ISO 7870-7:2020
Control charts — Part 7: Multivariate control charts
Control charts — Part 7: Multivariate control charts
- Статус документа:
- Действующий
- Формат:
- Электронный (PDF)
- Количество страниц:
- 25
- Дата публикации:
- 5 февраля 2020 г.
- Издание:
- ISO IS 7870 edition 1 version 1
- ICS:
- 03.120.30
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.
Abstract
Overview
ISO 7870-7:2020 - Control charts - Part 7: Multivariate control charts specifies how to construct and use multivariate control charts within statistical process control (SPC). The standard presents practical, state-of-the-art methods for monitoring several related quality characteristics simultaneously (multivariate statistical process control, MSPC). It focuses on control-chart design, limits and interpretation for vector-valued measurements (mean vector and covariance matrix), and gives worked examples and estimation guidance. Note: the use of PCA and PLS for MSPC is explicitly excluded from this document.
Key topics and technical requirements
- Purpose and applying conditions for multivariate control charts, including when variables are correlated and why univariate charts can be misleading.
- Classification of multivariate charts and guidance for selecting an appropriate charting method.
- Charts for monitoring the process mean:
- Procedures for subgroup size n > 1 and n = 1.
- χ control charts (when pre-specified parameter values are known).
- T control charts (when pre-specified parameter values are unknown).
- Multivariate EWMA / MEWMA (multivariate exponential weighted moving average) methods and selection of weighting parameters.
- Control charts for process dispersion and tests for assignable causes.
- Interpretation of out-of-control signals and recommended follow-up actions.
- Annexes with practical examples (MSPC example, MEWMA example) and an annex on estimation of μ (mean vector) and Σ (covariance matrix).
- Definitions, symbols and abbreviations (SPC, MSPC, EWMA, MEWMA, UCL/LCL, ARL) and normative reference to ISO 3534-2 (statistics vocabulary).
Practical applications
- Monitoring processes where multiple correlated quality characteristics must be controlled simultaneously (e.g., chemical processes, semiconductor manufacturing, multi-attribute inspection).
- Detecting multivariate mean shifts and dispersion changes while accounting for covariance between variables to reduce false alarms.
- Implementing MSPC modules in SPC software and quality management systems.
- Supporting process capability assessments for multivariate distributions (in conjunction with related standards).
Who should use this standard
- Quality engineers, process engineers and statisticians implementing SPC for multidimensional measurements.
- Software developers and data scientists building MSPC tools and dashboards.
- Auditors and compliance professionals assessing multivariate control procedures in manufacturing and process industries.
Related standards
- ISO 3534-2: vocabulary and symbols for applied statistics (normative reference).
- ISO 22514-6: methods for capability statistics for multivariate distributions (complementary guidance).
Keywords: ISO 7870-7, multivariate control charts, statistical process control, MSPC, MEWMA, EWMA, T control chart, χ control chart, covariance matrix, process monitoring, quality control.
Технические детали
- Технический комитет
- ISO/TC 69/SC 4 - Applications of statistical methods in product and process management
- SKU
- ISO 7870-7:2020
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