Download ASTM E DOWNLOAD PDF - KB. Share Embed Donate. Report this link Designation: E – An American. pdf download toolmalls org, astm e madcad com, inter laboratory test planning astm e pdf jacketswinkel com, astm e 08 standard practice for . astm e 16 standard no, astm e epub download jacketswinkel com, astm astm e pdfsdocuments2 com, astm e pdf geowoodstock info.
|Language:||English, Dutch, Arabic|
|Genre:||Politics & Laws|
|ePub File Size:||16.72 MB|
|PDF File Size:||13.60 MB|
|Distribution:||Free* [*Registration Required]|
Home; ASTM E standard by ASTM International, 04/01/ View all Printed Edition + PDF;; Immediate download; $; Add to Cart. PDF | Analysis of inter laboratory performance of X-ray fluorescence analysis eleven analyses from hydraulic cements based upon ASTM E Download full-text PDF. Content uploaded by Paul Stutzman. Author content. All content in this. Generate the tables for an interlab analysis as described by the ASTM E - 99 the Precision of a Test Method", ASTM International, Barr Harbor Drive.
Some would have had worse levels of variation than others and no lab can assume it automatically would perform like any other lab.
Standard Practice for
The second item reported, reproducibility, is partially the result of relative biases among the participating labs. For these reasons, Section A22 of Form and Style for ASTM Standards interprets uncertainty to be exclusively the responsibility of a given lab and that estimates from an interlaboratory study do not necessarily describe how a given method would behave in a particular lab.
One way of viewing the difference in associating uncertainty in metrological measurements versus testing is how calibration is considered.
For metrological measurements, the evaluation of uncertainty applies to the instrument through the calibration process that does not necessarily address the myriad of factors that can influence the measurement.
It is, however, expected that the lab shall incorporate those possible influences through the development of an uncertainty budget. To some extent such contributions to uncertainty may be estimated through actual measurements. For some discussion, see for example, the guide for reporting uncertainty of test results and use of the term measurement uncertainty in ASTM test methods E Calibration involving a traceable system does not apply to many ASTM test methods, since there are very rarely any true reference standards.
Perhaps even more important is that the individual operators and environments are not formally a part of the process. As much as we would like to predict and model the way a test method is undertaken, the reality is that it is essential to recognize that each test environment must develop and monitor its own practices and use the facts so accumulated.
A recent series of studies involved a new standard for use of various Vernier calipers to measure the width of sheet materials. In one case a series of measurements were taken on a fixed set of different size materials, using a single set of calipers, by a number of operators in the same facility.
Significant differences in the results by operator were revealed on all materials and instruments. Give instructions on the number of significant digits to be recorded, usually one more, if possible, than required by the test method. Also, supply test result sheets on which test results can be calculated and reported. In many instances this can be combined with the raw data sheet.
Specify the number of significant digits to be reported, usually two more than required by the test method. Request the laboratories send raw data and test result sheets as soon as the testing is completed, and at least weekly if testing will continue over several weeks. This record, to be sent to the ILS coordinator, will provide a valuable source of information both in dealing with unusual data and in making improvements in the test method in future revisions.
NOTE 1It may be convenient to use established reference materials, since their homogeneity has been demonstrated. Number of Test Results per Material In many cases, the standard deviation in question will be a function of the property level being measured.
When this occurs, the standard deviation should be determined separately for each level.
It is generally sound to limit the number of test results on each material in each laboratory to a small number, such as three or four. E 05 If the task group has decided to intermingle test units from different materials in the order of testing, the testing should not start until all the test units have arrived at the laboratory so they can be tested in the specified order.
The laboratory ILS supervisor should discuss this with the ILS coordinator, who may send a replacement set of test units, replace the misused test units, or do nothing, as may seem desirable. By comparing the progress of all laboratories, the coordinator can determine whether some laboratories are lagging considerably behind the others and so advise these laboratories.
Replacement sets of test units or of specific test units may be sent when there is missing or obviously erroneous data. The task group can decide later whether or not the additional data should be used in the estimation of the precision of the test method.
Looking for other ways to read this?
Also obtain any other information that may be needed in preparing the final research report on the ILS see Footnote 3. The results of this pilot run also give the task group an indication of how well each laboratory will perform in terms of promptness and following the protocol.
Laboratories with poor performance should be encouraged and helped to take corrective action. Calculation of the Statistics The statistical analysis of the data for estimates of the precision statistics is simply a one-way analysis of variance within- and between-laboratories carried out separately for each level material.
Since such an analysis can be invalidated by the presence of severe outliers, it is necessary to first examine the consistency of the data.
Dependence of Precision on Analyte Concentration One universal feature of data derived from analytical chemistry measurements is non-constant error variance. Error standard deviation in analytical chemistry has been demonstrated by Horwitz Horwitz, Kamps and Boyer, ; Horwitz, to be reasonably approximated by a power law over a wide range 6 orders of magnitude of concentrations.
This has been demonstrated in data from thousands of collaborative trials involving all analytical technologies and matrices that are found in food, pharmaceutical and environmental analysis. Based on a large set of collaborative trials, each with enough data to estimate the exponent in the power law, the estimates of its value tend to be near 0. Therefore, the error standard deviation in analytical chemistry tends to be an increasing function of concentration that increases more slowly than a constant coefficient of variation would indicate.
ILS: Interlaboratory Study
As a consequence of this, control samples which have different concentrations must be charted separately. There are however, cases in which the expected concentration range for a specific application of an analytical method is sufficiently narrow that constant error standard deviation can be a useful approximation.
However, even at a fixed concentration, a minor modification to something as simple as sample prep can change the error variance.In addition, a PC software package for Windows 3. If the randomization and distribution of individual test specimens rather than test units does not conflict with the procedure for preparing the sample for test, as specified in the test method, greater homogeneity between test units can be achieved by randomizing test specimens.
Also obtain any other information that may be needed in preparing the final research report on the ILS see Footnote 3.
Significant differences in the results by operator were revealed on all materials and instruments.
For some discussion, see for example, the guide for reporting uncertainty of test results and use of the term measurement uncertainty in ASTM test methods E The key term here is monitoring. One way of viewing the difference in associating uncertainty in metrological measurements versus testing is how calibration is considered. The ruggedness test see 8. The following paragraphs show, in terms of a numerical example, how the entire program is carried out: Full Scale Run