-driven approach that bridges theoretical modeling with real-world industrial needs.

Research Focus

Key Achievements

1
H-Index
1
Papers
6
Total Citations
6
Avg Citations/Paper
🏆 Most Cited Paper
Multivariable coating thickness distribution model for robotic spray painting
6 citations · 2017
📈 Most Prolific Year: 2017 (1 Papers)
🤝 Key Collaborators: 4

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 10 days ago