Forecasting and Parameters Optimization of Reflow Soldering Profile Based on BPNN and GA

Er Shun Pan; Yao Jin; Hu Xu; Wen Zhu Liao

doi:10.4028/www.scientific.net/AMR.139-141.990

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 139-141Forecasting and Parameters Optimization of Reflow...

Forecasting and Parameters Optimization of Reflow Soldering Profile Based on BPNN and GA

Abstract:

This paper proposes an effective method to determine the optimal parameters settings of reflow soldering profile and helps reduce the try-and-error time in practical application. Due to the complex nonlinear relationship between reflow thermal profile and process parameters in this problem, BPNN is adopted to establish the model for description of this intricate relationship between inputs and outputs. According to the requirements of the reflow soldering profile, GA is used to calculate the best input parameters with its strong global research ability. Thus, a combined model with BPNN and GA is proposed for parameters optimization and contributes to reduction of decision time of input parameter for reflow soldering profile. In addition, a case study is given to prove the accuracy of the proposed method.

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Periodical:

Advanced Materials Research (Volumes 139-141)

Pages:

990-995

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.139-141.990

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Online since:

October 2010

Authors:

Er Shun Pan, Yao Jin, Hu Xu, Wen Zhu Liao

Keywords:

BP Neural Network (BPNN), Genetic Algorithm (GA), Printed Circuit Board (PCB), Reflow Soldering, Surface Mount Technology (SMT)

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