ISO/TC 69 - Applications of statistical methods

This document describes a data format for the exchange of quality information: — the data format is distinguished by a transparent structure that is easy to edit; — it is flexible, space saving and easily be copied and compacted; All files are language independent because of the allocation of an explicit key to a language independent field, the content of which can be translated into any language required.

This document — introduces conditions, constraints and resources necessary to evaluate a measurement method or a result; — defines an organizational scheme for the acquisition of trueness and precision data by study; — provides the necessary definitions, statistical model and principles for ISO 5725 (all parts). — is not applicable to proficiency testing or production of the reference item that has their own standards (ISO 13528, respectively and ISO Guide 35). This document is concerned exclusively with measurement methods which yield results on a continuous scale and give a single value as the test result, although this single value may be the outcome of a calculation from a set of observations. It defines values which describe, in quantitative terms, the ability of a measurement method to give a true result (trueness) or to replicate a given result (precision). Thus, there is an implication that exactly the identical item is being measured, in exactly the same way, and that the measurement process is under control. This document may be applied to a very wide range of test items, including gas, liquids, powders and solid objects, manufactured or naturally occurring, provided that due consideration is given to any heterogeneity of the test item. This document does not include methods of calculation that are described in the other parts.

This document provides a) a discussion of alternative experimental designs for the determination of trueness and precision measures including reproducibility, repeatability and selected measures of intermediate precision of a standard measurement method, including a review of the circumstances in which their use is necessary or beneficial, and guidance as to the interpretation and application of the resulting estimates, and b) worked examples including specific designs and computations. Each of the alternative designs discussed in this document is intended to address one (or several) of the following issues: a) a discussion of the implications of the definitions of intermediate precision measures; b) a guidance on the interpretation and application of the estimates of intermediate precision measures in practical situations; c) determining reproducibility, repeatability and selected measures of intermediate precision; d) improved determination of reproducibility and other measures of precision; e) improving the estimate of the sample mean; f) determining the range of in-house repeatability standard deviations; g) determining other precision components such as operator variability; h) determining the level of reliability of precision estimates; i) reducing the minimum number of participating laboratories by optimizing the reliability of precision estimates; j) avoiding distorted estimations of repeatability (split-level designs); k) avoiding distorted estimations of reproducibility (taking the heterogeneity of the material into consideration). Often, the performance of the method whose precision is being evaluated in a collaborative study will have previously been assessed in a single-laboratory validation study conducted by the laboratory which developed it. Relevant factors for the determination of intermediary precision will have been identified in this prior single-laboratory study.

This document establishes a guide to the use and understanding of Shewhart control chart approach to the methods for statistical control of a process. This document is limited to the treatment of statistical process control methods using only Shewhart system of charts. Some supplementary material that is consistent with Shewhart approach, such as the use of warning limits, analysis of trend patterns and process capability is briefly introduced. However, there are several other types of control charts which can be used in different situations.

This document provides statistical techniques for the determination of the reproducibility of the level of detection for a) binary (qualitative) test methods for continuous measurands, e.g. the content of a chemical substance, and b) binary (qualitative) test methods for discrete measurands, e.g. the number of RNA copies in a sample. The reproducibility precision is determined according to ISO 5725 (all parts). Precision estimates are subject to random variability. Accordingly, it is important to determine the uncertainty associated with each estimate, and to understand the relationship between this uncertainty, the number of participants and the experimental design. This document thus provides not only a description of statistical tools for the calculation of the LOD reproducibility precision, but also for the standard error of the estimates.

The current ISO 16355 series is written intentionally independent of industry because the principles of applying statistical methods for product and technology development are similar for all types of products. However, when applying the standard for the development of fully or partially digitized products in practice, specific characteristics of digital goods in product development (such as measurability, immateriality, economies of scale effects, etc.) are taken into account. This document gives guidelines for adapting the quality function deployment (QFD) process, its purpose, users, and tools as they are described in the ISO 16355 series that consider these specific characteristics for developing digitalized products and services. Table 1 illustrates the scope of this document by stating examples of the types of products the standard focuses on. Users of this document include all organization functions necessary to assure customer satisfaction, including business planning, marketing, sales, research and development (R&D), engineering, information technology (IT), manufacturing, procurement, quality, production, service, packaging and logistics, support, testing, regulatory, and other phases in hardware, software, service, and system organizations.

This document specifies experimental procedures and statistical analysis for the determination of measurement uncertainty in situations where the following conditions are fulfilled: Condition 1: The level of the measurand is non-negative, e.g. concentration level of a contaminant in a sample. Condition 2: Measurement error consists of two independent components: for one of these components the relative standard deviation is constant (that is, the absolute deviation is proportional to the level of the measurand), whereas for the other component the absolute standard deviation is constant (that is, independent of the level of the measurand). Condition 3: Samples for different levels of the measurand can be made available; if the level of the measurand is the concentration of a chemical substance, samples could be obtained e.g. by fortifying (spiking) blank samples. Conditions 1 and 2 are met for most applications of instrumental chemical analyses. Condition 3 can be met for chemical analyses if blank samples are available. This document can also be used to determine precision data for a particular laboratory for different technicians, different environmental conditions, the same or similar test items, with the same level of the measurand, over a certain period of time.

This document specifies two-stage (double) sampling plans by attributes for inspection for a proportion of nonconforming items in a target population of discrete units, in particular: a) the proportion of nonconforming items in a lot of product items; b) the proportion of nonconforming function instances of an internal control system (ICS); c) the proportion of misstatements in a population of accounting entries or booking records; d) the proportion of nonconforming test characteristics of an entity subject to an acceptance test, e.g. in product and process audits. The plans are preferable to single sampling plans where the cost of inspection is high or where the delay and uncertainty caused by the possible requirement for second samples is inconsequential. The statistical theory underlying the plans, tables and figures are provided in Annexes A through K.

This document describes a method to evaluate the standard uncertainty for a process mean, arising from observable variation in successive possibly autocorrelated measurements. In this document, the successive measurements are restricted to stationary processes. This document also includes tests for validity of assumptions. The resulting uncertainty is related to that arising from observable measurements while other sources of uncertainty are also considered.

This document provides detailed descriptions of statistical methods for proficiency testing providers to use to design proficiency testing schemes and to analyse the data obtained from those schemes. This document provides recommendations on the interpretation of proficiency testing data by participants in such proficiency testing schemes and by accreditation bodies. The procedures in this document can be applied to demonstrate that the measurement results obtained by laboratories, inspection bodies, and individuals meet specified criteria for acceptable performance. This document is applicable to proficiency testing where the results reported are either quantitative measurements or qualitative observations on test items. NOTE The procedures in this document can also be applied for the assessment of expert opinion where the opinions or judgments are reported in a form which can be compared objectively with an independent reference value or a consensus statistic. For example, when classifying proficiency test items into known categories by inspection - or in determining by inspection whether proficiency test items arise, or do not arise, from the same original source - and the classification results are compared objectively, the provisions of this document that relate to nominal (qualitative) properties can be applied.

This document specifies single sampling plans for lot-by-lot inspection under the following conditions: a) where the inspection procedure is applied to a continuing series of lots of discrete products, all supplied by one producer using one production process; b) where only a single quality characteristic, x, of these products is taken into consideration, which is measurable on a continuous scale; c) where production is under statistical control and the quality characteristic, x, is distributed according to a normal distribution or a close approximation to the normal distribution; d) where a contract or standard defines a lower specification limit, L, an upper specification limit, U, or both. An item is qualified as conforming if its measured quality characteristic, x, satisfies as appropriate one of the following inequalities: 1) x ≥ L (i.e. the lower specification limit is not violated); 2) x ≤ U (i.e. the upper specification limit is not violated); 3) x ≥ L and x ≤ U (i.e. neither the lower nor the upper specification limit is violated). Inequalities 1) and 2) are cases with a single specification limit, and 3) is a case with double specification limits. Where double specification limits apply, it is assumed in this document that conformity to both specification limits is equally important to the integrity of the product. In such cases, it is appropriate to apply a single AQL to the combined percentage of a product outside the two specification limits. This is referred to as combined control.

This document sets out guidelines for checking conformity with quantifiable characteristics using the test or measurement result and its associated measurement uncertainty. This document is applicable whenever the uncertainty may be quantified according to the principles laid down in ISO/IEC Guide‑98‑3 (GUM). The term uncertainty is thus a descriptor for all elements of variation in the measurement result, including uncertainty due to sampling. This document does not give rules for how to act when an inconclusive result of a conformity test has been obtained. NOTE There are not limitations on the nature of the entity subject to the requirements nor on the quantifiable characteristic. Examples of entities together with quantifiable characteristics are given in Table A.1.

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 provides guidance for implementing the theories of the ISO 11843 series in various practical situation. As defined in this series, the term minimum detectable value corresponds to the limit of detection or detection limit defined by the IUPAC. The focus of interest is placed on the practical applications of statistics to quantitative analyses.

This document introduces five statistical methods for evaluating the precision of binary measurement methods and their results. The five methods can be divided into two types. Both types are based on measured values provided by each laboratory participating in a collaborative study. In the first type, each laboratory repeatedly measures a single sample. The samples measured by the laboratories are nominally identical. The second type is an extension of the first type, where there are several levels of samples. For each statistical method, this document briefly summarizes its theory and explains how to estimate the proposed precision measures. Some real cases are illustrated to help the readers understand the evaluation procedures involved. For the first and second types of methods, five and three cases are presented, respectively. Finally, this document compares the five statistical methods.

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 part of ISO 16355 describes the quality function deployment (QFD) process, its purpose, users, and tools. It does not provide requirements or guidelines for organizations to develop and systematically manage their policies, processes, and procedures in order to achieve specific objectives. Users of this part of ISO 16355 will include all organization functions necessary to assure customer satisfaction, including business planning, marketing, sales, research and development (R&D), engineering, information technology (IT), manufacturing, procurement, quality, production, service, packaging and logistics, support, testing, regulatory, and other phases in hardware, software, service, and system organizations.

This document specifies guidelines for applying the robust tolerance design (RTD) provided by the Taguchi methods to a product in order to finalize the design of the product. NOTE 1 RTD is applied to the target product to set the optimum tolerances of the design parameters around the nominal values. RTD identifies the effects of errors in the controllable design parameters on product output and estimates the total variance of the product output if the tolerances are changed. Hence, RTD achieves the target variance of the output from the viewpoints of robustness, performance, and cost. NOTE 2 The tolerance expresses a maximum allowable error in the value of a design parameter in the manufacturing process. In a perfect world, the parts or elements of every product have the designed nominal values of the design parameters. However, actual manufacturing does not reproduce the exact designed nominal values of the design parameters for all products. The actual products have errors in the values of their parts or elements. These errors are supposed to be within the designed tolerances.

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 necessary steps of the one-way and two-way analyses of variance (ANOVA) for fixed effect models in balanced design. Unbalanced design, random effects and nested design patterns are not included in this document. This document provides examples to analyse the differences among group means by splitting the overall observed variance into different parts. Several illustrations from different fields with different emphasis suggest the procedure of the analysis of variance.

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 establishes single sampling plans for conformance testing, i.e., for assessing whether the quality level of a relevant audit population (lot, process, inventory, file etc) conforms to a declared value. Sampling plans are provided corresponding to four levels of discriminatory ability. The limiting quality ratio (LQR) (see Clause 4) of each sampling plan is given for reference. For levels I-III, the sampling plans have been devised so as to obtain a risk no more than 5 % of contradicting a correct declared quality level. The risk of failing to contradict an incorrectly declared quality level which is related to the LQR is no more than 10 %. The sample sizes for level 0 are designed in a way that the LQR factors of the sampling plans are compatible with the LQR factors for level I. In contrast to the procedures in the other parts of the ISO 2859 series, the procedures in this document are not applicable to acceptance assessment of lots. Generally, this document mainly focuses on controlling type I error, which differs from the balancing of the risks in the procedures for acceptance sampling. This document can be used for various forms of quality inspection in situations where objective evidence of conformity to some declared quality level is to be provided by means of inspection of a sample. The procedures are applicable to entities such as lots, process output, etc. that allow random samples of individual items to be taken from the entity. The sampling plans provided in this document are applicable, but not limited, to the inspection of a variety of targets such as: — end items; — components and raw materials; — operations; — materials in process; — supplies in storage; — maintenance operations; — data or records; — administrative procedures; — accounting procedures or accounting entries; — internal control procedures. This document considers two types of quality models for discrete items and populations, as follows. i) The conforming-nonconforming model, where each item is classified as conforming or nonconforming, and where the quality indicator of a population of items is the proportion p of nonconforming items, or, equivalently, the percentage 100 p of nonconforming items. ii) The nonconformities model, where the number of nonconformities is counted on each item, and where the quality indicator of a population of items is the average number λ of nonconformities found on items in the population, or, equivalently, the percentage 100 λ of nonconformities on items in the population.

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.

1.1 This document — specifies basic methods for estimating the bias of a measurement method and the laboratory bias when a measurement method is applied; — provides a practical approach of a basic method for routine use in estimating the bias of measurement methods and laboratory bias; — provides a brief guidance to all personnel concerned with designing, performing or analysing the results of the measurements for estimating bias. 1.2 It is concerned exclusively with measurement methods which yield measurements on a continuous scale and give a single value as the measurement result, although the single value can be the outcome of a calculation from a set of observations. 1.3 This document applies when the measurement method has been standardized and all measurements are carried out according to that measurement method. NOTE In ISO/IEC Guide 99:2007(VIM), "measurement procedure" (2.6) is an analogous term related to the term "measurement method" used in this document. 1.4 This document applies only if an accepted reference value can be established to substitute the true value by using the value, for example: — of a suitable reference material; — of a suitable measurement standard; — referring to a suitable measurement method; — of a suitable prepared known sample. 1.5 This document applies only to the cases where it is sufficient to estimate bias on one property at a time. It is not applicable if the bias in the measurement of one property is affected by the level of any other property (i.e. it does not consider interferences by any influencing quantity). Comparison of the trueness of two-measurement methods is considered in ISO 5725-6.

This document specifies an acceptance sampling system for inspection by attributes indexed by limiting quality (LQ). The sampling system is used for lots in isolation (isolated sequences of lots, an isolated lot, a unique lot or a short series of lots), where switching rules, such as those of ISO 2859‑1, are not applicable. Inspection levels, as provided by ISO 2859‑1 to control the relative amount of inspection, are not provided in this document. In many industrial situations, in which switching rules might be used, they are not applied for a number of reasons, not all of which might be valid: a) production is intermittent (not continuous); b) production is from several different sources in varying quantities, i.e. "job lots"; c) lots are isolated; d) lots are resubmitted after inspection. The sampling plans in this document are indexed by a series of specified values of limiting quality (LQ), where the consumer's risk (the probability of acceptance at the LQ) is usually below 0,10 (10 %), except in some instances. This document is intended both for inspection for nonconforming items and for inspection for nonconformities per 100 items. It is intended to be used when the supplier and the consumer both regard the lot to be in isolation. That is, the lot is unique in that it is the only one of its type produced. It can also be used when there is a series of lots too short for switching rules to be applied.

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.

1.1 This document — amplifies the general principles for designing experiments for the numerical estimation of the precision of measurement methods by means of a collaborative interlaboratory experiment; — provides a detailed practical description of the basic method for routine use in estimating the precision of measurement methods; — provides guidance to all personnel concerned with designing, performing or analysing the results of the tests for estimating precision. NOTE Modifications to this basic method for particular purposes are given in other parts of ISO 5725. 1.2 It is concerned exclusively with measurement methods which yield measurements on a continuous scale and give a single value as the test result, although this single value can be the outcome of a calculation from a set of observations. 1.3 It assumes that in the design and performance of the precision experiment, all the principles as laid down in ISO 5725-1 are observed. The basic method uses the same number of test results in each laboratory, with each laboratory analysing the same levels of test sample; i.e. a balanced uniform-level experiment. The basic method applies to procedures that have been standardized and are in regular use in a number of laboratories. 1.4 The statistical model of ISO 5725-1:1994, Clause 5, is accepted as a suitable basis for the interpretation and analysis of the test results, the distribution of which is approximately normal. 1.5 The basic method, as described in this document, (usually) estimates the precision of a measurement method: a) when it is required to determine the repeatability and reproducibility standard deviations as defined in ISO 5725-1; b) when the materials to be used are homogeneous, or when the effects of heterogeneity can be included in the precision values; and c) when the use of a balanced uniform-level layout is acceptable. 1.6 The same approach can be used to make a preliminary estimate of precision for measurement methods which have not reached standardization or are not in routine use.

This document provides guidance for QFD-related approaches to optimization through robust parameter design to ensure customer satisfaction with new products, services, and information systems. It is applicable to identify optimum nominal values of design parameters based on the assessment of robustness of its function at the product design phase. NOTE Some of the activities described in this document can be used at earlier and later stages. Other approaches to solve optimization problems in new technology and product development processes are listed in Annex B.

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.

This document provides guidelines for the identification of distributions related to the implementation of Six Sigma. Examples are given to illustrate the related graphical and numerical procedures. It only considers one dimensional distribution with one mode. The underlying distribution is either continuous or discrete.

This document presents methods for determining the critical value of the response variable and the minimum detectable value in Poisson distribution measurements. It is applicable when variations in both the background noise and the signal are describable by the Poisson distribution. The conventional approximation is used to approximate the Poisson distribution by the normal distribution consistent with ISO 11843‑3 and ISO 11843‑4. The accuracy of the normal approximation as compared to the exact Poisson distribution is discussed in Annex C.

This document describes quantitative approaches for acquisition of the voice of customer (VOC) and voice of stakeholder (VOS) and its purpose, and provides recommendations on the use of the applicable tools and methods. It is not a management system standard. NOTE It does not provide requirements or guidelines for organizations to develop and systematically manage their policies, processes, and procedures in order to achieve specific objectives. Users of this document include all organization functions necessary to assure customer satisfaction, including business planning, marketing, sales, research and development (R&D), engineering, information technology (IT), manufacturing, procurement, quality, production, service, packaging and logistics, support, testing, regulatory, and other phases in hardware, software, service, and system organizations.

1.1 This document is concerned with polynomial calibration functions that describe the relationship between a stimulus variable and a response variable. These functions contain parameters estimated from calibration data consisting of a set of pairs of stimulus value and response value. Various cases are considered relating to the nature of any uncertainties associated with the data. 1.2 Estimates of the polynomial function parameters are determined using least‐squares methods, taking account of the specified uncertainty information. It is assumed that the calibration data are fit for purpose and thus the treatment of outliers is not considered. It is also assumed that the calibration data errors are regarded as drawn from normal distributions. An emphasis of this document is on choosing the least‐squares method appropriate for the nature of the data uncertainties in any particular case. Since these methods are well documented in the technical literature and software that implements them is freely available, they are not described in this document. 1.3 Commonly occurring types of covariance matrix associated with the calibration data are considered covering (a) response data uncertainties, (b) response data uncertainties and covariances, (c) stimulus and response data uncertainties, and (d) stimulus data uncertainties and covariances, and response data uncertainties and covariances. The case where the data uncertainties are unknown is also treated. 1.4 Methods for selecting the degree of the polynomial calibration function according to prescribed criteria are given. The covariance matrix associated with the estimates of the parameters in the selected polynomial function is available as a by‐product of the least‐squares methods used. 1.5 For the chosen polynomial function this document describes the use of the parameter estimates and their associated covariance matrix for inverse and direct evaluation. It also describes how the provisions of ISO/IEC Guide 98‐3:2008 (GUM) can be used to provide the associated standard uncertainties. 1.6 Consideration is given to accounting for certain constraints (such as the polynomial passing through the origin) that may need to be imposed and also to the use of transformations of the variables that may render the behaviour of the calibration function more polynomial‐like. Interchanging the roles of the variables is also considered. 1.7 Examples from several areas of measurement science illustrate the use of this document.

Background noise exists ubiquitously in analytical instruments, whether or not a sample is applied to the instrument. This document is concerned with mathematical methodologies for estimating the minimum detectable value in case that the most predominant source of measurement uncertainty is background noise. The minimum detectable value can directly and mathematically be derived from the stochastic characteristics of the background noise. This document specifies basic methods to — extract the stochastic properties of the background noise, — use the stochastic properties to estimate the standard deviation (SD) or coefficient of variation (CV) of the response variable, and — calculate the minimum detectable value based on the SD or CV obtained above. The methods described in this document are useful for checking the detection of a certain substance by various types of measurement equipment in which the background noise of the instrumental output predominates over the other sources of measurement uncertainty. Feasible choices are visible and ultraviolet absorption spectrometry, atomic absorption spectrometry, atomic fluorescence spectrometry, luminescence spectrometry, liquid chromatography and gas chromatography.

This International Standard specifies sequential sampling plans and procedures for inspection by variables of discrete items. The plans are indexed in terms of producer's risk point and the consumer's risk point. Therefore, they are suitable not only for the purposes of acceptance sampling, but for the more general purpose of the testing of simple statistical hypotheses for proportions. The purpose of this International Standard is to provide procedures for the sequential assessment of inspection results that may be used to induce the supplier to supply lots of a quality having a high probability of acceptance. At the same time, the consumer is protected by a prescribed upper limit to the probability of accepting a lot (or process) of poor quality. This International Standard is primarily designed for use under the following conditions: a) where the inspection procedure is to be applied to a continuing series of lots of discrete products all supplied by one producer using one production process. In such a case, sampling of particular lots is equivalent to the sampling of the process. If there are different producers or production processes, this International Standard shall be applied to each one separately; b) where only a single quality characteristic x of these products is taken into consideration, which must be measurable on a continuous scale; c) where the measurement error is negligible (i.e. with a standard deviation no more than 10 % of the process standard deviation); d) where production is stable (under statistical control) and the quality characteristic x has a known standard deviation, and is distributed according to a normal distribution or a close approximation to the normal distribution; CAUTION — The procedures in this International Standard are not suitable for application to lots that have been screened previously for nonconforming items. e) where a contract or standard defines an upper specification limit U, a lower specification limit L, or both; an item is qualified as conforming if and only if its measured quality characteristic, x, satisfies the appropriate one of the following inequalities: x ≤ U (i.e. the upper specification limit is not violated); x ≥ L (i.e. the lower specification limit is not violated); and (i.e. neither the upper nor the lower specification limit is violated.) Inequalities 1) and 2) are called cases with a "single specification limit", and 3) is the case with "double specification limits". In this International Standard, it is assumed that, where double specification limits apply, conformance to both specification limits is either equally important to the integrity of the product or is considered separately for both specification limits. In the first case, it is appropriate to control the combined percentage of product outside the two specification limits. This is referred to as combined control. In the second case, nonconformity beyond each of the limits is controlled separately, and this is referred to as separate control.

ISO 28592:2017 provides double sampling plans by attributes for the acceptance inspection of lots of discrete items. The plans are indexed by the producer's risk quality (PRQ) and the consumer's risk quality (CRQ) where the nominal producer's and consumer's risks are respectively either (5 %, 5 %), (5 %, 10 %) or (10 %, 10 %). Plans are provided for inspection for percent nonconforming and for inspection for nonconformities per 100 items. The lot is accepted if there are no nonconforming items (nonconformities) in the first random sample, and rejected if it contains two or more nonconforming items (nonconformities). If precisely one nonconforming item is found in the first sample, a second random sample is drawn; the lot is then accepted if the second sample contains no nonconforming items (nonconformities) and rejected otherwise. The objective of this International Standard is to provide procedures that enable lot disposition to be determined quickly and economically if quality is particularly good or bad. For intermediate quality, a second sample is drawn in order to be able to discriminate more reliably between acceptable and unacceptable lots. The two sample sizes are chosen to minimize the maximum expected sample size with respect to incoming quality subject to the nominal risks not being exceeded. Similarly, the plans may be used to test the hypothesis that a lot or process quality level is equal to the PRQ (i.e. acceptable) against the alternative hypothesis that the quality level is equal to the CRQ (i.e. unacceptable). The plans are preferable to single sampling plans where the cost of inspection is high, where the delay and uncertainty caused by the possible requirement for second samples is inconsequential and where a relatively large ratio of the consumer's risk quality to the producer's risk quality can be tolerated. The plans are suitable for isolated lots or for short series of lots, where the sum of the two sample sizes is no larger than about 10 % of the size of the lot. The plans are also suitable for continuing series of lots when lots that fail to satisfy the acceptance criteria are 100 % inspected and all nonconforming items replaced by conforming items; however, for continuing series of lots, consideration should also be given to using double sampling plans from ISO 2859‑1. The statistical theory underlying the plans, tables and figures is provided in Annex A.

ISO 28590:2017 provides a general introduction to acceptance sampling by attributes and provides a brief summary of the attribute sampling schemes and plans used in ISO 2859‑1, ISO 2859‑2, ISO 2859‑3, ISO 2859‑4 and ISO 2859‑5, which describe specific types of attribute sampling systems. It also provides guidance on the selection of the appropriate inspection system for use in a particular situation.

ISO 28598-1:2017 provides guidelines specifying the organizational principles of acceptance sampling in situations where the contract or the legislation provides for successive inspection to be carried out by different parties: the supplier, the customer and/or a third party. These guidelines are designed for inspection of populations of any product supplied or delivered in discrete items in lots. They are applicable to - supplier inspection (final inspection, product certification upon supplier's request), - customer inspection (incoming inspection, audit inspection, acceptance sampling), - third-party inspection (certification of product, inspection and supervision for observance of International Standard requirements, quality inspection carried out at the supplier, and/or customer, request), where the quality levels and the lot acceptability criteria are specified unilaterally by the supplier or contractually by the supplier and the customer. These guidelines are also applicable to situations when only one sampling inspection is actually needed. NOTE Single sampling APP plans by attributes are given in ISO 28598‑2. The guidelines provided by this part of ISO 28598 may be applied in developing standards on acceptance sampling for standard inspection models, specific items or quality levels, as well as in developing contracts, specifications and instructions. In contractual use of the APP, the parties concerned should acknowledge in the contract that they approve of its principles (also by referring to the present guidelines). The parties may also provide for the use of the APP in disputes and arbitration.

ISO 28593:2017 specifies a system of single sampling schemes for lot-by-lot inspection by attributes. All the sampling plans of the present system are of accept-zero form, i.e. no lot is accepted if the sample from it contains one or more nonconforming items. The schemes depend on a suitably-defined average outgoing quality limit (AOQL), the value of which is chosen by the user; no restrictions are placed on the choice of the value of the AOQL or on the sizes of successive lots in the series. The methodology ensures that the overall average quality reaching the customer or market-place will not exceed the AOQL in the long run.

ISO 28597:2017 specifies, for quality levels expressed as nonconforming items per million items, procedures for estimating the quality level of a single entity (e.g. a lot) and, when the production process is in statistical control, for estimating the process quality level based on evidence from several samples. Procedures are also specified for using this information when selecting a suitable sampling plan so as to verify that the quality level of a given lot does not exceed a stated limiting quality level (LQL). For the case where no prior sample data is available, guidance is given for presuming a process quality level in selecting a plan.

ISO 28591:2017 specifies sequential sampling plans and procedures for inspection by attributes of discrete items. The plans are indexed in terms of the producer's risk point and the consumer's risk point. Therefore, they can be used not only for the purposes of acceptance sampling, but for a more general purpose of the verification of simple statistical hypotheses for proportions. The purpose of this International Standard is to provide procedures for sequential assessment of inspection results that may be used to induce the supplier, through the economic and psychological pressure of non-acceptance of lots of inferior quality, to supply lots of a quality having a high probability of acceptance. At the same time, the consumer is protected by a prescribed upper limit to the probability of accepting lots of poor quality. ISO 28591:2017 provides sampling plans that are applicable, but not limited, to inspection in different fields, such as: - end items, - components and raw materials, - operations, - materials in process, - supplies in storage, - maintenance operations, - data or records, and - administrative procedures. ISO 28591:2017 contains sampling plans for inspection by attributes of discrete items. The sampling plans may be used when the extent of nonconformity is expressed either in terms of proportion (or percent) nonconforming items or in terms of nonconformities per item (per 100 items). The sampling plans are based on the assumption that nonconformities occur randomly and with statistical independence. There may be good reasons to suspect that one nonconformity in an item could be caused by a condition also likely to cause others. If so, it would be better to consider the items just as conforming or not, and ignore multiple nonconformities. The sampling plans from this International Standard should primarily be used for the analysis of samples taken from processes. For example, they may be used for the acceptance sampling of lots taken from a process that is under statistical control. However, they may also be used for the acceptance sampling of an isolated lot when its size is large, and the expected fraction nonconforming is small (significantly smaller than 10 %). In the case of the acceptance sampling of continuing series of lots, the system of sequential sampling plans indexed by acceptance quality limit (AQL) for lot-by-lot inspection published in ISO 2859‑5 should be applied.

ISO 28594:2017 provides a set of accept‑zero sampling systems and procedures for planning and conducting inspections to assess quality and conformance to specified requirements. In addition, this International Standard provides requirements for alternative acceptance methods proposed by the supplier. Such alternative methods would be based upon establishing and implementing an internal prevention‑based quality management system as a means of ensuring that all products conform to requirements specified by the contract and associated specifications and standards. ISO 28594:2017, when cited in contract, is applicable to the supplier and extends to subcontractors or vendors. The quality plans are to be applied as specified in the contract documents, and deliverables may be submitted for acceptance if the requirements of this International Standard have been met. Sampling systems and procedures in this International Standard are applicable, when appropriate, to assess conformance to requirements of the following: a) end items; b) components or basic materials; c) operations or services; d) materials in process; e) supplies in storage; f) maintenance operations; g) data or records; h) administrative procedures. NOTE Use of the word "product" throughout this International Standard also refers to services and other deliverables. The sampling systems and procedures of this International Standard are not intended for use with destructive tests or where product screening is not feasible or desirable. In such cases, the sampling systems to be used will be specified in the contract or product specifications.

This part of ISO 28598 provides attributes sampling procedures and single sampling plans for successive independent inspections of the same lot conducted by the supplier, customer and/or a third party. This part of ISO 28598 addresses: - supplier inspection (final inspection, product certification upon supplier's request); - customer inspection (incoming inspection, surveillance, acceptance sampling); - third party inspection. This part of ISO 28598 may also be applicable when only one inspection is needed. A catalogue of single sampling plans is given, indexed by the normative quality limits (NQLs). This part of ISO 28598 provides sampling procedures for: - finished product; - components and discrete items; - operations; - discrete items and the processes that produce them; - data and records. Attributes sampling procedures are provided for inspection of an isolated lot or a continuing series of lots of a discrete product. These procedures are applicable when a normative quality limit (NQL) is given and expressed in terms of percent nonconforming or nonconformities per 100 items. This part of ISO 28598 provides a co-ordinated system of supplier, customer and third party acceptance sampling procedures. It is also applicable to the case where a supplier individually, or on agreement with a customer, in a contract, specifies a lot quality criterion expressed in terms of an NQL. In either case, it provides a coherent methodology for designating lots as satisfactory or unsatisfactory for shipment and proposed use.

ISO 21748:2017 gives guidance for - evaluation of measurement uncertainties using data obtained from studies conducted in accordance with ISO 5725‑2, and - comparison of collaborative study results with measurement uncertainty (MU) obtained using formal principles of uncertainty propagation (see Clause 14). ISO 5725‑3 provides additional models for studies of intermediate precision. However, while the same general approach may be applied to the use of such extended models, uncertainty evaluation using these models is not incorporated in this document. ISO 21748:2017 is applicable to all measurement and test fields where an uncertainty associated with a result has to be determined. ISO 21748:2017 does not describe the application of repeatability data in the absence of reproducibility data. ISO 21748:2017 assumes that recognized, non-negligible systematic effects are corrected, either by applying a numerical correction as part of the method of measurement, or by investigation and removal of the cause of the effect. The recommendations in this document are primarily for guidance. It is recognized that while the recommendations presented do form a valid approach to the evaluation of uncertainty for many purposes, it is also possible to adopt other suitable approaches. In general, references to measurement results, methods and processes in this document are normally understood to apply also to testing results, methods and processes.

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/TR 16355-8:2017 describes after optimization of product design to address non-functional requirements, for example, test, produce, commercialize, deliver, support, and eventually retire a product from the market and provides guidance on the use of the applicable tools and methods. The goal is to identify and assure key processes and measures in order to satisfy and deliver value to customers and stakeholders. The topics in this document are not exhaustive and vary according to industry, product, and markets. They are considered a guide to encourage users of this document to explore activities needed to accomplish the same goal for their products. NOTE Some of the activities described in this document can be used at an earlier stage. Users of this document include all organization functions necessary to assure customer satisfaction, including business planning, marketing, sales, research and development (R&D), engineering, information technology (IT), manufacturing, procurement, quality, production, service, packaging and logistics, support, testing, regulatory, business process design, and other phases in hardware, software, service, and system organizations.