A neuro-computing approach to the thermal profile control of the second-side reflow process in surface mount assembly

Tsung Nan Tsai, Ta-Ho Yang

研究成果: Article同行評審

10 引文 斯高帕斯(Scopus)

摘要

Purpose - A neural-network-based predictive model is proposed to model the second-side thermal profile reflow process in surface mount assembly with a view to facilitating the oven set-up procedure and improving production yield. Design/methodology/approach - This study performs a 38-4 fractional factorial experimental twice to collect the thermal-profile data from a second-side board. The first experiment has components on the second side only, while the second experiment also has additional components on the primary side. A back-propagation neural network (BPN) is then used to model the relationship between control variables and thermal-profile measures. Findings - Empirical results illustrate the efficiency and effectiveness of the proposed BPN in solving the second-side thermal-profile prediction and control problem. Originality/value - There is no study dedicated to the investigation of the second-side thermal-profile variance with and without the presence of primary-side components. The study suggests that a variant oven-setting strategy for the second-side reflow process is important to ensure reflow-soldering quality.

原文English
頁(從 - 到)343-359
頁數17
期刊Journal of Manufacturing Technology Management
16
發行號3
DOIs
出版狀態Published - 2005 5月 30

All Science Journal Classification (ASJC) codes

  • 軟體
  • 控制與系統工程
  • 電腦科學應用
  • 策略與管理
  • 工業與製造工程

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