ISO 5725-5 PDF

ISO 英文 – INTERNATIONAL STANDARD IS0 TECHNICAL CORRIGENDUM 1 Published ISO Accuracy (Trueness and Precision) of Measurement Methods and Results – Part 5: Alternative Methods for the Determination of the Precision of a. Find the most up-to-date version of ISO at Engineering

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This is a small difference, so table 1 and figures B.

If outliers are present in the data then these will inflate the denominators and produce a distorted effect in the graphs of the statistics. If a laboratory is achieving poor repeatability then it will give unusually large k statistics in the graph that is derived from the be?

It provides a convenient method 57255-5 applying robust analysis to precision experiments with more than two factors such as the design for a heterogeneous material in clause 5 57725-5 this part of IS0and the staggered-nested designs of IS0 The approach that is used in the examples that follow is to use the iterative method to find an approximate solution, then solve equation 68 to find the exact solution.

They are used to identify results that are so inconsistent with the remainder of the data reported in the experiment that their inclusion in the calculation of the repeaiability and reproducibility standard deviations would affect the values of these statistics substantially.

B informative Derivation of the factors used in algorithms A 572-55 S The two samples within a level are denoted U and 6,where a represents a sample of one material, and b represents a sample of the other, similar, material. It should be noted, however, that they provide isl means of combining, in a robust manner, cell averages, cell standard deviations and cell ranges. In an experiment on a heterogeneous material, the results of applying these tests should be acted on in the following order.

Degrees of freedom V 1 2 3 4 5 6 Limit factor iI 1, 1, Adjustment factor 5 1, 1. These are given in table 8. With the notation as set out in 6. The ISO Accuracy of Measurement Methods and Results Package provides the general principles necessary to accurately assess measurement methods, results, applications and practical estimations.


Figure 7 shows consistent positive or negative h statistics in most laboratories with Laboratories 1, 6 and 10 again achieving the largest values. Robust analysis for a particular level of a split-level design Click to learn more. Obtain the values of 5 and q required by the algorithm from table Between-sample ranges for Level 6 Between-sample Table 16 -Example 2: An experiment on a heterogeneous material There were nine participating laboratories, and the experiment contained 14 levels.

Equation 67 in 6. The analysis would then continue with an investigation of possible functional relationships between the repeatability and reproducibility standard deviations and the general average. The formulae presented in 575-5.

Figure 2 does not reveal any noteworthy pattern. The use of robust estimates of the standard deviations as the denominators in the h and k statistics, and of robust estimates of the overall averages in the calculation of the h statistics, avoids this distortion.

To check the consistency of the between-sample ranges, calculate the k statistics as: Alternative methods for the determination of the precision of a standard measurement method Part 6: Formulae for calculating values for the repeatability and reproducibility standard deviations for the general design are given below in 5.

The p participating laboratories are each provided with two samples at q levels, and obtain two test results on each sample.

BS ISO 5725-5:1998

The formulae given in 5. Initially the test portion is prepared so that it is all retained on a 572-5 sieve. Find Similar Items This product falls into the following categories. It is reasonable to assume that the variation between samples is random, does not depend on the laboratory, but may depend on the level of the experiment, so the term Hiil has a zero expectation, and a variance: Royal Society of Chemistry, London. Calculation of the sum of squares for samples i 1 Sum of squares for Degrees of freedom for samples: Uso first verify your email before subscribing to alerts.

5725- Analyst,pp. Cell averages for Level 6 Cell average 57725-5 In the more general design, g or n or both are greater than two. The first term on the right-handside of equation 8. The sum of squares for repeatability with summation over i ,r and k: In concrete technology the particle site distribution of sand is measured by sieve testing e.


A method that is used to measure their ability to do this is the magnesium sulfate soundness test [21, in which a test portion of aggregate is subjected to a number of cycles of soaking in saturated magnesium sulfate solution, followed by drying.

This is a simple method to program on a computer.

ISO Accuracy of Measurement Methods and Results Package

A split-level experiment – Determination of protein which involved the determination by combustion of the 4. The robust methods described in this clause allow the data to be analysed in such a way that it is not required to make decisions that affect the results of the calculations.

If data are rejected, recalculate the statistics. Robust analysis for a particular level of an experiment on a heterogeneous material Biometrika Tables for the chi-squared distribution give the values of q shown in table 23 of this part of IS0 The basic method requires the preparation of a number of identical samples of the material isl use in the experiment. Each combination of a laboratory and a level gives a “cell” in this table, containing two items of data, yiia and ygb.

Level 57725-5 in that example is of particular interest because Laboratory 1 gave a cell average that was shown to be a near-straggler by Grubbs’ test, and Laboratory 6 gave a cell range that was shown to be a nearstraggler by Cochran’s test. Such graphs can help identify those laboratories that have the largest biases relative to the other laboratories. This standard is also available to be included in Standards Subscriptions.

E The repeatability standard aviation srj, between-samples standard deviation sW, between-laboratory standard deviation sLp and reproducibility standard deviation sR using: