基于集群的控制图表的两个变量的综合变化点检测和在线监测方法
Adel Ahmadi Nadi1, Ali Yeganeh1,2, Sandile Charles Shongwe2
1Department of Industrial Engineering, Faculty of Engineering, Ferdowsi University of Mashhad, Mashhad, Iran.
Journal of applied statistics
|September 4, 2025
概括
这项研究引入了一种基于集群的新型控制图表,用于监测两个随机特征的比率 (RZ图表). 这种新方法消除了分布和方向假设,提高了统计过程的监控.
科学领域:
- 统计过程监测 (SPM)
- 质量控制
- 机器学习应用
背景情况:
- 传统的RZ图假设正常分布和已知的偏差方向,限制了它们的适用性.
- 当现有方法在现实场景中违反过程假设时,可能会失败.
- 在SPM中集成机器学习提供了先进的解决方案,但缺乏RZ图表应用.
研究的目的:
- 在第二阶段开发一个新的,无假设的控制图.
- 解决关于数据分布和偏差方向的传统RZ图的局限性.
- 引入基于机器学习的方法来加强RZ过程的监控.
主要方法:
- 一个基于集群的控制图表被开发用于RZ监测.
- 建议的方法不假设单个特征的正常分布.
- 它在不需要预先了解RZ偏差方向的情况下运行.
主要成果:
- 在没有限制性统计假设的情况下,新图表有效地监测RZ.
- 该方法证明了该过程的变化点 (CP) 的估计能力.
- 它为传统的RZ控制图提供了灵活的替代方案.
结论:
- 提出的基于集群的RZ图表通过删除关键假设来推进统计过程监测.
- 这种方法提高了RZ监控在各种工业环境中的适应性和适用性.
- 估计变化点的能力为过程分析和控制增加了显著的价值.
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