Scholarlink

<p>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.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

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

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年5月29日

查看全文
  • Yanwei Dai,
  • Fei Qin,
  • Xinyue Jia,
  • Yuqi Hao

摘要

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.