第二阶段监测多通道配置文件中的工艺变异性
Zahra Jalilibal1, Amirhossein Amiri1, Orod Ahmadi2
1Department of Industrial Engineering, Faculty of Engineering, Shahed University, Tehran, Iran.
PloS one
|December 12, 2025
概括
本研究引入了一种新的统计过程监控 (SPM) 方法,用于多道数据. 该方法增强了共变矩阵转移的检测,改善了过程可变性监测.
科学领域:
- 工业工程 工业工程 工业工程
- 统计过程控制 统计过程控制
- 多变量数据分析 多变量数据分析
背景情况:
- 使用个人资料数据监测流程的变化是具有挑战性的,特别是对于多道个人资料.
- 检测多变量正常过程的共变量矩阵的变化对于有效的过程监控至关重要.
- 高维度过程由于众多变量和有限的样本大小而存在复杂性.
研究的目的:
- 引入一种新的方法来监测多通道数据的共变矩阵在第二阶段.
- 为了解决传统方法的局限性,这些方法仅假定共变矩阵元素中同时存在少数偏差.
- 为了提高复杂的,高维的系统中过程转移的检测能力.
主要方法:
- 该研究整合了一个指数加权移动平均 (EWMA) 控制图.
- 多通道功能主要组件分析 (MFPCA) 用于导出监控统计数据.
- 拟议的方法是为二期监测多道过程数据而设计的.
主要成果:
- 模拟结果证明了拟议方法的有效性.
- 该方法在各种轮班模式中,在平均运行长度 (ARL) 方面表现出卓越的性能.
- 该方法成功地监测了多通道数据的协差矩阵的变化.
结论:
- 开发的EWMA-MFPCA方法提供了一种有效的解决方案,用于监测多通道过程中的协差矩阵变化.
- 与现有技术相比,这种方法提供了更好的灵敏度和性能,特别是在高维场景中.
- 这些发现有助于推进复杂工业应用的统计过程监测.
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