Optimization design on process parameters of copper wire bonding for power modules - HU Biao; CHENG Lanxian; LI Zhenling; DAI Xiaoping (机车电传动)
In order to improve the copper wire bonding performance of the power modules, an optimization design scheme of process parameters for copper wire bonding was proposed by using the six-factor five-level orthogonal test method, and combining the back propagation (BP) neural network and genetic algorithm (GA). Firstly, the selected samples were orthogonally tested and the results were analyzed by range analysis to generate the influence weight ranking of the process parameters on the bonding quality. Secondly, a prediction model of copper wire bonding performance was constructed using the BP neural network, and the optimal values of process parameters were generated by solving the BP neural network fitness function with GA. Comparing the optimization results from the BP genetic algorithm with those from the traditional methods, the former was found in the stability of the copper wire bonding process improved more significantly. Finally, the power cycle test was carried out on the power module, showing that the power cycle capability of the module optimized by the BP genetic algorithm was significantly improved.