基于可变样本的大小的EWMA控制图,用于生产过程监控的指数级缩放机制
Ibrahim A Nafisah1, Mohammed M A Almazah2, A Y Al-Rezami3
1Department of Statistics and Operations Research, College of Sciences, King Saud University, P. O. Box 2454, 11451, Riyadh, Saudi Arabia.
Scientific reports
|August 22, 2025
概括
本研究引入了适应性样本大小EWMA控制图,以加强统计过程控制. 新图表有效地检测过程变化,在检测小到中等变化方面超过现有方法.
科学领域:
- 工业工程
- 统计质量控制
- 运营研究
背景情况:
- 统计过程控制 (SPC) 对于保持稳定的生产过程至关重要.
- 检测工艺变化是防止缺陷和确保质量的关键.
- 现有的EWMA图表在适应变化的工艺变化方面存在局限性.
研究的目的:
- 开发和评估一个具有适应性样本大小的新型EWMA控制图.
- 提高SPC中转移检测的灵敏度和效率.
- 为现实世界的过程监控提供一个强大的工具.
主要方法:
- 开发一个指数加权移动平均线 (EWMA) 控制图,采用适应性样本大小.
- 使用广泛的蒙特卡洛模拟进行性能评估.
- 与固定样本大小EWMA (FEWMA) 和可变样本大小EWMA图表进行比较.
- 对现实世界的工业数据集进行分析.
主要成果:
- 与FEWMA和可变样本大小EWMA图表相比,建议的自适应样本大小EWMA图表在转移检测方面表现出更高的性能.
- 该图表特别有效地识别了小到中等的工艺转移.
- 平均运行长度 (ARL) 和运行长度标准偏差 (SDRL) 等指标证实了增强的检测能力.
- 该方法平衡了检测灵敏度和计算效率.
结论:
- 适应性样本大小EWMA图表在统计过程控制中提供了显著的进步.
- 这种方法为监测过程变化提供了更快速和更稳定的方法.
- 它的实用性通过现实数据分析得到验证,突出了其在工业环境中的价值.
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