Yunfeng Zhang
Yunfeng Zhang, Ph.D.
Professor,
Department of Mechanical Engineering,
National University of Singapore.
Email: mpezyf@nus.edu.sg

Biography:

Dr. Yunfeng Zhang received his B.Eng. in Mechanical Engineering from Shanghai Jiao Tong University, China in 1985 and Ph.D. from the University of Bath, UK in 1991. He is currently an Associate Professor at the Department of Mechanical Engineering, National University of Singapore. His research interests include (1) operations research, in particular, computational intelligence in design and manufacturing (process planning, scheduling, and their integration, VRP, and multi‐objective optimization for UAV mission planning); (2) hybrid manufacturing (3D printing and 5-axis machining) technology for parts repair. He has authored more than 200 publications and received various international awards including the Kayamori Best Paper Award in ICRA 1999 and the IMechE Thatcher Bros Prize in 2011.


Abstract:

Laser Deposition Path Planning for Hybrid Manufacturing
 
For worn components of high value, regional repairing is normally applied to make those components to meet requirements again thus extending their service time. Existing repairing methods rely on welding and manual finishing, which is labor intensive and dependent upon the skill of the operators. Recently, hybrid manufacturing, i.e., laser metal deposition (LMD) and multi-axis milling in the same machine frame, has emerged to provide an alternative way to repair defective components. It is capable of performing material deposition followed by multi-axis milling to achieve the required surface finish. The whole repair process is conducted in the same set-up, thus improving efficiency and reducing cost.
 
However, parameter selection for LMD still remains a major challenge. An operator has to try the selected parameters on the machine before knowing the resulted material property. To fully achieve its potential in industrial application, in this talk, a comprehensive framework for the selection of LMD parameters is presented. In particular, a finite element analysis (FEA) based simulation model for LMD is developed to evaluate the selected parameter sets by providing thermal stress field map and temperature field map during deposition. The output graphs can help compare different parameter settings and select an appropriate one.
 



 
COUNTDOWN
  • DAYS
  • HOURS
  • MINUTES
  • SECONDS
Key Dates

  Abstract continue accepting
  
Deadline for early registration
  September 15, 2017