» 1.5 西格玛转变

1.5 西格玛转变

1990
  • Mikel Harry
质量控制工程师,分析制造业的流程能力指标。.

(生成的图像仅供参考)

The 1.5 sigma shift is an empirical correction used in 六西格玛 calculations to account for the long-term dynamic variation of a process. It posits that over time, a process mean will tend to drift by about 1.5 standard deviations from its short-term centered position. This shift is the reason a 6 sigma process corresponds to 3.4 DPMO, not the theoretical 2 defects per billion.

免责声明:1.5 西格玛转变是六西格玛中最具争议的方面之一。 它起源于 观察 that short-term data, collected over a brief period, typically shows less variation than long-term data from the same process. This is because over longer periods, factors like tool wear, material variations, operator differences, and environmental changes cause the process mean to drift. The 1.5 sigma value was determined empirically by Motorola engineers as a reasonable general estimate for this drift. By incorporating this shift, Six Sigma provides a more realistic, long-term view of 工艺性能. The calculation for DPMO is thus based on the probability of an outcome falling outside a specification limit that is [latex]4.5\sigma[/latex] from the drifted mean ([latex]6\sigma – 1.5\sigma[/latex]). Critics argue that the 1.5 value is arbitrary and that a well-controlled process should not drift this much. Proponents argue it’s a pragmatic adjustment that makes the Six Sigma standard more applicable to real-world industrial processes.

UNESCO Nomenclature: 3308
– Industrial engineering and technology

类型

抽象系统

中断

递增

使用方法

广泛使用

前体

  • Walter A. Shewhart’s work on common and special cause variation
  • long-term vs. short-term 过程能力 studies
  • 工业过程的经验观察
  • 控制图理论

应用

  • 计算长期过程能力(Cpk、Ppk)
  • setting realistic quality targets in 制造业
  • 财务建模中的风险评估
  • 长寿命产品的可靠性工程

专利:

NA

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Related to: 1.5 sigma shift, process drift, six sigma, dpmo, 统计过程控制, process capability, long-term variation, motorola, quality control, standard deviation.

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历史背景

1.5 西格玛转变

1990
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1990
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1990
1990
1991
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1993

(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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