用EWMA函数处理后关于平均值的玛分布数据对称性
Mohammad M Hamasha1, Mohammed S Obeidat2, Khalid Alzoubi2
1Department of Industrial Engineering, Faculty of Engineering, The Hashemite University, P.O.Box 330127, Zarqa, 13133, Jordan. mhamasha@hu.edu.jo.
Scientific reports
|September 12, 2023
概括
使用指数加权移动平均线 (EWMA) 图表的统计过程控制 (SPC) 有效地监测制造质量. 这项研究评估了EWMA参数.
科学领域:
- 工业工程 工业工程 工业工程
- 统计质量控制 统计质量控制
- 制造系统制造系统的制造
背景情况:
- 统计过程控制 (SPC) 对于制造质量和变化减少至关重要.
- 指数加权移动平均线 (EWMA) 控制图对于检测小工艺转移和确保产品一致性是有效的.
- 关于EWMA图表的一个关键问题是数据不对称,这可能会影响控制极限的准确性.
研究的目的:
- 评估EWMA参数对EWMA控制图表性能的影响.
- 评估EWMA处理后在马分布数据中减小斜率和曲.
- 调查EWMA参数如何影响数据分布的形状.
主要方法:
- 蒙特卡洛模拟用于生成马分布式数据.
- 应用了EWMA功能来处理生成的数据.
- 在EWMA处理之前和之后评估了数据的斜度和曲率.
主要成果:
- EWMA 处理可以减少数据偏差和曲率,但可能无法完全解决不对称问题.
- EWMA参数显著影响斜度的程度和缩的减少.
- 该研究确定了最佳的EWMA参数,以改善对照图表的性能,使用不对称的数据.
结论:
- 对于质量监测,EWMA控制图表非常有价值,但对于不对称数据,参数选择至关重要.
- 了解EWMA参数对数据分布形状的影响对于准确的过程控制至关重要.
- 这项研究为选择适当的EWMA参数提供了指导,以提高制造业控制图的可靠性.
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