利用无监督机器学习极早发现整车制造公差漂移与隐蔽软件缺陷
基于千万级车辆运行流式特征运行高维 DBSCAN 密度聚类与隔离森林（Isolation Forest）算法，在引发大规模召回前将零散异常收敛为高置信度缺陷特征簇。
高维特征空间自组织聚类与异常溯源
将逆变器温升速率与环境温度做多维交叉聚类，精准圈定特定生产批次中导热硅脂涂覆不均等微观制造缺陷。
- Early identification of silent manufacturing batch defects.
- Automated correlation between driving conditions and failure modes.
- Reduction of unneeded warranty repair costs by 35%.
- Closed-loop feedback to OEM CAD and manufacturing engineering teams.
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