Artificial intelligence-assisted reliability assessment in electronics packaging: a brief review

Abstract The recent progress in utilizing machine learning methods for electronics packaging has drawn some special attention. In this paper, we review the more recent progress in artificial intelligence methods for electronics packaging. Machine learning methods adopted for mechanical parameter extraction and constitutive law parameter determination, such as solder fatigue prediction and warpage prediction, are reviewed. The utilization of machine learning methods has opened new avenues to address crucial problems in electronics packaging, such as enhancing prediction efficiency and improving optimization design variety. We also present some emerging future trends.