Work

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

Year: 2026

Type: article

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.

Source: Moore and More

DOI: 10.1007/s44275-026-00047-6

Authors: Yanwei Dai, Fei Qin, Xinyue Jia, Yuqi Hao

Institution: Beijing University of Technology

Language: English

Topic: Electronic Packaging and Soldering Technologies

Subfield: Electrical and Electronic Engineering

Field: Engineering

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: diamond

Funders: National Natural Science Foundation of China, Natural Science Foundation of Beijing Municipality