Rongjie Li

Title: Rongjie Li: Innovator in Defect Prediction Methods

Introduction

Rongjie Li is a prominent inventor based in Guangzhou, China. He has made significant contributions to the field of additive manufacturing through his innovative approaches to defect prediction. His work focuses on enhancing the quality and reliability of manufacturing processes.

Latest Patents

Rongjie Li holds a patent for a defect prediction method based on a multi-feature parallel multi-stage neural network (MF-PMSNN). This method involves obtaining a trajectory dataset and preprocessing data related to defects in workpieces during additive manufacturing. The MF-PMSNN is designed to evaluate output classification results based on specific evaluation indicators. It enables real-time defect prediction and allows for the deployment of a trained MF-PMSNN model in a production environment. The innovation effectively combines thermal imaging-based in-situ monitoring data with X-ray computed tomography (XCT)-based in-situ monitoring data, ensuring temporal and spatial consistency. This comprehensive approach captures the molten pool status and porosity distribution in the data, facilitating accurate defect prediction.

Career Highlights

Rongjie Li is affiliated with the Guangdong University of Technology, where he contributes to research and development in the field of manufacturing technologies. His expertise in neural networks and defect prediction has positioned him as a key figure in advancing additive manufacturing techniques.

Collaborations

Rongjie Li has collaborated with notable colleagues, including Jiewu Leng and Junxing Xie. Their combined efforts in research have furthered the understanding and application of advanced manufacturing processes.

Conclusion

Rongjie Li's innovative work in defect prediction methods showcases his commitment to improving additive manufacturing. His contributions are vital for enhancing production quality and efficiency in the industry.