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本文(ASTM D7372-2012 8750 Standard Guide for Analysis and Interpretation of Proficiency Test Program Results《熟练试验程序结果的分析和说明用标准指南》.pdf)为本站会员(bowdiet140)主动上传,麦多课文库仅提供信息存储空间,仅对用户上传内容的表现方式做保护处理,对上载内容本身不做任何修改或编辑。 若此文所含内容侵犯了您的版权或隐私,请立即通知麦多课文库(发送邮件至master@mydoc123.com或直接QQ联系客服),我们立即给予删除!

ASTM D7372-2012 8750 Standard Guide for Analysis and Interpretation of Proficiency Test Program Results《熟练试验程序结果的分析和说明用标准指南》.pdf

1、Designation: D7372 12An American National StandardStandard Guide forAnalysis and Interpretation of Proficiency Test ProgramResults1This standard is issued under the fixed designation D7372; the number immediately following the designation indicates the year oforiginal adoption or, in the case of rev

2、ision, the year of last revision. A number in parentheses indicates the year of last reapproval. Asuperscript epsilon () indicates an editorial change since the last revision or reapproval.1. Scope*1.1 This guide covers the analysis and interpretation ofproficiency test (PT) program results. For par

3、ticipants ininterlaboratory proficiency test (PT) (or crosscheck, checkscheme, etc.) programs, this guide describes procedures forassessing participants results relative to the PT programresults and potentially improving the laboratorys testingperformance based on the assessment findings and insight

4、s. Forthe committees responsible for the test methods included ininterlaboratory proficiency testing programs, this guide de-scribes procedures for assessing industrys ability to performtest methods and for potentially identifying needs for methodimprovement.1.2 This standard does not purport to add

5、ress all of thesafety concerns, if any, associated with its use. It is theresponsibility of the user of this standard to establish appro-priate safety and health practices and determine the applica-bility of regulatory limitations prior to use.2. Referenced Documents2.1 ASTM Standards:2D1266 Test Me

6、thod for Sulfur in Petroleum Products(Lamp Method)D2622 Test Method for Sulfur in Petroleum Products byWavelength Dispersive X-ray Fluorescence SpectrometryD4294 Test Method for Sulfur in Petroleum and PetroleumProducts by Energy Dispersive X-ray Fluorescence Spec-trometryD4951 Test Method for Deter

7、mination of Additive Ele-ments in Lubricating Oils by Inductively Coupled PlasmaAtomic Emission SpectrometryD5185 Test Method for Determination of Additive Ele-ments, Wear Metals, and Contaminants in Used Lubricat-ing Oils and Determination of Selected Elements in BaseOils by Inductively Coupled Pla

8、sma Atomic EmissionSpectrometry (ICP-AES)D5453 Test Method for Determination of Total Sulfur inLight Hydrocarbons, Spark Ignition Engine Fuel, DieselEngine Fuel, and Engine Oil by Ultraviolet FluorescenceD6259 Practice for Determination of a Pooled Limit ofQuantitationD6299 Practice for Applying Sta

9、tistical Quality Assuranceand Control Charting Techniques to Evaluate AnalyticalMeasurement System PerformanceD6617 Practice for Laboratory Bias Detection Using SingleTest Result from Standard MaterialD6792 Practice for Quality System in Petroleum Productsand Lubricants Testing LaboratoriesD7039 Tes

10、t Method for Sulfur in Gasoline and Diesel Fuelby Monochromatic Wavelength Dispersive X-ray Fluores-cence SpectrometryE177 Practice for Use of the Terms Precision and Bias inASTM Test MethodsE456 Terminology Relating to Quality and StatisticsE2655 Guide for Reporting Uncertainty of Test Results andU

11、se of the Term Measurement Uncertainty in ASTM TestMethods3. Terminology3.1 Definitions:3.1.1 accuracy, ncloseness of agreement between anobserved value and an accepted reference value. E177, E4563.1.2 assignable cause, nfactor that contributes to varia-tion and that is feasible to detect and identi

12、fy. E4563.1.3 bias, nsystematic error that contributes to the dif-ference between a population mean of the measurements or testresults and an accepted reference or true value. E177, E4563.1.4 control limits, nlimits on a control chart that areused as criteria for signaling the need for action or for

13、 judgingwhether a set of data does or does not indicate a state ofstatistical control. E4561This guide is under the jurisdiction of ASTM Committee D02 on PetroleumProducts and Lubricants and is the direct responsibility of Subcommittee D02.94 onCoordinating Subcommittee on Quality Assurance and Stat

14、istics.Current edition approved April 15, 2012. Published October 2012. Originallyapproved in 2007. Last previous edition approved in 2007 as D737207. DOI:10.1520/D7372-12.2For referenced ASTM standards, visit the ASTM website, www.astm.org, orcontact ASTM Customer Service at serviceastm.org. For An

15、nual Book of ASTMStandards volume information, refer to the standards Document Summary page onthe ASTM website.1*A Summary of Changes section appears at the end of this standard.Copyright ASTM International, 100 Barr Harbor Drive, PO Box C700, West Conshohocken, PA 19428-2959, United States.3.1.5 in

16、-statistical-control, adjprocess, analytical mea-surement system, or function that exhibits variations that canonly be attributable to common cause. D62993.1.6 Interlaboratory Crosscheck Program (ILCP),nASTM International Proficiency Test Program sponsoredby Committee D02 on Petroleum Products and L

17、ubricants, seeASTM website for current details.3.1.7 proficiency testing, ndetermination of a laboratorystesting capability by participation in an interlaboratory cross-check program D62993.1.8 uncertainty, nan indication of the magnitude oferror associated with a value that takes into account boths

18、ystematic errors and random errors associated with the mea-surement or test process. E26553.1.9 Z-score, nstandardized and dimensionless measureof the difference between an individual result in a data set andthe arithmetic mean of the dataset, re-expressed in units ofstandard deviation of the datase

19、t (by dividing the actualdifference from the mean by the standard deviation for the dataset). D62993.1.10 Z-score, nmeasure similar to the Z-score exceptthat the PT program standard deviation is replaced with onethat takes into account the site precision of the laboratory. Z isa valid approach when

20、the laboratorys site precision standarddeviation is less than the PT program (that is, these datastandard deviation) or stated otherwise when the TPI 1.Z8 5Xi X!Ss8!21 Ssthese data2nDDwhere:Z = site precision adjusted Z-Score,Xi= laboratorys result,X = PT average value,s = site precision standard de

21、viation estimate,andsthese data= PT Program standard deviation estimate.3.2 Definitions of Terms Specific to This Standard:3.2.1 common (chance, random) cause, nfor quality as-surance programs, one of generally numerous factors, individu-ally of relatively small importance, that contributes to varia

22、-tion, and that is not feasible to detect or control. D62993.2.2 site precision (R), nvalue below which the absolutedifference between two individual test results obtained undersite precision conditions may be expected to occur with aprobability of approximately 0.95 (95 %). It is defined as 2.77tim

23、es the standard deviation of results obtained under siteprecision conditions. D62993.2.3 site precision conditions, nconditions under whichtest results are obtained by one or more operators in a singlesite location practicing the same test method on a singlemeasurement system which may comprise mult

24、iple instru-ments, using test specimens taken at random from the samesample of material, over an extended period of time spanningat least a 15-day interval. D62993.2.4 these test data, nterm used by the ASTM Interna-tional D02 PT program to identify statistical results calculatedfrom the data submit

25、ted by program participants.3.3 Symbols:3.3.1 Iindividual observation (as in I-chart).3.3.2 QCquality control.3.3.3 Rsite precision.4. Summary of Guide4.1 Petroleum and petroleum product samples are regularlyanalyzed by specified standard test methods as part of aproficiency test program. This guide

26、 provides a laboratory withthe tools and procedures for evaluating their results from thePT program. Techniques are presented to screen, plot, andinterpret test results in accordance with industry-acceptedpractices.5. Significance and Use5.1 This guide can be used to evaluate the performance of alab

27、oratory or group of laboratories participating in an inter-laboratory proficiency test (PT) program involving petroleumand petroleum products.5.2 Data accrued, using the techniques included in thisguide, provide the ability to monitor analytical measurementsystem precision and bias. These data are u

28、seful for updatingstandard test methods, as well as for indicating areas ofpotential measurement system improvement for action by thelaboratory. This guide serves both the individual participatinglaboratory and the responsible standards development group asfollows:5.2.1 Tools and Approaches for Part

29、icipating Laboratories.Administrative ReviewsFlagged Data and InvestigationsData Normality ChecksHistogramsBias (Deviation from Mean)Z-ScoresTPI (Industry)PTP and Site Precision Comparisons5.2.2 Tools and Approaches for Responsible Standards De-velopment Groups.TPI and precision trendsBias via box p

30、articipants shouldexercise caution in planning actions for flagged dataAD 1 this is strong evidence of inadequate variation in the dataset due toinadequate numerical resolution (Could also arise from un-removedoutliers or a perversely non-normal data distribution)6.3.2 In addition, graphical tools a

31、re available for evaluatingnormality. For example, use a normal probability or a q-q plot(an equivalent plot to the normal probability plot) to visuallyassess the validity of the normality assumption. Refer toPractice D6299 for guidance regarding the preparation andinterpretation of normal probabili

32、ty plots and correspondingAD statistics. If data are normally distributed, the normalprobability plot should be approximately linear. Major devia-tions from linearity are an indication of nonnormal distribu-tions. The appearance of a series of steps in the plotted datarather than a smooth line is an

33、 indication that the data (ormeasurement) resolution is too coarse relative to the precisionof the test method. A few examples of these normal probabilityplots are shown in parallel with histograms in X3.1.6.4 Histograms:6.4.1 Plotting PT data as histograms is a useful graphicaltool for viewing data

34、 distribution and variability. The ILCPprogram plots histograms for all data sets where n 20; andincludes the mean and the 1st and 99th percentile limits on thehistogram for data sets with n 30. These limits are based on“median 6 2.33 Robust Standard Deviation,” where 62.33 arerespectively the first

35、 and 99th percentiles of the standardnormal distribution.6.4.2 PT participants should review histograms when avail-able and note unusual data distributions. Participants shouldlocate where their result falls within the histogram bins.Depending on the histogram, the location of data in certain binsco

36、uld indicate a potential issue such as bias. Consider review-ing the histogram in parallel with corresponding statistics suchas the Z-score, AD statistic, TPI (Industry) and the normalprobability (or deviate) plot. See X3.1 for examples.6.5 Bias (Deviation from Mean):6.5.1 As mentioned in Practice D

37、6299, subsection 7.6,evaluate proficiency test results by plotting the signed devia-tions from the mean for each result for each test cycle. PracticeD6299 suggests plotting the signed deviations from the con-sensus value (robust mean) on control charts. Laboratorieswould then apply the run rule stra

38、tegy outlined in that standardto identify outliers and other issues such as long-term biases.The recommended control chart is a chart of individualobservations (called an I-Chart) with an exponentiallyweighted moving average (EWMA) overlaid on the data. SeeX3.2 for examples.D7372 1236.5.2 Another gr

39、aphical approach for monitoring bias in-volves use of Box and Whisker graphs. As is the case forreviewing histograms, laboratories should use the Box andWhisker graphs to observe where their particular result lies inthe graph relative to the general distribution of results for thetest method they us

40、ed. Consider investigating any data outsidethe whisker end, if those data were not flagged already forother causes.Areview of the apparent distribution of results foreach test method measuring the same parameter may providevaluable insight regarding overall biases between methods. See7.2 for more in

41、formation on box and whisker plots.6.5.3 Another statistical approach for evaluating bias isdescribed in D6617. This guide estimates whether or not asingle test result is biased compared to the consensus valuefrom the PT program.6.6 Z-scoreThe Z-score calculated for each datum sub-mitted by the labo

42、ratory should be reviewed with respect to thefollowing:6.6.1 Sign and Magnitude of Z-scoreThe sign (that is, “+”or “”) of the statistic reflects the relative bias of the individualresult versus the mean of the sample group. Z-score valuesfalling in the ranges of plus or minus 0-1, 1 to 2, 2 to 3, an

43、d 3can be compared to control chart values falling in the rangesbetween the mean and 1-sigma, 1 to 2-sigma, 2 to 3-sigma, and 3-sigma. For normally distributed data, there is an expecta-tion that about 68% of the data will lie in the -1 sigma to +1sigma range, about 95% in the -2 sigma to +2 sigma r

44、ange, and99% in the -3 to +3 sigma range. The further a laboratorysZ-score is from zero, the greater the relative bias and lower theprobability that the data is considered within statistical control.Conduct investigations to determine the cause of any perceivedbias as needed.6.6.2 Trend of Z-scores

45、from Previous RoundsRecord theZ-score values for each test method (parameter) for successivePT program rounds on a control chart to show the trend overtime. The lab can use the run rules promulgated in PracticeD6299 to evaluate any observed trends. Conduct investigationsto determine causes as needed

46、. The ILCP uses the PrecisionIndicator (PI) statistic (ratio of the Pooled Z-score StandardDeviation to the average Z-score standard deviation for a givenlaboratory) to assist laboratories in assessing Z-scores. TheILCP program team also adopted PI = 0.8 as the critical valuefor taking action. If th

47、e resulting calculation produces a PI 3 (or 1.2 The performance of the group providing data is probably satisfactoryrelative to the corresponding ASTM published precision.0.8 to 1.2 The performance of the group providing data may be marginal andeach laboratory should consider reviewing the test meth

48、odprocedures to identify opportunities for improvement.1.0.7. ProcedureAnalysis and Interpretation by StandardsDevelopment Group7.1 This section covers the analysis and interpretation ofproficiency test data by a committee or working group chargedwith determining the overall implications that the pu

49、blishedresults have with respect to the corresponding test method or tothe working group of participants as a whole. The followingcover the evaluations and analyses that the working groupshould consider during their review in addition to the ap-proaches covered in the previous section.7.2 TPI and Precision TrendsCompare precisions ob-tained over a reasonable number of rounds for a given PTprogram test method (or parameter). Plotting such data seriesoften shows the appearance of trends more clearly. Theprecision estimates followed may include TP

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