1、Designation: E1169 07 E1169 12 An American National StandardStandard Practice forConducting Ruggedness Tests1This standard is issued under the fixed designation E1169; the number immediately following the designation indicates the year oforiginal adoption or, in the case of revision, the year of las
2、t revision. A number in parentheses indicates the year of last reapproval. Asuperscript epsilon () indicates an editorial change since the last revision or reapproval.1. Scope1.1 This practice covers conducting ruggedness tests. The purpose of a ruggedness test is to identify those factors that stro
3、nglyinfluence the measurements provided by a specific test method and to estimate how closely those factors need to be controlled.1.2 This practice restricts itself to designs with two levels per factor. The designs require the simultaneous change of the levelsof all of the factors, thus permitting
4、the determination of the effects of each of the factors on the measured results.1.3 The system of units for this practice is not specified. Dimensional quantities in the practice are presented only as illustrationsof calculation methods. The examples are not binding on products or test methods treat
5、ed.1.4 This standard does not purport to address all of the safety concerns, if any, associated with its use. It is the responsibilityof the user of this standard to establish appropriate safety and health practices and determine the applicability of regulatorylimitations prior to use.2. Referenced
6、Documents2.1 ASTM Standards:2E456 Terminology Relating to Quality and StatisticsE1325 Terminology Relating to Design of ExperimentsE1488 Guide for Statistical Procedures to Use in Developing and Applying Test MethodsF2082 Test Method for Determination of Transformation Temperature of Nickel-Titanium
7、 Shape Memory Alloys by Bend andFree Recovery3. Terminology3.1 DefinitionsThe terminology defined in Terminology E456 applies to this practice unless modified herein.3.1.1 ruggedness, ninsensitivity of a test method to departures from specified test or environmental conditions.3.1.1.1 DiscussionAn e
8、valuation of the “ruggedness” of a test method or an empirical model derived from an experiment is useful in determiningwhether the results or decisions will be relatively invariant over some range of environmental variability under which the testmethod or the model is likely to be applied.3.1.2 rug
9、gedness test, na planned experiment in which environmental factors or test conditions are deliberately varied in orderto evaluate the effects of such variation.3.1.2.1 DiscussionSince there usually are many environmental factors that might be considered in a ruggedness test, it is customary to use a
10、“screening” type of experiment design which concentrates on examining many first order effects and generally assumes that secondorder effects such as interactions and curvature are relatively negligible. Often in evaluating the ruggedness of a test method, if1 This practice is under the jurisdiction
11、 of ASTM Committee E11 on Quality and Statistics and is the direct responsibility of Subcommittee E11.20 on Test MethodEvaluation and Quality Control.Current edition approved Aug. 1, 2007Nov. 1, 2012. Published October 2007 December 2012. Originally approved in 1987. Last previous edition approved i
12、n 20022007as E1169 02.E1169 07. DOI: 10.1520/E1169-07.10.1520/E1169-12.2 For referenced ASTM standards, visit the ASTM website, www.astm.org, or contact ASTM Customer Service at serviceastm.org. For Annual Book of ASTM Standardsvolume information, refer to the standards Document Summary page on the
13、ASTM website.This document is not an ASTM standard and is intended only to provide the user of an ASTM standard an indication of what changes have been made to the previous version. Becauseit may not be technically possible to adequately depict all changes accurately, ASTM recommends that users cons
14、ult prior editions as appropriate. In all cases only the current versionof the standard as published by ASTM is to be considered the official document.Copyright ASTM International, 100 Barr Harbor Drive, PO Box C700, West Conshohocken, PA 19428-2959. United States1there is an indication that the res
15、ults of a test method are highly dependent on the levels of the environmental factors, there is asufficient indication that certain levels of environmental factors must be included in the specifications for the test method, or eventhat the test method itself will need further revision.3.2 Definition
16、s of Terms Specific to This Standard:3.2.1 factor, ntest variable that may affect either the result obtained from the use of a test method or the variability of thatresult.3.2.1.1 DiscussionFor experimental purposes, factors must be temporarily controllable.3.2.2 foldover, ntest runs, added to a two
17、-level fractional factorial experiment, generated by duplicating the original designby switching levels of one or more factors in all runs.3.2.2.1 DiscussionThe most useful type of foldover is with signs of all factors switched. The foldover runs are combined with the initial test results.The combin
18、ation allows main effects to be separated from interactions of other factors that are aliased in the original design.4. Summary of Practice4.1 Conducting a ruggedness test requires making systematic changes in the variables, called factors, that are associated withthe test method and then observing
19、the subsequent effect of those changes upon the test result of each run.4.2 The factors chosen for ruggedness testing are those believed to have the potential to affect the results. However, since nocontrol limits are provided in the standard for these factors, ruggedness testing is intended to eval
20、uate this potential.4.3 This practice recommends statistically designed experiments involving two levels of multiple factors. The steps to beconducted include:4.3.1 Identification of relevant factors;4.3.2 Selection of appropriate levels (two for each factor) to be used in experiment runs;4.3.3 Disp
21、lay of treatment combinations in cyclic shifted order (see Annex A1 for templates), which assigns factors and levelsto runs;4.3.4 Execution of runs arranged in a random order;4.3.5 Statistical analysis to determine the effect of factors on the test method results; and4.3.6 Possible revision of the t
22、est method as needed.5. Significance and Use5.1 A ruggedness test is a special application of a statistically designed experiment. It is generally carried out when it is desirableto examine a large number of possible factors to determine which of these factors might have the greatest effect on the o
23、utcomeof a test method. Statistical design enables more accurate determination of the factor effects than would be achieved if separateexperiments were carried out for each factor. The proposed designs are easy to use and are efficient in developing the informationneeded for evaluating quantitative
24、test methods.5.2 In ruggedness testing, the two levels for each factor are chosen to use moderate separations between the high and lowsettings. In general, the size of effects, and the likelihood of interactions between the factors, will increase with increased separationbetween the high and low set
25、tings of the factors.5.3 Ruggedness testing is usually done within a single laboratory on uniform material, so the effects of changing only the factorsare measured. The results may then be used to assist in determining the degree of control required of factors described in the testmethod.5.4 Ruggedn
26、ess testing is part of the validation phase of developing a standard test method as described in Guide E1488. It ispreferred that a ruggedness test precedes an interlaboratory (round robin) study.6. Ruggedness Test Design6.1 A series of fractional factorial designs are recommended for use with rugge
27、dness tests for determining the effects of the testmethod variables (see Annex A1). All designs considered here have just two levels for each factor. They are known asPlackett-Burman designs (1).33 The boldface numbers in parentheses refer to the list of references at the end of this standard.E1169
28、1226.1.1 Choose the level settings so that the measured effects will be reasonably large relative to measurement error. It is suggestedthat the high and low levels be set at the extreme limits that could be expected to exist between different qualifying laboratories.6.2 Table 1 shows the recommended
29、 design for up to seven factors, each factor set at two levels. The level setting is indicatedby either (-1) or (1) for low or high levels, respectively. For factors with non-ordered scales (categorical), the designation “low”or “high” is arbitrary.6.3 The design provides equal numbers of low and hi
30、gh level runs for every factor. In other words, the designs are balanced.Also, for any factor, while it is at its high level, all other factors will be run at equal numbers of high and low levels; similarly,while it is at its low level, all other factors will be run at equal numbers of high and low
31、levels. In the terminology used bystatisticians, the design is orthogonal.6.4 The difference between the average response of runs at the high level and the average response of runs at the low level ofa factor is the “main effect” of that factor. When the effect of a factor is the same regardless of
32、levels of other factors, then themain effect is the best estimate of the factors effect.6.5 If the effect of one factor depends on the level of another factor, then these two factors interact. The interaction of two factorscan be thought of as the effect of a third factor for which the column of sig
33、ns is obtained by multiplying the columns of signs forthe two initial factors. For example, the eight signs for Column C of Table 1, multiplied by the corresponding eight signs in ColumnD, gives a column of signs for the interaction CD. The complication of the fractional factorial designs presented
34、here is that maineffects are confounded (aliased) with the two-factor interactions. Factors are aliased when their columns of signs are the negativesor positives of each other. For example, the column of signs for the interaction CD is identical to minus the column of signs forColumn A.6.6 To separa
35、te factor main effects from interactions, the design shall be increased with additional runs. A “foldover,” as shownin Table 2, is recommended to separate the main effects from the aliased interactions. When the runs in Tables 1 and 2 arecombined, all main factors will no longer be aliased with two-
36、factor interactions.6.7 Sensitivity of the experiment can be increased by the addition of a second block of runs that replicates the first (that is, runswith the same factor settings as the first block). Increasing the size of the experiment improves the precision of factor effects andfacilitates th
37、e evaluation of statistical significance of the effects. However, the preference of this practice is to use a foldover ratherthan a repeat of the original design.6.8 The sequence of runs in Tables 1 and 2 is not intended to be the actual sequence for carrying out the experiments. The orderin which t
38、he runs of a ruggedness experiment are carried out should be randomized to reduce the probability of encountering anypotential effects of unknown, time-related factors. Alternatively, optimum run orders to control the number of required factorchanges and the effect of linear time trends have been de
39、rived (2). In some cases, it is not possible to change all factors in acompletely random order. It is best if this limitation is understood before the start of the experiment. A statistician may be contactedfor methods to deal with such situations.7. Ruggedness Test Calculations7.1 Estimate factor e
40、ffects by calculating the difference between average responses at the high and the low levels. When thedesign is folded over, obtain the main effect of a factor by averaging effects from the design and its foldover. Estimate thecorresponding confounded interactions by taking half the difference of t
41、he main effects.7.2 A half-normal plot is used to identify potentially statistically significant effects.7.2.1 Construct a half-normal plot by plotting the absolute values of effects on the X-axis, in order from smallest to largest,against the half-normal plotting values given in Annex A2 on the Y-a
42、xis. Effects for all columns in the design, including columnsTABLE 1 Recommended Design for Up to Seven FactorsNOTE 1For four factors, use Columns A, B, C, and E; for five factors, use Columns A, B, C, D, and F; for six factors, use Columns A, B, C, D, F,and G.PB Order Run # A B C D E F G Test Resul
43、t1 1 1 1 -1 1 -1 -12 -1 1 1 1 -1 1 -13 -1 -1 1 1 1 -1 14 1 -1 -1 1 1 1 -15 -1 1 -1 -1 1 1 16 1 -1 1 -1 -1 1 17 1 1 -1 1 -1 -1 18 -1 -1 -1 -1 -1 -1 -1Ave +Ave -EffectE1169 123not used to assign levels to any real experiment factor, are plotted. The half-normal plotting values do not depend on data. T
44、heydepend only on the half-normal distribution and the number of effects plotted.7.2.2 A reference line in the half normal plot is provided with slope 1/seffect, if an estimate of precision is available. Potentiallysignificant effects are those that fall farthest to the right of the line.7.3 If an e
45、stimate of precision is available or can be derived from the experiment, statistical tests of factor effects can bedetermined using the Students t-test. The t-test statistic for a factor is the effect divided by the standard error seffect, which is thesame for all factors with a balanced and orthogo
46、nal design. If the t-value is greater than the t-value corresponding to the 0.05significance level, the factor is statistically significant at level 0.05.7.3.1 If fewer factors are used with the design than the maximum number, then “effects” estimated for the unused columns differfrom zero only as a
47、 result of experimental error (or interactions of other factors). The root mean square of unused effects is anestimate of the standard error of an effect having degrees of freedom equal to the number of unused effects averaged (3).7.3.2 The design may be replicated; that is, a second block of runs u
48、sing the same factor settings as the original design is run.Then an estimate of the standard error of an effect is:seffect 5 4sr2N 3reps (1)with degrees of freedom of (N 1) (reps 1),where:N = number of runs in the design,reps = number of replicates of the design, andsr = the estimated standard devia
49、tion of the test results.7.3.2.1 An example showing calculation of sr2 and seffect is given in 8.2.8. Example of a Replicated Ruggedness Experiment8.1 An example of a seven-factor ruggedness experiment comes from a study done for Test Method F2082. This test methoddetermines a transformation temperature for nickel-titanium shape memory alloys. The factors of interest are quench method, bathtemperature at deformation, equilibrium time, bending strain, pin spacing, linear variable differential transducer (LVDT) probeweight, and heating rate. Table 3 provides t
