Simulation and Experimental Investigation on Active Thermography Test of the Solder Balls

Abstract

The miniaturized electronic products require not only high density, but also high reliability. Defect inspection for the high-density package becomes challenging gradually. In this article, active thermography technology is used to detect the solder balls in flip-chip (FC) packages. A single-layer FC model is constructed and heat conduction in the FC package is simulated by using the finite-element analysis code of COMSOL. Experimental investigation is also carried out to inspect the solder defects by using the laser excitation thermography test system. Infrared images of the SFA1 package are captured, and the spatial adaptive filtering algorithm is used to remove the thermal noise. The hot spots of the solder balls are segmented from the filtered infrared image, and the representative features are extracted for each hot spot. The modified learning vector quantization (LVQ) neural network is used for the classification of the solder balls. The missing solder balls are identified accurately. The simulation and experimental results prove that the proposed approach using active thermography and LVQ algorithm is effective for defect inspection in high-density electronic devices.