1.1 本实践为确定几种常见使用场景下的过程能力和性能提供了指导，包括:( 一 )基于正态分布的能力和性能指标，如 C p , C 主键 , P p 和 P 主键 ; ( b )使用不合格单元和每个单元类型变量的不合格属性数据的过程能力，以及( c )处理过程能力或性能的其他方法。 1.2 本国际标准是根据世界贸易组织技术性贸易壁垒（TBT）委员会发布的《关于制定国际标准、指南和建议的原则的决定》中确立的国际公认标准化原则制定的。 ====意义和用途====== 4.1 过程能力- 过程能力可以定义为处于统计控制状态的稳定过程的自然或固有行为 ( 1. ) . 4. 当过程没有表现出可检测的模式或趋势时，即达到“统计控制状态”，因此数据中的变化被认为是随机的，并且是过程固有的。过程能力与控制图的使用和统计控制状态有关。 在评估过程能力之前，必须研究过程以评估其控制状态。 4.2 过程控制- 有许多方法可以实现控制图，但最常见的选择是实现所研究过程的统计控制状态。特殊原因由基于概率论的一组规则确定。每当图表显示出现特殊原因时，就会对该过程进行调查。采取适当措施消除已识别的特殊原因并防止其再次出现，最终将达到统计控制状态。 在这种状态下，可能会达到最小变化水平，这被称为共同原因或固有变化。就本标准而言，这种变化是对过程输出均匀性的测量，通常是产品特性。 4.3 过程能力指数- 统计控制状态下过程的行为（与固有可变性相关）用于描述其能力。为了将过程与客户要求（或规范）进行比较，通常根据产品规范或公差内的过程输出比例来考虑能力。 该比例的指标是规范使用的过程分布百分比。这种比较成为所有过程能力度量的本质。计算这些指标的方式定义了不同类型的能力指数及其使用。中定义了两个过程能力指数 5.2和 5.3 . 在实践中，这些指标用于通过持续改进来推动流程改进。这些指数可用于确定减少共同原因变化、比较不同来源的产品和比较过程所需的管理行动的需求。 4.4 过程性能指标- 当一个过程不处于统计控制状态时，该过程会受到特殊原因变化的影响，这可以在过程可变性上以各种方式表现出来。特殊原因可能导致过程的短期可变性发生变化，或者可能导致过程均值的长期偏移或漂移。特殊原因也可能在过程平均值中产生瞬态偏移或峰值。即使在这种情况下，也可能需要评估长期- 使用过程性能指数，根据客户规范对过程的术语可变性进行定义 6.2和 6.3 . 这些指数与能力指数类似，仅在计算中使用的可变性估计方面有所不同。这种估计的变异性包括由于特殊原因引起的额外变异成分。由于过程性能指数具有额外的变化成分，因此过程性能的传播范围通常比过程能力传播范围更广。 与产品均匀性相比，这些测量有助于确定测量和采样可变性的作用。 4.5 属性能力应用发生在属性数据用于评估过程的情况下，可能涉及使用不合格单元或每个单元的不合格项。 4.6 处理评估的其他措施和方法包括指数 C 下午 ，其中包含可变数据的目标参数，以及滚动吞吐量产量（RTY）的计算，该计算用于衡量一系列过程步骤的优劣。

1.1 This practice provides guidance for determining process capability and performance under several common scenarios of use including: ( a ) normal distribution based capability and performance indices such as C p , C pk , P p , and P pk ; ( b ) process capability using attribute data for non-conforming units and non-conformities per unit type variables, and ( c ) additional methods in working with process capability or performance. 1.2 This international standard was developed in accordance with internationally recognized principles on standardization established in the Decision on Principles for the Development of International Standards, Guides and Recommendations issued by the World Trade Organization Technical Barriers to Trade (TBT) Committee. ====== Significance And Use ====== 4.1 Process Capability— Process capability can be defined as the natural or inherent behavior of a stable process that is in a state of statistical control ( 1 ) . 4 A “state of statistical control” is achieved when the process exhibits no detectable patterns or trends, such that the variation seen in the data is believed to be random and inherent to the process. Process capability is linked to the use of control charts and the state of statistical control. A process must be studied to evaluate its state of control before evaluating process capability. 4.2 Process Control— There are many ways to implement control charts, but the most popular choice is to achieve a state of statistical control for the process under study. Special causes are identified by a set of rules based on probability theory. The process is investigated whenever the chart signals the occurrence of special causes. Taking appropriate actions to eliminate identified special causes and preventing their reappearance will ultimately obtain a state of statistical control. In this state, a minimum level of variation may be reached, which is referred to as common cause or inherent variation. For the purpose of this standard, this variation is a measure of the uniformity of process output, typically a product characteristic. 4.3 Process Capability Indices— The behavior of a process (as related to inherent variability) in the state of statistical control is used to describe its capability. To compare a process with customer requirements (or specifications), it is common practice to think of capability in terms of the proportion of the process output that is within product specifications or tolerances. The metric of this proportion is the percentage of the process spread used up by the specification. This comparison becomes the essence of all process capability measures. The manner in which these measures are calculated defines the different types of capability indices and their use. Two process capability indices are defined in 5.2 and 5.3 . In practice, these indices are used to drive process improvement through continuous improvement efforts. These indices may be used to identify the need for management actions required to reduce common cause variation, compare products from different sources, and to compare processes. 4.4 Process Performance Indices— When a process is not in a state of statistical control, the process is subject to special cause variation, which can manifest itself in various ways on the process variability. Special causes can give rise to changes in the short-term variability of the process or can cause long-term shifts or drifts of the process mean. Special causes can also create transient shifts or spikes in the process mean. Even in such cases, there may be a need to assess the long-term variability of the process against customer specifications using process performance indices, which are defined in 6.2 and 6.3 . These indices are similar to those for capability indices and differ only in the estimate of variability used in the calculation. This estimated variability includes additional components of variation due to special causes. Since process performance indices have additional components of variation, process performance usually has a wider spread than the process capability spread. These measures are useful in determining the role of measurement and sampling variability when compared to product uniformity. 4.5 Attribute capability applications occur where attribute data are being used to assess a process and may involve the use of non-conforming units or non-conformities per unit. 4.6 Additional measures and methodology to process assessments include the index C pm , which incorporates a target parameter for variable data, and the calculation of Rolled Throughput Yield (RTY), that measures how good a series of process steps are.