# Research on Lifespan Prediction Methods Using Ultrasonic Microimaging for Electronic Packaging
## 1 Introduction  
Electronic packaging components are subject to complex thermal load environments throughout their service [1]. These components are mounted onto board-level systems, where they cannot freely expand or contract. This restriction, coupled with the mismatch in the coefficients of thermal expansion among different materials, results in significant stress accumulation at critical points, such as solder joints, consequently making these joints the weakest links in electronic packaging [2, 3]. Therefore, predicting the lifespan of electronic packaging, particularly that of solder joints, has become a primary research direction to enhance the reliability of electronic systems [4, 5]. Acoustic microimaging (AMI), a non-destructive testing technique with a strong capability to detect internal material defects, has seen increasing application in the non-destructive testing and evaluation of internal defects of electronic packaging [6, 7]. [PERSON] et al. demonstrated the superior capability of AMI in detecting solder joint defects, offering newperspectives for predicting the lifespan of electronic packaging [8; 9]. However, variations in temperature and stress fields under steady-state conditions differ significantly across different electronic packages. Predicting the distribution of internal heat sources within electronic packaging is challenging: the shape of thermal energy pulses varies, affecting the distribution of thermal stress fields, the location of hot spots, the degree and location of stress concentration, and the shape and position of defects [10]. To date, a comprehensive theoretical framework that describes and predicts the failure mechanisms of electronic packaging has not yet been established. Therefore, existing methods primarily rely on failure modeling for electronic packaging lifespan prediction. [PERSON] et al. developed an ultrasonic fatigue testing method and FEM simulation using the Anand model to predict solder joint lifetimes, addressing strain rate effects in PbSnAg, Sn3.5 Ag, and SnSbAg alloys across temperatures and bridging accelerated tests with service conditions [11]. [PERSON] et al. proposed an improved Norris-Landzberg model combined with an optimal design approach for accelerated life testing (ALT) based on temperature cycling. Finite element analysis (FEA) was employed to study the impact of temperature cycling parameters on the thermal fatigue life of 63 Sn-37 Pb solder joints, establishing an optimal model aimed at minimizing the estimated median lifespan under normal usage conditions [12]. [PERSON] et al. introduced a modeling approach for SAC305 solder joints based on the Anand viscoplastic model. The model's accuracy was validated across a broad range of temperatures and stress levels through shear creep tests conducted on solder joint samples [13]. [PERSON] et al. explored the impact of creep failure mechanisms on the thermomechanical reliability of electronic packaging and proposed a failure modeling method to describe the creep fatigue failure mechanisms of electronic packaging [14]. Current research reveals that models for predicting solder joint failure lifespan are often semi-theoretical and semi-empirical, relying on methods such as finite element analysis and requiring destructive techniques to acquire failure data [15; 16]. Such methods result in the destruction of test samples, preventing continuous monitoring of the same sample's condition throughout its life cycle [11; 17]. In response to these challenges, this study proposes a novel method for predicting the lifespan of electronic packaging using acoustic microimaging (AMI). The primary purpose of this research is to construct a robust, data-driven model for solder joint failure prediction under thermal cycling conditions. This method accelerates the aging and failure of experimental samples through thermal cycling experiments while collecting full life-cycle data of the samples using AMI during the experimental process.