Neural networks, multiple outputs
Title:A neuro-computing approach to the thermal profile control of the second-side reflow process in surface mount assembly
Author(s):Tsung-Nan Tsai, (Department of Industrial Management, Shu-Te University, Kaohsiung, Taiwan), Taho Yang, (Institute of Manufacturing Engineering, National Cheng Kung University, Tainan, Taiwan)
Citation:Tsung-Nan Tsai, Taho Yang, (2005) "A neuro-computing approach to the thermal profile control of the second-side reflow process in surface mount assembly", Journal of Manufacturing Technology Management, Vol. 16 Iss: 3, pp.343 - 359
Keywords:Neural nets, Printed circuits, Solder, Technology led strategy
Article type:Research paper
DOI:10.1108/17410380510583644 (Permanent URL)
Publisher:Emerald Group Publishing Limited
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.