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» 休哈特控制图

休哈特控制图

1924
  • Walter A. Shewhart
用于质量控制过程监控的 Shewhart 控制图。.

(图片仅供参考)

一种用于图形工具 统计过程控制 用于监测过程变量随时间的变化。它将数据点绘制在中心线 (CL)(代表过程平均值)与上限 (UCL) 和下限 (LCL) 之间。这些限值通常设定为均值三个标准差 (μ ± 3σ),定义了预期共同原因变异的范围。

The control chart is the primary instrument of Statistical Process Control. Invented by Walter A. Shewhart, it serves as a visual method to distinguish between common and special cause variation in a process. A typical chart has a time-based x-axis and a measurement-based y-axis. Three horizontal lines are crucial: the Center Line (CL), which is the statistical average of the process data; the Upper Control Limit (UCL); and the Lower Control Limit (LCL). These control limits are not arbitrary goals or specification limits set by customers. Instead, they are calculated directly from the process data itself, representing the “voice of the process.”

The standard calculation for these limits is based on the process mean ([latex]\mu[/latex]) and standard deviation ([latex]\sigma[/latex]), with the UCL at [latex]\mu + 3\sigma[/latex] and the LCL at [latex]\mu – 3\sigma[/latex]. The use of three standard deviations is a statistical and economic choice; it balances the risk of failing to detect a process shift (a Type II error) with the risk of a false alarm (a Type I error). When data points fall within these limits and exhibit a random pattern, the process is considered “in statistical control.” However, if a point falls outside the limits, or if the points within the limits show a non-random pattern (as defined by rules like the Western Electric Rules), it signals the presence of a special cause of variation that requires investigation.

UNESCO Nomenclature: 1209
- 统计资料

类型

软件/算法

中断

重大的

用法

广泛使用

前体

  • 运行图(时间序列图)
  • 标准差的概念(卡尔·皮尔逊)
  • 统计抽样理论
  • 区分普通原因变异和特殊原因变异(沃尔特·A·休哈特)

应用程序

  • 制造过程监控(例如,零件尺寸、重量)
  • 服务行业绩效跟踪(例如,呼叫等待时间、错误率)
  • 医疗保健患者监测(例如,血压、感染率)
  • 软件性能监控(例如,服务器响应时间、错误报告)
  • 财务审计(例如,费用报告差异)

专利:

NA

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相关术语:控制图、休哈特图、上限控制限、下限控制限、中心线、三西格玛限值、过程监控、SPC、质量控制、统计分析。

历史背景

休哈特控制图

1900
1903
1914
1924
1925
1930
1931
1899
1900
1911
1922
1925
1928
1930
1936

(如果日期未知或不相关,例如“流体力学”,则提供其显著出现的近似估计)

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