Optimization of reflow soldering temperature curve based on genetic algorithm

Abstract

The current SMT reflow soldering process usually adopts experimental methods to predict the temperature curve, and the disadvantages of high cost and low efficiency are urgent problems. In view of the high heat capacity and poor wetting of the product during the reflow soldering process, this paper optimizes the temperature curve prediction model. First, the existing furnace temperature model is simplified, and then a method based on genetic algorithm is proposed by introducing heating factors. Based on the above, we established a reflow temperature curve optimization model. Finally, the MAPE evaluation method is used to compare the predicted results with the production data, and the results show that the predicted values meet the error accuracy requirements. Therefore, it is proved that the mathematical model of genetic algorithm established can effectively predict the temperature curve, and provide guidance for the production process of the reflow soldering of the enterprise.

Keywords

• Reflow soldering
• Temperature curve optimization
• Genetic algorithm
• Heating factor