Open Access
E3S Web Conf.
Volume 236, 2021
3rd International Conference on Energy Resources and Sustainable Development (ICERSD 2020)
Article Number 04041
Number of page(s) 7
Section Green Technology Innovation and Intelligent Application of Environmental Equipment
Published online 09 February 2021
  1. Pan Kailin, Zhou Dejian, Qin Kuangyu. Research status of SMT reflow welding Process Prediction and Simulation Technology [J]. Electronic Process Technology, 2000(5): 185–187. [Google Scholar]
  2. Mao Xinlong, Han Guoming, Huang Bingyuan, et al. Modeling and Simulation of reflow welding process in SMT [J]. Welding technology, 2004,33 (5): 17–20. [Google Scholar]
  3. Feng Zhigang, Yu Tingwen, Zhu Yunhe. Influence of reflow welding parameters on temperature curve [J]. Electronic Technology, 2004, (6): 243–246. [Google Scholar]
  4. Li Yan, Zhao Libo, Zhang Wei, Qiu Zhaoyi. Analysis and Optimization of reflow welding furnace temperature Setting [J]. Ship electric technology, 2010, 30(07): 44–46. [Google Scholar]
  5. Zhu Guibing, Chen Wensuo, Zhao Xiongming. Research on the optimization of reflow welding temperature curve to prevent defects [J]. Hot working process, 2011,40 (19): 133–135, 138. [Google Scholar]
  6. Gong yubing. Research on optimization of temperature curve of reflow welding furnace [J]. Thermal processing technology,2013,15(42): 187–190,193. [Google Scholar]
  7. Wan Xuebin. Fitting study of reflow welding temperature curve [J]. Henan Science and Technology, 2008,11(12):53–54. [Google Scholar]
  8. Fei Zemin. Setting of temperature distribution curve of reflow furnace [J]. Electronic Technology,1997, (04): 22–25. [Google Scholar]
  9. Lei Xiangxiao, Tang Chunxia, Xu Lijuan. Temperature control of hot air reflow welding based on RBF-PID [J]. Journal of Shaoyang university (natural science edition),2020,17(04):31–38. [Google Scholar]
  10. Sun Liqiang. PCB Reflow welding Temperature curve Setting optimization [J]. Electronic Technology and Software Engineering, 2014, (07): 150–151. [Google Scholar]
  11. Guo Yu, Sun Zhili, Yuan Zhe, Pan Ershun. Parameter setting of reflow welding based on Neural Network Genetic Algorithm [J]. Mechanical science and technology,2013,32(08):1211–1214,1220. [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.