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GB/T 43751-2024Rubber and rubber products - Guidance on the application of statistics to physical testing (English PDF)

橡胶与橡胶制品统计学在物理试验上的应用指南

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Issued by

State Administration for Market Regulation, China National Standardization Administration

Level / Type

National · Recommended

Issue date

March 15, 2024

Implementation date

October 1, 2024

Scope

GB/T 43751-2024 is the English-translated version of 橡胶与橡胶制品统计学在物理试验上的应用指南.

GB/T 43751-2024 — This document provides guidance on the application of statistics to rubber testing. This document is not intended to contradict or replace existing standards covering basic statistical methods, but rather to supplement them and provide Example of application of statistical methods in the field of rubber testing.

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Document preview — GB/T 43751-2024

National Standard of the People's Republic of China

ICS: 83.060
Classification: G 40

Issued by: State Administration for Market Regulation, China National Standardization Administration

Preface
Introduction
1 Scope
2 Normative references
3 Terms and Definitions
4 Symbols
5 Limitations of the trial results
5.1 Variability
5.2 Accuracy, trueness and precision
5.3 Correlation and significance
6 Distribution of results and measures of central tendency
6.1 Overview
6.2 Method
6.2.1 Types of distribution
6.2.2 Measures of central tendency
6.2.3 Discrete measures
6.2.4 Transformation to Normal Distribution
6.2.5 Tests for departures from normality
6.3 Application in rubber testing
6.3.1 Overview
6.3.2 Tensile test
6.3.3 Fatigue
6.3.4 Transformation to Normal Distribution
6.3.5 Other uses of the median
7 Confidence limits and significant differences
7.1 Overview
7.2 Method
7.2.1 Confidence Limits and Confidence Intervals
7.2.2 Significant Differences
7.3 Application in rubber testing
7.3.1 Overview
7.3.2 Confidence limits and indicator limits
7.3.3 Comparison of results
8 Sorting Method 29
8.1 Overview
8.2 Method
8.2.1 Friedman test
8.2.2 External counting inspection
8.3 Application in rubber testing
9 Criteria for Rejecting Outliers
9.1 Overview
9.2 Method
9.2.1 Overview
9.2.2 Dixon's test
9.2.3 Cochran's test
9.3 Application in rubber testing
9.3.1 Overview
9.3.2 Dixon's test applied to a single result
9.3.3 Cochran's variance test
9.3.4 Dixon's test applied to a set of means
10 Analysis of variance (ANOVA)
10.1 Overview
10.2 Method
10.2.1 Overview
10.2.2 Single Factor with the Same Number of Observations
10.2.3 Single Factor with Variable Number of Observations
10.2.4 Two-way (and multi-way) ANOVA
10.3 Application in rubber testing
11 Regression Analysis 42
11.1 Overview
11.2 Method
11.2.1 Overview
11.2.2 Linear Least Squares Method
11.2.3 Quadratic Least Squares
11.2.4 Cubic Least Squares
11.3 Application in rubber testing
11.3.1 Overview
11.3.2 Effect of temperature on compression set
11.3.3 Effect of aging on tensile strength
11.3.4 Temperature of the shrinkage test
12 Measurement uncertainty
12.1 Overview
12.2 Method
12.2.1 Overview
12.2.2 Establishment of measurement model
12.2.3 Evaluation of standard uncertainty
12.2.4 Combined standard uncertainty
12.2.5 Determination of expanded uncertainty
12.2.6 Reporting of measurement uncertainty
12.3 Application in Rubber Testing
13 Sampling
13.1 Overview
13.2 Method
13.2.1 Overview
13.2.2 Acceptance Quality Limit (AQL) and Limiting Quality (LQ)
13.2.3 Determination of non-conformity
13.2.4 Inspection level
13.2.5 Attribute sampling plans
13.2.6 Random Sampling
13.3 Application in Rubber Testing
14 Number of samples.
14.1 Principle
14.2 Method
14.3 Application in Rubber Testing
14.3.1 Overview
14.3.2 Optimization of confidence level
14.3.3 Optimization of pass/fail status
15 The result shows
15.1 Overview
15.2 Method
15.2.1 Test report
15.2.2 Numerical rounding to
15.3 Application in Rubber Testing
15.3.1 Overview
15.3.2 Constructing a Histogram
15.3.3 Rounding Example
16 Precision Statement
16.1 Overview
16.2 Method
16.3 Application in Rubber Testing
17 Experimental Design
17.1 Overview
17.1.1 General Information
17.1.2 Principle
17.2 Methods
17.2.1 Overview
17.2.2 Descriptive Experiments
17.2.3 Comparative Experiments
17.2.4 Response Experiment
17.3 Application in Rubber Testing
17.3.1 Descriptive Experiments
17.3.2 Comparative Experiment
17.3.3 Response Experiment
18 Statistical Quality Control
18.1 Overview
18.2 Method
18.2.1 Overview
18.2.2 Count Control Chart
18.2.3 Measurement control chart
18.3 Application in Rubber Testing
18.3.1 Overview
18.3.2 Control chart
18.3.3 Cumulative graph
Appendix A (Informative) Comparison of this document with ISO 19003:2006 structure numbers
Appendix B (Informative) Technical differences between this document and ISO 19003:2006 and their causes
Annex C (informative) Editorial changes to ISO 19003:2006
Appendix D (Informative) Other forms of mean
Appendix E (Informative) Mathematical forms of distribution functions cited in this document
Appendix F (informative) Correlation between measures of central tendency in the double exponential and Weibull distributions
Appendix G (Informative) Constructing Weibull Probability Paper
Appendix H (Informative) Analysis of Variance
Appendix I (Informative) Calculation of regression equation coefficients using Excel
References

Foreword

This document is in accordance with the provisions of GB/T 1.1-2020 "Guidelines for standardization work Part 1: Structure and drafting rules for standardization documents" Drafting.

This document is modified to adopt ISO 19003:2006 "Guide to the application of statistics to physical testing of rubber and rubber products".

Compared with ISO 19003:2006, this document has many structural adjustments. The structural number changes between the two documents are shown in the table below.

See Appendix A.

This document has many technical differences compared to ISO 19003:2006.

A single line (|) is used to indicate these technical differences. A list of these technical differences and their reasons is given in Appendix B.

This document has undergone a number of editorial changes compared to ISO 19003:2006.A list of these editorial changes and their reasons is given in Appendix C.

Introduction

Statistical methods play an important role in all stages of the experimental process, from the design of the experiment to the interpretation of the results.

Trial personnel need to have a basic understanding of statistical principles and knowledge of the statistical techniques required.

There are many textbooks and standards on statistical methods, but it is easy to find the most commonly used methods and formulas, and also consider other Guidance on the specific application of various rubber test methods is convenient. This document was prepared as a supplement to the statistical general standards and the standard complements both.

This document presents an overview, methods, and applications to rubber testing for each topic. Under Overview, basic concepts are outlined. Methods Consider the statistical techniques that can be used, giving the basic procedures and formulas. If applicable, provide additional information for less common methods or more advanced treatments.

"Application to rubber testing" refers to how and where these methods can be applied and gives specific information on rubber properties.

and experimental examples.

The term "rubber" in this document "Rubber Physical Tests" is broad in meaning and includes raw rubber, unvulcanized rubber, Adhesive and rubber products.

Statistics of rubber and rubber products in physical tests Application Guide

1 Scope

This document provides guidance on the application of statistics to rubber testing.

This document is not intended to contradict or replace existing standards covering basic statistical methods, but rather to supplement them and provide

Example of application of statistical methods in the field of rubber testing.

2 Normative references

This document has no normative references.

3 Terms and definitions

The following terms and definitions apply to this document.

Note. These terms, as far as possible, are expressed in non-mathematical terms and apply to the main statistical terms used. For more comprehensive and rigorous terms, see GB/T 3358 (all parts) and references dealing with professional statistical techniques.

Overall population

All data that can be obtained (theoretically) to characterize the properties of a test rubber, compound or process.

Sample

Data actually obtained from a population as a result of an implemented experimental test program.

Variability

The tendency for tests conducted on nominally identical specimens to produce different test results.

arithmetic mean

The total of the data (of a population or sample) divided by the number of values used.

Note. The average is the most common statistic used to describe a set of data. There are several types of averages, which are often used in common speech without specifying their type, which may be confusing.

There are two types of averages. calculation and positional. The arithmetic mean is the most commonly used calculation average result, and others are listed in Appendix D.

The positional average is the median and the mode. The calculation of the arithmetic mean is shown in formula (1) and formula (2) of 6.2.2.2.

median

The middle value (or the average of the two middle values) when the sample data are arranged in ascending order.

Mode

Performance test value that occurs at the maximum frequency.

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This preview omits tables, figures, formulas and parts of the technical clauses. The complete document — 108 pages — is available in the English PDF.

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