基于数字双胞胎的生产过程异常的可解释机制
Weiwei Qian1,2, Litong Zhang3,4, Yu Guo3
1Ningbo University of Technology, Ningbo, China. qianww@nuaa.edu.cn.
Nature communications
|January 10, 2026
概括
制造异常会扰乱时间表,造成损失. 本研究介绍了一种可解释的生产过程异常 (EM2PA) 机制,以确定原因并实现根源原因分析,提高生产可靠性.
科学领域:
- 制造业 工程 制造工程
- 工业工程 工业工程 工业工程
- 数据科学数据科学数据科学
背景情况:
- 制造业中的异常生产导致了严重的经济和声誉损害.
- 现有的方法在识别生产异常的根本原因时往往缺乏清晰度.
研究的目的:
- 为生产过程异常 (EM2PA) 提供一个可解释的机制.
- 为了澄清复杂的关系,确定影响因素,并为异常生产提供因果解释.
- 为了能够追溯分析制造异常.
主要方法:
- EM2PA包括三个模块:用于小样本异常数据的数据增强,用于解关系的影响因子识别,以及用于解释的因果解释.
- 利用一个离散制造车间的案例研究.
主要成果:
- 在EM2PA有效地确定了生产异常的根本原因.
- 证明了分析各种因素对生产过程的影响的能力.
- 验证了可解释性和因果分析在异常检测中的重要性.
结论:
- 开发的EM2PA提供了一个强大的解决方案,用于识别和解释制造业中的生产异常.
- 可解释的人工智能和因果分析对于提高制造过程控制和可靠性至关重要.
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