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使用可变样本大小和工程应用的贝叶斯控制图

Imad Khan¹, Atif M Alamri², Abdullah M Almarashi³

¹Abdul Wali Khan University Mardan, Mardan, Pakistan.

Scientific reports

|October 21, 2024

概括

本研究引入了使用贝叶斯方法的可变样本大小 (VSS) 的自适应指数加权移动平均 (AEWMA) 控制图. 新图表在动态制造环境中提供了更好的检测和更少的错误报警.

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
运营研究运营研究

背景情况:

传统的统计过程控制 (SPC) 方法经常与动态的制造环境作斗争.
现有的贝叶斯式EWMA和AEWMA图表具有固定的样本大小,在响应和检测方面存在局限性.

研究的目的:

提出一个创新的自适应指数加权移动平均线 (AEWMA) 控制图,该控制图在贝叶斯方法论下结合了可变样本大小 (VSS).
在动态制造环境中提高统计过程控制的响应性和有效性.

主要方法:

使用可变样本大小 (VSS) 开发一个自适应指数加权移动平均 (AEWMA) 控制图.
整数线性函数的集成用于基于AEWMA统计数据的动态样本大小调整.
从EWMA图表中纳入平滑常数,以提高监控响应能力.
进行了广泛的模拟,将拟议图与现有的贝叶斯式EWMA和AEWMA图与固定的样本大小 (FSS) 进行比较.

主要成果:

拟议的贝叶斯VAEWMA控制图表显示,与现有方法相比,其性能优越.
新的图表显示了用于检测改进的增强灵敏度.
随着拟议的图表,观察到虚假报警率的显著下降.
贝叶斯VAEWMA图表在模拟中被证明是整体上更有效的.

结论:

这些发现支持在动态制造过程中需要动态统计过程控制工具.
适应性SPC方法对于优化现代制造环境中的控制至关重要.
一个真实数据应用验证了拟议的贝叶斯VAEWMA控制图的有效性和最佳性能.

关键词:

这就是ARL.ARL.贝叶斯的方法是贝叶斯的方法.控制图表中的控制图表.记录记录正常记录正常马克斯-EWMAMA 的时间.SDRL SDRL SDRL SDRL SDRL SDRL SDRL SDRL SDRL SDRL SDRL SDRL SDRL SDRL SDRL SDRL SDRL

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