记忆类型 贝叶斯适应性最大-EWMA控制图对韦布尔过程的控制图
Abdullah A Zaagan1, Imad Khan2, Amel Ayari-Akkari3
1Department of Mathematics, Faculty of Science, Jazan University, P.O. Box 2097, 45142, Jazan, Saudi Arabia.
Scientific reports
|April 18, 2024
概括
本研究引入了一种新的贝叶斯适应性最大指数加权移动平均线 (Max-EWMA) 控制图,用于监测非正常过程. 拟议的图表有效地检测了工艺转移,超过了半导体制造中现有的方法.
科学领域:
- 统计过程控制 统计过程控制
- 质量工程 质量工程
- 工业统计 工业统计 工业统计
背景情况:
- 同时监测工艺平均值和分散是至关重要的,特别是对于正常分布.
- 现有的方法往往假定正常性,限制其应用到非正常的过程.
- 有效监测非正常过程需要专门的控制图表技术.
研究的目的:
- 介绍一个新的贝叶斯适应性最大指数加权移动平均线 (Max-EWMA) 控制图.
- 共同监测非正常过程的平均值和分散,特别是那些遵循韦布尔分布的过程.
- 评估拟议图表的性能与现有的Max-EWMA图表相比.
主要方法:
- 利用了对韦布尔分布式过程的逆响应函数.
- 员工平均运行长度 (ARL) 和运行长度标准偏差 (SDRL) 用于绩效评估.
- 将拟议的贝叶斯式Max-EWMA图与传统的Max-EWMA图进行比较.
主要成果:
- 拟议的贝叶斯马克斯-EWMA控制图表在检测失控信号方面表现出卓越的灵敏度.
- 该图表显示了各种损失函数 (LF) 下的韦布尔过程的有效性能.
- 一个关于半导体硬过程的案例研究验证了图表的实际适用性和快速检测能力.
结论:
- 新的贝叶斯适应性Max-EWMA控制图对于监测非正常过程非常有效.
- 与现有方法相比,拟议的图表在检测过程偏差方面提供了显著的改进.
- 这有助于加强半导体制造等行业的工艺监测和质量控制.
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