Genetic algorithms for defect detection of flip chips

Flip chip packaging technology is widely used in high density assembly and superior performance devices. The solder joints are sandwiched between dies and substrates, leading to the defects optically opaque. Defect inspection of flip chips become more difficult. In this paper, a nondestructive detection method was presented. Ultrasonic excitations were forced on the surface of the flip chips and the raw vibration signals were measured by a laser scanning vibrometer. Eleven time domain features and twenty-four frequency domain features were extracted for analysis. After that, the genetic algorithm was introduced for feature selection and the back propagation network was adopted for classification and recognition. The flip chips were divided into three categories: good flip chips, flip chips with missing solder joints, and flip chips with open solder joints. They are recognized under the features selected by genetic algorithms rapidly and accurately, compared with those under other feature datasets, demonstrating that the approach using genetic algorithms is effective for defect inspection in flip chip packaging.