PurposeThe purpose of this paper is to evaluate the application of an acoustic micro‐imaging (AMI) inspection technique in monitoring solder joints through lifetime performance and demonstrate the robustness of the monitoring through analysis of AMI data.Design/methodology/approachAccelerated thermal cycling (ATC) test data on a flip chip test board were collected through AMI imaging. Subsequently, informative features and parameters of solder joints in acoustic images were measured and analysed. Through analysing histogram distance, mean intensity and grey area of the solder joints in acoustic images, cracks between the solder bump and chip interface were tracked and monitored. The results are in accord with associated Finite Element (FE) prediction.FindingsAt defective bumps, the formation of a crack causes a larger acoustic impedance mismatch which provides a stronger ultrasound reflection. The intensity of solder joints in the acoustic image increase according to the level of damage during the ATC tests. By analysing the variation of intensity and area, solder joint fatigue failure was monitored. A failure distribution plot shows a normal distribution pattern, where corner joints have the lowest reliability and are more likely to fail first. A strong agreement between AMI monitoring test data and FE prediction was observed, demonstrating the feasibility of through lifetime monitoring of solder joints using AMI.Originality/valueThe paper indicates the feasibility of the novel application of AMI inspection to monitor solder joint through lifetime performance non‐destructively. Solder joints' real life conditions can be tracked by an AMI technique, hence solder joint fatigue failure cycles during the ATC tests can be monitored and analysed non‐destructively.

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A robust feature extraction and blob analysis system was developed for high quality solder joint assessment during accelerated thermal cycling (ATe). Thermal cycling test performed on flip chip type devices were inspected by Acoustic Micro Imaging (AMI). An automated image analysis system has been developed to provide enhanced images and facilitate the solder joint inspection process. The proposed system consists of three stages: solder joint detection, feature extraction and defect evaluation. The existence and location of solder joints in an ultrasound C-scan image are through detection by a gradient-based circular Hough Transform. Subsequently, useful features and parameters are extracted based on a region growing algorithm. The method is verified by inspecting test samples before, during and after accelerated thermal cycling. Informative features and analysis results are presented. The results clearly distinguish between normal and abnormal joints and show the cracks between the chip-to-bump interfaces after accelerated thermal cycling tests.

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