1.5σ偏移是一种经验修正方法，用于…… 六西格玛 计算旨在解释过程的长期动态变化。它假设随着时间的推移，过程均值会偏离其短期中心位置约 1.5 个标准差。正是这种偏移导致 6σ 过程对应的 DPMO 为 3.4，而不是理论上的每十亿个缺陷 2 个。
1.5 西格玛转变
1990
- Mikel Harry
（图片仅供参考）
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 process performance. 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
工业工程与技术
类型
抽象系统
中断
递增
用法
广泛使用
前体
- 沃尔特·A·休哈特关于普通原因和特殊原因变异的研究
- 长期与短期过程能力研究
- 工业过程的经验观察
- 控制图理论
应用程序
- 计算长期过程能力（Cpk、Ppk）
- 在制造业中设定切合实际的质量目标
- 财务建模中的风险评估
- 长寿命产品的可靠性工程
专利：
NA
潜在创新理念
Related to: 1.5 sigma shift, process drift, six sigma, dpmo, statistical process control, process capability, long-term variation, motorola, quality control, standard deviation.
历史背景
1.5 西格玛转变
（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）
