03.120.30 - Application of statistical methods
ICS 03.120.30 Details
Application of statistical methods
Anwendung statistischer Methoden
Application des méthodes statistiques
Uporaba statističnih metod
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This document covers EWMA control charts, originally proposed by Roberts (1959)[16], 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 mean. In this chart, the process mean is evaluated in terms of exponentially weighted moving average of all previous observations or averages. The EWMA control chart’s application is worthwhile in particular when — production rate is slow, — a minor or moderate shift in the process mean is vital to be detected, — sampling and inspection procedure is complex and time consuming, — testing is expensive, and — it involves safety risks. NOTE EWMA control charts are applicable for both variables and attributes data. The given examples illustrate both types (see 5.5, Annex A, Annex B and Annex C).
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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.
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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.
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This document specifies an acceptance sampling system of single sampling plans for inspection by variables, primarily designed for use under the following conditions: a) where the inspection procedure is applied to an isolated lot of discrete products all supplied by one producer using one production process; b) where only a single quality characteristic, x, of this process is taken into consideration, which is measurable on a continuous scale; c) where the quality characteristic, x, is distributed according to a normal distribution or a close approximation to a normal distribution; d) where the quality characteristic can be measured without error or with moderate measurement error; e) 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 and only if its measured quality characteristic, x, satisfies the 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, whereas inequality 3) is a case with double specification limits. Where double specification limits apply, it is assumed in this document that conformance to both specification limits is equally important to the integrity of the product. In such cases, it is appropriate to apply a single LQ to the combined fraction of a product outside the two specification limits. This is referred to as combined control.
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This document describes process capability and performance measures when the specifications are given by geometrical product specifications e.g. maximum material requirements or linear size with a modifier. The purpose of this document of the international series of standards on capability calculation is to assist the organizations to calculate the PCIs (process capability index) when geometrical product specifications are used on drawings.
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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.
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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.
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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.
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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.
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This International Standard gives a number of optimized test plans, the corresponding border lines and characteristics. In addition the algorithms for designing test plans using a spreadsheet program are also given, together with guidance on how to choose test plans.
This standard specifies procedures to test whether an observed value of
- failure rate,
- failure intensity,
- mean operating time to failure (MTTF),
- mean operating time between failures (MTBF),
conforms to a given requirement.
It is assumed, except where otherwise stated, that during the accumulated test time, the times to failure or the operating times between failures are independent and identically exponentially distributed. This assumption implies that the failure rate or failure intensity is assumed to be constant.
Four types of test plans are described as follows:
- truncated sequential probability ratio test (SPRT);
- fixed time/failure terminated test (FTFT);
- fixed calendar time terminated test without replacement;
- combined test.
This standard does not cover guidance on how to plan, perform, analyse and report a test. This information can be found in IEC 60300-3-5.
This standard does not describe test conditions. This information can be found in IEC 60605-2 and in IEC 60300-3-5.
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This International Standard gives a number of optimized test plans, the corresponding border lines and characteristics. In addition the algorithms for designing test plans using a spreadsheet program are also given, together with guidance on how to choose test plans. This standard specifies procedures to test whether an observed value of - failure rate, - failure intensity, - mean operating time to failure (MTTF), - mean operating time between failures (MTBF), conforms to a given requirement. It is assumed, except where otherwise stated, that during the accumulated test time, the times to failure or the operating times between failures are independent and identically exponentially distributed. This assumption implies that the failure rate or failure intensity is assumed to be constant. Four types of test plans are described as follows: - truncated sequential probability ratio test (SPRT); - fixed time/failure terminated test (FTFT); - fixed calendar time terminated test without replacement; - combined test. This standard does not cover guidance on how to plan, perform, analyse and report a test. This information can be found in IEC 60300-3-5. This standard does not describe test conditions. This information can be found in IEC 60605-2 and in IEC 60300-3-5.
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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.
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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.
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IEC 61124:2023 gives a number of optimized test plans, the corresponding border lines and characteristics. In addition, the algorithms for designing test plans using a spreadsheet program are also given, together with guidance on how to choose test plans.
This document specifies procedures to test whether an observed value of
failure rate,
failure intensity,
mean operating time to failure (MTTF),
mean operating time between failures (MTBF), conforms to a given requirement.
It is assumed, except where otherwise stated, that during the accumulated test time, the times to failure or the operating times between failures are independent and identically exponentially distributed. This assumption implies that the failure rate or failure intensity is assumed to be constant.
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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.
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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.
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IEC 61123:2019 is intended to define a procedure to verify if a reliability of an item/system complies with the stated requirements. The requirement is assumed to be specified as the percentage of success (success ratio) or the percentage of failures (failure ratio). This document can be used where a number of items are tested (number of trials performed) and classified as passed or failed. It can also be used where one or a number of items are tested repeatedly. The procedures are based on the assumption that the probability of success or failure is the same from trial to trial (statistically independent events). Plans for fixed trial/failure terminated tests as well as truncated sequential probability ratio tests (SPRTs) are included. This document contains extensive tables with ready-to-use SPRT plans and their characteristics for equal and non-equal risks for supplier and customer. In the case of the reliability compliance tests for constant failure rate/intensity, IEC 61124 applies. This second edition cancels and replaces the first edition published in 1991. This edition constitutes a technical revision. This edition includes the following significant technical changes with respect to the previous edition: The sequential probability ratio test (SPRT) [1, 2][1] has been significantly developed in recent years [3, 4, 5]. This edition contains shorter and accurate tests, a wide range of test plans, and significant additional characteristic data, as follows: the tests are significantly truncated (the maximum trial numbers are low) without substantially increasing the expected number of trials to decision (ENT); the true producer’s and consumer’s risks (α', β') are given and very close to the nominal (α, β); the range of the test parameters is wide (failure ratio, risks and discrimination ratio); the test plans include various risk ratios (not restricted to equal risks only); the values of ENT are accurate and given in the relevant region (for practical use); guidelines for extension of the test sets (interpolation and extrapolation) are included. In Annex C, the use of the cumulative binomial distribution function of Excel that simplifies the procedure of designing has been added (Clause C.3). Keywords: verify if a reliability of an item/system complies with the stated requirements
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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- Technical report38 pagesEnglish languagesale 15% off
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.
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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.
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- Standard50 pagesEnglish languagesale 15% off
IEC 60812:2018 explains how failure modes and effects analysis (FMEA), including the failure modes, effects and criticality analysis (FMECA) variant, is planned, performed, documented and maintained. The purpose of failure modes and effects analysis (FMEA) is to establish how items or processes might fail to perform their function so that any required treatments could be identified. An FMEA provides a systematic method for identifying modes of failure together with their effects on the item or process, both locally and globally. It may also include identifying the causes of failure modes. Failure modes can be prioritized to support decisions about treatment. Where the ranking of criticality involves at least the severity of consequences, and often other measures of importance, the analysis is known as failure modes, effects and criticality analysis (FMECA). This document is applicable to hardware, software, processes including human action, and their interfaces, in any combination. An FMEA can be used in a safety analysis, for regulatory and other purposes, but this being a generic standard, does not give specific guidance for safety applications. This third edition cancels and replaces the second edition published in 2006. This edition constitutes a technical revision.This edition includes the following significant technical changes with respect to the previous edition: a) the normative text is generic and covers all applications; b) examples of applications for safety, automotive, software and (service) processes have been added as informative annexes; c) tailoring the FMEA for different applications is described; d) different reporting formats are described, including a database information system; e) alternative means of calculating risk priority numbers (RPN) have been added; f) a criticality matrix based method has been added; g) the relationship to other dependability analysis methods have been described. Keywords: failure modes and effects analysis (FMEA), failure modes effects and criticality analysis (FMECA)
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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.
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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.
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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.
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This document gives guidelines for the selection of appropriate statistical techniques that can be useful
to an organization, irrespective of size or complexity, in developing, implementing, maintaining and
improving a quality management system in conformity with ISO 9001:2015.
This document does not provide guidance on how to use the statistical techniques.
- Standard36 pagesEnglish languagesale 10% offe-Library read for1 day
This document gives guidelines for the selection of appropriate statistical techniques that can be useful to an organization, irrespective of size or complexity, in developing, implementing, maintaining and improving a quality management system in conformity with ISO 9001:2015. This document does not provide guidance on how to use the statistical techniques.
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- Standard31 pagesEnglish, Spanish and Russian languagesale 15% off
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.
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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.
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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.
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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.
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This document describes the construction and applications of control charts for stationary processes.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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