ISO/TC 69/SC 4 - Applications of statistical methods in product and process management

This document describes examples for software validation for software implementing the standards of ISO 22514‑7 on the capability of measurement processes. In detail, the following standards are covered: — ISO 22514‑7. It provides data sets and test results for testing the implementation of the evaluation methods described in these standards. This includes: a) the calculation of standard uncertainties from other sources (other than experiments – type B – ISO/IECGuide 98‑3); b) the estimation of uncertainty components using repeated measurements on reference parts; c) the estimation of uncertainty components using repeated measurements on multiple parts with different operators and their evaluation using the ANOVA method; d) the combination of uncertainty components using the Gaussian law of uncertainty propagation; e) the calculation of measurement process capability indices; f) the influence of operators on attributive measurements; g) the uncertainty range and capability indices for attributive measurements. The test examples are intended to cover the calculation of the measuring system capability and measurement process capability according to ISO 22514‑7.

This document describes statistical procedures for setting up cumulative sum (CUSUM) schemes for process and quality control using variables (measured) and attribute data. It describes general‑purpose methods of decision-making using cumulative sum (CUSUM) techniques for monitoring, control and retrospective analysis.

This document defines a procedure to validate measuring systems and a measurement process in order to state whether a given measurement process can satisfy the requirements for a specific measurement task with a recommendation of acceptance criteria. The acceptance criteria are defined as a capability figure (CMS, CMP) or a capability ratio (QMS, QMP). NOTE This document follows the approach taken in ISO/IEC Guide 98-3 (GUM), and establishes a basic, simplified procedure for stating and combining uncertainty components used to estimate a capability index for an actual measurement process. This document is primarily developed to be used for simple one-dimensional measurement processes, where it is known that the method uncertainty and the specification uncertainty are small compared to the implementation uncertainty. It can also be used in similar cases, where measurements are used to estimate process capability or process performance. It is not suitable for complex geometrical measurement processes, such as surface texture and position measurements that rely on several measurement points or simultaneous measurements in several directions.

This document describes the steps for conducting short-term performance studies that are typically performed on machines (including devices, appliances, apparatuses) where parts produced consecutively under repeatability conditions are considered. The number of observations to be analysed vary according to the patterns the data produce, or if the runs (the rate at which items are produced) on the machine are low in quantity. The methods are not considered suitable where the sample size produced is less than 30 observations. Methods for handling the data and carrying out the calculations are described. In addition, machine performance indices and the actions required at the conclusion of a machine performance study are described. This document is not applicable when tool wear patterns are expected to be present during the duration of the study, nor if autocorrelation between observations is present. The situation where a machine has captured the data, sometimes thousands of data points collected in a minute, is not considered suitable for the application of this document.

This document describes the construction and applications of control charts for stationary processes.

This document describes examples for software validation for SPC software implementing the standards of the ISO 7870 series on control charts and the ISO 22514 series on capability and performance. In detail ISO 7870‑2, ISO 22514‑2 and ISO 22514‑8 are covered. It provides data sets and test results for testing the implementation of the evaluation methods described in these standards. This includes the detection of out of control situations as well as the calculation of sample statistics and process capability indices. The test examples cover the following situations: a) General: — different sample and subgroup sizes, accuracy of calculation for large/small numbers; b) ISO 22514 series: — calculation of sample statistics for location and dispersion; — different distribution models; c) ISO 7870‑2: — calculation of control limits; — visualization of data (histogram, control charts); — detection of out of control situations.

This document gives guidance on the uses of acceptance control charts and establishes general procedures for determining sample sizes, action limits and decision criteria. An acceptance control chart should be used only when: a) the within subgroup variation is in-control and the variation is estimated efficiently; b) a high level of process capability has been achieved. An acceptance control chart is typically used when the process variable under study is normally distributed; however, it can be applied to a non-normal distribution. The examples provided in this document illustrate a variety of circumstances in which this technique has advantages; these examples provide details of the determination of the sample size, the action limits and the decision criteria.

This document describes the construction and use of multivariate control charts in statistical process control (SPC) and establishes methods for using and understanding this generalized approach to control charts where the characteristics being measured are from variables data. The use of principal component analysis (PCA) and partial least squares (PLS) in the field of multivariate statistical process control is not presented in this document NOTE The document describes the current state of the art of multivariate control charts that are being applied in practice nowadays. It does not describe the current state of scientific research on the topic.

This document presents key elements and the philosophy of the control chart approach, and identifies a wide variety of control charts (including those related to the Shewhart control chart, those stressing process acceptance or online process adjustment, and specialized control charts). It presents an overview of the basic principles and concepts of control charts and illustrates the relationship among various control chart approaches to aid in the selection of the most appropriate part of ISO 7870 for given circumstances. It does not specify statistical control methods using control charts. These methods are specified in the relevant parts of ISO 7870.

This document describes a method to calculate process capability and performance indices for attribute characteristics. This method can be used as a supplement to the commonly used capability calculations for variable characteristics.

ISO 7870-8:2017 describes ways of applying regular variables control charts to short runs and small mixed batches where the sample size for monitoring is restricted to one. It provides a set of tools to facilitate the understanding of sources of variation in such processes so that the processes can be better managed. The charts described are process-focused rather than product-focused. The user can plot, monitor and control similar characteristics on different items, or different characteristics on an item, on a single control chart. NOTE 1 The terms short run and small batch size are not well defined. Here, short run and small batch size are taken to mean only a few items are manufactured before a different item is then produced. NOTE 2 For situations where the subgroup size is larger than one, other standards apply.

ISO 22514-2:2017 describes a procedure for the determination of statistics for estimating the quality capability or performance of product and process characteristics. The process results of these quality characteristics are categorized into eight possible distribution types. Calculation formulae for the statistical measures are placed with every distribution. The statistical methods described in this document only relate to continuous quality characteristics. They are applicable to processes in any industrial or economical sector. NOTE This method is usually applied in case of a great number of serial process results, but it can also be used for small series (a small number of process results).

ISO 22514-4:2016 describes process capability and performance measures that are commonly used.

ISO 7870-6:2016 covers EWMA control charts as a statistical process control technique to detect small shifts in the process mean. It makes possible the faster detection of small to moderate shifts in the process average. In this chart, the process average is evaluated in terms of exponentially weighted moving average of all prior sample means. EWMA weights samples in geometrically decreasing order so that the most recent samples are weighted most highly while the most distant samples contribute very little depending upon the smoothing parameter (λ).

ISO 22514-8:2014 aims to define the evaluation method to quantify the short-term capability of a production process (capacity of the production tool, widely termed capability), i.e. the machine performance index, to ensure compliance to a toleranced measurable product characteristic, when said process does not feature any kind of sorting system. If the production process integrates a sorting system, then this one (clearing away nonconforming parts) should be analysed independently. ISO 22514-8:2014 does not aim to define evaluation methods of the capability of a production process that is gauged through long-term observation (capability process or performance process indices). ISO 22514-8:2014 defines the principles guiding the development of indicators for quantifying capability, and the statistical methods to be employed. The characteristics used to evaluate production process capability have statistical distributions, and it is presumed, a priori, that at least one of these distributions is multi-modal. A distribution is presumed to be multimodal if it results from the marked effect of at least one cause inducing a significant difference between the produced items. ISO 22514-8:2014 applies, for example, to characteristics generated by processes such as the following: multi-cavity casting, multi-fixture machining, batch load treatments. Each cavity, fixture, or position in the batch load corresponds to a different state. The multi-state process can be understood as the result of the combination of different states within the same process (e.g. cavity, fixture, position in the batch load).

ISO 2514-1:2014 describes the fundamental principles of capability and performance of manufacturing processes. It has been prepared to provide guidance about circumstances where a capability study is demanded or necessary to determine if the output from a manufacturing process or the production equipment (a production machine) is acceptable according to appropriate criteria. Such circumstances are common in quality control when the purpose for the study is part of some kind of production acceptance. These studies can also be used when diagnosis is required concerning a production output or as part of a problem solving effort. The methods are very versatile and have been applied for many situations. ISO 2514-1:2014 is applicable to the following: organizations seeking confidence that their product characteristics requirements are fulfilled; organizations seeking confidence from their suppliers that their product specifications are and will be satisfied; those internal or external to the organization who audit it for conformity with the product requirements; and those internal to the organization who deal with analysing and evaluating the existing production situation to identify areas for process improvement.

ISO 7870-5:2014 establishes a guide to the use and understanding of specialized control charts in situations where commonly used Shewhart control chart approach to the methods of statistical control of a process may either be not applicable or less efficient in detecting unnatural patterns of variation of the process.

ISO 7870-2:2013 establishes a guide to the use and understanding of the Shewhart control chart approach to the methods for statistical control of a process. ISO 7870-2:2013 is limited to the treatment of statistical process control methods using only the Shewhart system of charts. Some supplementary material that is consistent with the Shewhart approach, such as the use of warning limits, analysis of trend patterns and process capability is briefly introduced. There are, however, several other types of control chart procedures, a general description of which can be found in ISO 7870-1.

ISO 22514-6:2013 provides methods for calculating performance and capability statistics for process or product quantities where it is necessary or beneficial to consider a family of singular quantities in relation to each other. The methods provided here mostly are designed to describe quantities that follow a bivariate normal distribution. In principle, this part of ISO 22514 can be used for multivariate cases. ISO 22514-6:2013 does not offer an evaluation of the different provided methods with respect to different situations of possible application of each method. For the current state, the selection of one preferable method might be done following the users preferences. The purpose is to give definitions for different approaches of index calculation for performance and capability in the case of a multiple process or product quantity description.

ISO 11462-2:2010 provides a catalogue of tools and techniques to help an organization in planning, implementation and evaluation of an effective statistical process control (SPC) system. This catalogue gives tools and techniques that are essential for the successful realization of the SPC elements.

Statistical process control (SPC) concerns the use of statistical techniques and/or statistical or stochastic control algorithms to achieve one or more of the following objectives: a) to increase knowledge about a process; b) to steer a process to behave in the desired way; c) to reduce variation of final-product parameters, or in other ways improve performance of a process. These guidelines give the elements for implementing an SPC system to achieve these objectives. The common economic objective of statistical process control is to increase good process outputs produced for a given amount of resource inputs. NOTE 1 SPC operates most efficiently by controlling variation of a process parameter or an in-process product parameter that is correlated with a final-product parameter; and/or by increasing the process's robustness against this variation. A supplier's final-product parameter may be a process parameter to the next downstream supplier's process. NOTE 2 Although SPC is concerned with manufactured goods, it is also applicable to processes producing services or transactions (for example, those involving data, communications, software, or movement of materials). This part of ISO 11462 specifies SPC system guidelines for use _ when a supplier's capability to reduce variation in processes associated with design or production needs to be proven or improved; or _ when a supplier is beginning SPC implementation to achieve such capability. These guidelines are not intended for contractual, regulatory or certification use.

ISO 7870-1:2014 presents key elements and philosophy of the control chart approach, and identifies a wide variety of control charts (including those related to the Shewhart control chart, those stressing process acceptance or online process adjustment, and specialized control charts). It presents an overview of the basic principles and concepts and illustrates the relationship among various control chart approaches to aid in the selection of the most appropriate standard for given circumstances. It does not specify statistical control methods using control charts. These methods will be specified in future parts of ISO 7870.

ISO 22514-2:2013 describes a procedure for the determination of statistics for estimating the quality capability or performance of product and process characteristics. The process results of these quality characteristics are categorized into eight possible distribution types. Calculation formulae for the statistical measures are placed with every distribution. The statistical methods described in ISO 22514-2:2013 only relate to continuous quality characteristics. They are applicable to processes in any industrial or economical sector.

ISO 22514-7:2012 defines a procedure to validate measuring systems and a measurement process in order to state whether a given measurement process can satisfy the requirements for a specific measurement task with a recommendation of acceptance criteria. The acceptance criteria are defined as a capability figure or a capability ratio.

ISO 7870-3:2012 gives guidance on the uses of acceptance control charts and establishes general procedures for determining sample sizes, action limits and decision criteria. This chart should be used only when: a) the within subgroup variation is in-control and the variation is estimated efficiently; b) a high level of process capability has been achieved. This chart is typically used when the process variable under study is normally distributed, however, it can be applied to a non-normal distribution. Examples are included to illustrate a variety of circumstances in which this technique has advantages and to provide details of the determination of the sample size, the action limits and the decision criteria.

ISO 7870-4:2011 provides statistical procedures for setting up cumulative sum (cusum) schemes for process and quality control using variables (measured) and attribute data. It describes general-purpose methods of decision-making using cumulative sum (cusum) techniques for monitoring, control and retrospective analysis.

ISO 22514-1:2009 describes the fundamental principles of capability and performance of manufacturing processes. It has been prepared to provide guidance about circumstances where a capability study is requested or is necessary to determine if the output from a manufacturing process or the production equipment (a production machine) is acceptable according to appropriate criteria. Such circumstances are common in quality control when the purpose for the study is part of some kind of production acceptance. These studies may also be used when diagnosis is required concerning a production output or as part of a problem solving effort. The methods are very versatile and have been applied for many situations. ISO 22514-1:2009 is applicable to the following: organizations seeking confidence that their product characteristics requirements are fulfilled; organizations seeking confidence from their suppliers that their product specifications are and will be satisfied; those internal or external to the organization who audit it for conformity with the product requirements; those internal to the organization who deal with analysing and evaluating the existing production situation to identify areas for process improvement.

ISO 22514-3:2008 prescribes the steps to be taken in conducting short-term performance studies that are typically performed on machines where parts produced consecutively under repeatability conditions are considered. The number of observations to be analysed will vary according to the patterns the data produce, or if the runs (the rate at which items are produced) on the machine are low in quantity. The methods are not recommended where the sample size produced is less than 30 observations. Methods to be used for handling the data and carrying out the calculations are described. In addition, machine performance indices and the actions required at the conclusion of a machine performance study are described. ISO 22514-3:2008 is not applicable when tool wear patterns are expected to be present during the duration of the study, nor if autocorrelation between observations is present. The situation where a machine has captured the data, sometimes thousands of data points collected in a minute, is not considered suitable for the application of ISO 22514-3:2008.

ISO/TR 22514-4:2007 describes process capability and performance measures that are commonly used.

ISO 7870-1:2007 presents key elements and philosophy of the control chart approach, and identifies a wide variety of control charts (including those related to the Shewhart control chart and those stressing process acceptance or on-line process adjustment). ISO 7870-1:2007 presents an overview of the basic principles and concepts and illustrates the relationship among various control chart approaches to aid in the selection of the most appropriate standard for given circumstances. It does not specify statistical control methods using control charts.

ISO 21747:2006 describes a procedure for the determination of statistics in order to estimate the quality capability of product and process characteristics. The process results of these quality characteristics are tabularized into eight possible distribution types. Calculation formulae for the statistical values are placed with every distribution.These statistics relate to continuous quality characteristics exclusively. ISO 21747:2006 is applicable to processes in any industrial or economical sector.

Gives the principles of cusum charting and includes guidance on the preparation and interpretation of cusum charts using basic decision rules.

Specifies procedures for the statistical control of processes by using control charts based on calculating the arithmetic average of a sample and using warning limits and action limits. It is assumed that for large lots and for the mass output of piece and batch production, such a measure of quality is a random variable following a normal distribution. However, when averages of four or more items are plotted, this assumption of a normal distribution is not necessary for control purposes.

Gives guidance on the uses of acceptance control charts and establishes general procedures for determining sample sizes, action limits and decision criteria. Examples are included to illustrate a variety of circumstances in which this technique has advantages and to provide details of the determination of the sample size, the action limits and the decision criteria.

Presents key elements and philosophy of the control chart approach, and identifies a wide variety of control charts, including those related to the Shewhart control chart, the acceptance control chart and the adaptive control chart. Presents an overview of the basic principles and concepts and illustrates the relationship among various control chart approaches to aid in the selection of the most appropriate standard for given circumstances. Does not specify statistical control methods using control charts.

Adds in table 5, third column, first line "3" after "±".

Establishes a guide to the use and understanding of the control chart approach to the methods for statistical control of a process. Annex A is for information only.