# ISO 3086-2006

Reference numberISO 3086:2006(E)©ISO 2006INTERNATIONAL STANDARD ISO3086Fourth edition2006-04-15Iron ores — Experimental methods for checking the bias of sampling Minerais de fer — Méthodes expérimentales de contrôle de l erreur systématique d échantillonnage ISO 3086:2006(E) PDF disclaimer This PDF file may contain embedded typefaces. In accordance with Adobe s licensing policy, this file may be printed or viewed but shall not be edited unless the typefaces which are embedded are licensed to and installed on the computer performing the editing. In downloading this file, parties accept therein the responsibility of not infringing Adobe s licensing policy. The ISO Central Secretariat accepts no liability in this area. Adobe is a trademark of Adobe Systems Incorporated. Details of the software products used to create this PDF file can be found in the General Info relative to the file; the PDF-creation parameters were optimized for printing. Every care has been taken to ensure that the file is suitable for use by ISO member bodies. In the unlikely event that a problem relating to it is found, please inform the Central Secretariat at the address given below. © ISO 2006 All rights reserved. Unless otherwise specified, no part of this publication may be reproduced or utilized in any form or by any means, electronic or mechanical, including photocopying and microfilm, without permission in writing from either ISO at the address below or ISO s member body in the country of the requester. ISO copyright office Case postale 56 • CH-1211 Geneva 20 Tel. + 41 22 749 01 11 Fax + 41 22 749 09 47 E-mail copyright@iso.org Web www.iso.org Published in Switzerland ii © ISO 2006 – All rights reservedISO 3086:2006(E) © ISO 2006 – All rights reserved iiiContents Page Foreword iv 1 Scope . 1 2 Normative references . 1 3 Terms and definitions. 1 4 Principle. 2 5 General conditions . 2 6 Sampling and sample preparation methods 2 6.1 Sampling 2 6.2 Sample preparation 2 7 Analysis of experimental data . 3 7.1 Computation of the differences. 3 7.2 Determination of the mean and the standard deviation of the differences 3 7.3 Test for outliers – Grubbs test 3 7.4 Selection of data for use in statistical test for bias. 5 7.4.1 Consideration of outliers whose causes are assignable 5 7.4.2 Consideration of outliers whose causes are not assignable. 5 7.4.3 Consideration of amount of data remaining 5 7.5 Statistical test for bias 5 7.5.1 Determination of the confidence interval for d 5 7.5.2 Interpretation of confidence interval 6 8 Test report . 7 Annex A (normative) Flowsheets of the statistical analysis 8 Annex B (informative) Numerical examples of experiments 11 ISO 3086:2006(E) iv © ISO 2006 – All rights reservedForeword ISO (the International Organization for Standardization) is a worldwide federation of national standards bodies (ISO member bodies). The work of preparing International Standards is normally carried out through ISO technical committees. Each member body interested in a subject for which a technical committee has been established has the right to be represented on that committee. International organizations, governmental and non-governmental, in liaison with ISO, also take part in the work. ISO collaborates closely with the International Electrotechnical Commission (IEC) on all matters of electrotechnical standardization. International Standards are drafted in accordance with the rules given in the ISO/IEC Directives, Part 2. The main task of technical committees is to prepare International Standards. Draft International Standards adopted by the technical committees are circulated to the member bodies for voting. Publication as an International Standard requires approval by at least 75 % of the member bodies casting a vote. Attention is drawn to the possibility that some of the elements of this document may be the subject of patent rights. ISO shall not be held responsible for identifying any or all such patent rights. ISO 3086 was prepared by Technical Committee ISO/TC 102, Iron ore and direct reduced iron, Subcommittee SC 1, Sampling. This fourth edition cancels and replaces the third edition (ISO 3086:1998), which has been technically revised. INTERNATIONAL STANDARD ISO 3086:2006(E)© ISO 2006 – All rights reserved 1Iron ores — Experimental methods for checking the bias of sampling 1 Scope This International Standard specifies experimental methods for checking the bias of sampling of iron ores, when sampling is carried out in accordance with the methods specified in ISO 3082, having as reference a stopped-belt sampling method. It is recommended that an inspection of the mechanical sampling system be carried out before conducting bias testing. Sampling systems not completely in accordance with ISO 3082 are not always expected to be biased. Therefore, bias checking may be done when there is some disagreement about the importance of some departure from the conditions of ISO 3082. If one party argues that the bias is likely to be substantial under some particular set of conditions then bias testing should mostly be done when those conditions apply. NOTE The method for analysis of experimental data described here may also be applied: a) for checking the bias of sample preparation of iron ores, having as reference the methods for sampling preparation according to ISO 3082; b) for checking the bias of size distribution of iron ores by sieving, having as reference the hand sieving methods according to ISO 4701; c) for checking a possibly significant difference in the results obtained from the samples of one lot collected at different places, for example, a loading point and unloading point. 2 Normative references The following referenced documents are indispensable for the application of this document. For dated references, only the edition cited applies. For undated references, the latest edition of the referenced document (including any amendments) applies. ISO 3082:2000, Iron ores — Sampling and sample preparation procedures ISO 3085:2002, Iron ores — Experimental methods for checking the precision of sampling, sample preparation and measurement ISO 11323:2002, Iron ore and direct reduced iron — Vocabulary 3 Terms and definitions For the purposes of this document, the terms and definitions given in ISO 11323 apply. --```,,,,``,,,,,,`,`,,`,,,`,,`,-`-`,,`,,`,`,,`---ISO 3086:2006(E) 2 © ISO 2006 – All rights reserved4 Principle The results obtained from the method to be checked (referred to as method B) are compared with the results of a reference method (referred to as method A) which is considered to produce practically unbiased results, from technical and empirical viewpoints. In the event of there being no significant difference, in a statistical sense, between the results obtained by method B and method A, method B may be adopted as a routine method. This difference is assessed by comparing a 90 % confidence interval for the true average bias with the relevant bias, δ (see 5.2). 5 General conditions 5.1 The number of paired sets of measurement shall not be less than ten. The number of further tests required depends on the results of the outlier test and of the statistical analysis of the confidence interval for the true average bias, based on at least ten paired sets. NOTE A paired set of measurement is a paired measurement data of samples, which are sampled by methods A and B, and prepared and measured in the same way, for identical material. 5.2 The relevant bias, δ, which is considered large enough to justify the likely expense of reducing the average bias, shall be decided beforehand. As a guide, δ is likely to be less than σSPM, the standard deviation for sampling, sample preparation and measurement, determined according to ISO 3085. NOTE If the experiment is aimed at checking sample preparation only, the value of δ is likely to be less than σPM, determined according to ISO 3085. 5.3 Quality characteristics, such as total iron content, moisture content, size distribution and physical properties, may be used. 6 Sampling and sample preparation methods 6.1 Sampling The reference method, method A, for checking the bias of sampling is a stopped-belt sampling method in accordance with ISO 3082. Method A: take each increment from the full width and thickness of the ore stream on the stopped conveyor at a specified place, for a length of belt more than three times the nominal top size or 30 mm, whichever is the greater. The method to be checked, method B, carried out according to ISO 3082 as far as possible, shall be compared with method A for the same material. Method B: sampling methods, such as sampling from moving conveyors with a mechanical sampler and sampling during the transfer to or from ships and wagons, are examples of method B. Samples from Methods A and B shall be taken as close together as possible. This is particularly important for ore streams which are known to be variable. 6.2 Sample preparation 6.2.1 Increments obtained from one lot, in accordance with methods A and B, are made up into two gross samples, A and B. ISO 3086:2006(E) © ISO 2006 – All rights reserved 36.2.2 The gross samples, A and B, are subjected, in the same manner, to sample preparation as specified in ISO 3082, and tested as specified in the relevant International Standards separately, and a pair of measurements obtained. 6.2.3 The above procedure is performed on ten or more lots (see 5.1). When increments for methods A and B can be taken from closely adjacent portions of the ore, it is recommended that sample preparation and testing be carried out on individual increments or on combinations of a small number of adjacent increments. This allows comparisons of ten or more pairs of measurements to be made more quickly than if measurements were only made on entire lots. The above comparison of measurements should be made on pairs of increments taken from several lots, preferably of the same type of ore. However, it is not permitted to combine a number of paired results, originating from both increments and gross samples. It should be either a number of pairs from increments or from gross samples. NOTE Given the cost and inconvenience of stopped-belt sampling, it is generally economic to conduct sample preparation and measurement in duplicate and with great care so that the number of stopped-belt samples might be reduced. 7 Analysis of experimental data NOTE The procedures described in 7.1 to 7.5 are also shown in the form of a flowsheet in Annex A (normative). 7.1 Computation of the differences 7.1.1 Denote measurements obtained in accordance with methods A and B, by xAiand xBi, respectively. When sampling preparation and measurement have been conducted in duplicate, these measurements will be averaged. 7.1.2 Calculate the difference, di, between xAiand xBiusing the equation: BA1, 2, .iiidx x i k=− = (1) where k is the number of paired sets of measurements. 7.2 Determination of the mean and the standard deviation of the differences 7.2.1 Calculate the mean of the differences, ,d with one decimal place more than that used in the measurements themselves: 1iddk=∑(2) 7.2.2 Calculate the sum of squares, SSd, and the standard deviation of the differences, Sd, with one decimal place more than that used in the measurements themselves: ()221SSdi iddk=−∑∑(3) SS(1)ddSk=−(4) 7.3 Test for outliers – Grubbs test 7.3.1 Sort diinto ascending order. ISO 3086:2006(E) 4 © ISO 2006 – All rights reserved7.3.2 Calculate the Grubbs’ test statistics Gkand G1, using the following equations: kkdddGS−= (5) 11dddGS−= (6) where dkis the largest value of di; d1is the smallest value of di; 7.3.3 Choose the larger of Gkand G1. 7.3.4 Compare the larger of Gkand G1with the critical value for Grubbs test at the 5 % significance level according to Table 1. Table 1 — Critical values for Grubbs outlier test k Critical value (5 %) k Critical value(5 %) k Critical value (5 %) 6 1,887 12 2,412 18 2,651 7 2,020 13 2,462 19 2,681 8 2,126 14 2,507 20 2,709 9 2,215 15 2,549 21 2,733 10 2,290 16 2,585 22 2,758 11 2,355 17 2,620 23 2,781 NOTE Critical values for Grubbs’ test for a wider range of numbers of observations, and for additional significance levels, are given in Grubbs, F. E. and Beck, G. (1972) Extension of sample sizes and percentage points for significance tests of outlying observations, Technometrics 14, pp. 847-854. 7.3.4.1 If the larger of Gkand G1is less than or equal to the critical value, conclude that there is no outlier. Proceed with 7.5. 7.3.4.2 If the larger of Gkand G1is larger than the critical value: 7.3.4.2.1 If the larger is Gk, conclude that the largest value of the difference, dk, is an outlier. 7.3.4.2.2 If the larger is G1, conclude that the smallest value of the difference, d1, is an outlier. 7.3.5 Exclude the outlier di, repeat the procedure described in 7.2 to 7.3.3. 7.3.6 Compare the larger of Gkand G1with the critical value for Grubbs test at 5 % significance level according to Table 1. 7.3.6.1 If the larger of Gkand G1is less than or equal to the critical value, conclude that there is no outlier and proceed with 7.4. ISO 3086:2006(E) © ISO 2006 – All rights reserved 57.3.6.2 If the larger of Gkand G1is larger than the critical value: 7.3.6.2.1 If the larger is Gk, conclude that the largest value of the difference, dk, is an outlier. 7.3.6.2.2 If the larger is G1, conclude that the smallest value of the difference, d1, is an outlier. 7.3.7 If at least 60 % of the initial set of data remain, proceed with 7.3.5. 7.3.8 If not, stop the outlier test, reinstate all outliers and proceed with 7.5. 7.4 Selection of data for use in statistical test for bias 7.4.1 Consideration of outliers whose causes are assignable Once outliers have been detected by Grubbs test, consideration should be given to assignable causes for those outliers, such as change in the level of moisture, partial blockage of a cutter opening, or changes in characteristics of the material being sampled. For each outlier whose cause can be determined with reasonable confidence: If the cause is likely to occur in the future then reinstate the outlier, but if the cause is not likely to occur in the future then exclude the outlier. 7.4.2 Consideration of outliers whose causes are not assignable If the cause of an outlier could not be determined with reasonable confidence then the outlier should be excluded. 7.4.3 Consideration of amount of data remaining If at least 10 paired sets of measurements remain, proceed with 7.5. If not, carry out more sampling and testing to complete at least 10 paired sets of measurements, reinstate the outliers excluded, except those which have an assignable cause and are not likely to occur in the future, and repeat 7.1 to 7.4 since differences previously classified as outliers may or may not be found to be outliers when Grubbs test is applied to the larger set of data. 7.5 Statistical test for bias 7.5.1 Determination of the confidence interval for d 7.5.1.1 Calcu