ASTM E2587-2012 Standard Practice for Use of Control Charts in Statistical Process Control《统计过程控制中控制图使用的标准实施规程》.pdf

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1、Designation: E2587 10E2587 12 An American National StandardStandard Practice forUse of Control Charts in Statistical Process Control1This standard is issued under the fixed designation E2587; the number immediately following the designation indicates the year oforiginal adoption or, in the case of r

2、evision, 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. Scope1.1 This practice provides guidance for the use of control charts in statistical process control prog

3、rams, which improve processquality through reducing variation by identifying and eliminating the effect of special causes of variation.1.2 Control charts are used to continually monitor product or process characteristics to determine whether or not a process isin a state of statistical control. When

4、 this state is attained, the process characteristic will, at least approximately, vary within certainlimits at a given probability.1.3 This practice applies to variables data (characteristics measured on a continuous numerical scale) and to attributes data(characteristics measured as percentages, fr

5、actions, or counts of occurrences in a defined interval of time or space).1.4 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 treated.1.5

6、 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 Docume

7、nts2.1 ASTM Standards:2E456 Terminology Relating to Quality and StatisticsE1994 Practice for Use of Process Oriented AOQL and LTPD Sampling PlansE2234 Practice for Sampling a Stream of Product by Attributes Indexed by AQLE2281 Practice for Process and Measurement Capability IndicesE2762 Practice for

8、 Sampling a Stream of Product by Variables Indexed by AQL3. Terminology3.1 Definitions:3.1.1 See Terminology E456 for a more extensive listing of statistical terms.3.1.2 assignable cause, nfactor that contributes to variation in a process or product output that is feasible to detect and identify(see

9、 special cause).3.1.2.1 DiscussionMany factors will contribute to variation, but it may not be feasible (economically or otherwise) to identify some of them.3.1.3 attributes data, nobserved values or test results that indicate the presence or absence of specific characteristics or countsof occurrenc

10、es of events in time or space.3.1.4 average run length (ARL), nthe average number of times that a process will have been sampled and evaluated beforea shift in process level is signaled.1 This practice is under the jurisdiction of ASTM Committee E11 on Quality and Statistics and is the direct respon

11、sibility of Subcommittee E11.30 on Statistical QualityControl.Current edition approved Oct. 1, 2010Dec. 1, 2012. Published November 2010.February 2013. Originally approved in 2007. last previous edition approved in 20072010as E2587 07E2587 10.1. DOI: 10.1520/E2587-10.10.1520/E2587-12.2 For reference

12、dASTM standards, visit theASTM website, www.astm.org, or contactASTM Customer Service at serviceastm.org. For Annual Book of ASTM Standardsvolume information, refer to the standards Document Summary page on the ASTM website.This document is not an ASTM standard and is intended only to provide the us

13、er 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 consult prior editions as appropriate. In all cases only the current versionof the standard a

14、s 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 States13.1.4.1 DiscussionA long ARL is desirable for a process located at its specified level (so as to minimize calling for unneed

15、ed investigation orcorrective action) and a short ARL is desirable for a process shifted to some undesirable level (so that corrective action will becalled for promptly). ARL curves are used to describe the relative quickness in detecting level shifts of various control chartsystems (see section 5.4

16、). The average number of units that will have been produced before a shift in level is signaled may alsobe of interest from an economic standpoint.3.1.5 c chart, ncontrol chart that monitors the count of occurrences of an event in a defined increment of time or space3.1.6 center line, nline on a con

17、trol chart depicting the average level of the statistic being monitored.3.1.7 chance cause, nsource of inherent random variation in a process which is predictable within statistical limits (seecommon cause).3.1.7.1 DiscussionChance causes may be unidentifiable, or may have known origins that are not

18、 easily controllable or cost effective to eliminate.3.1.8 common cause, n(see chance cause).3.1.9 control chart, nchart on which are plotted a statistical measure of a subgroup versus time of sampling along with limitsbased on the statistical distribution of that measure so as to indicate how much c

19、ommon, or chance, cause variation is inherent inthe process or product.3.1.10 control chart factor, na tabulated constant, depending on sample size, used to convert specified statistics or parametersinto a central line value or control limit appropriate to the control chart.3.1.11 control limits, nl

20、imits on a control chart that are used as criteria for signaling the need for action or judging whethera set of data does or does not indicate a state of statistical control based on a prescribed degree of risk.3.1.11.1 DiscussionFor example, typical three-sigma limits carry a risk of 0.135 % of bei

21、ng out of control (on one side of the center line) when theprocess is actually in control and the statistic has a normal distribution.3.1.12 EWMA chart, ncontrol chart that monitors the exponentially weighted moving averages of consecutive subgroups.3.1.13 exponentially weighted moving average (EWMA

22、), nweighted average of time ordered data where the weights of pastobservations decrease geometrically with age.3.1.13.1 DiscussionData used for the EWMA may consist of individual observations, averages, fractions, numbers defective, or counts.3.1.14 I chart, ncontrol chart that monitors the individ

23、ual subgroup observations.3.1.15 lower control limit (LCL), nminimum value of the control chart statistic that indicates statistical control.3.1.16 MR chart, ncontrol chart that monitors the moving range of consecutive individual subgroup observations.3.1.17 p chart, ncontrol chart that monitors the

24、 fraction of occurrences of an event.3.1.18 R chart, ncontrol chart that monitors the range of observations within a subgroup.3.1.19 rational subgroup, nsubgroup chosen to minimize the variability within subgroups and maximize the variabilitybetween subgroups (see subgroup).3.1.19.1 DiscussionVariat

25、ion within the subgroup is assumed to be due only to common, or chance, cause variation, that is, the variation is believedto be homogeneous. If using a range or standard deviation chart, this chart should be in statistical control. This implies that anyassignable, or special, cause variation will s

26、how up as differences between the subgroups on a corresponding X chart.3.1.20 s chart, ncontrol chart that monitors the standard deviations of subgroup observations.3.1.21 special cause, n(see assignable cause).3.1.22 standardized chart, ncontrol chart that monitors a standardized statistic.E2587 12

27、23.1.22.1 DiscussionA standardized statistic is equal to the statistic minus its mean and divided by its standard error.3.1.23 state of statistical control, nprocess condition when only common causes are operating on the process.3.1.23.1 DiscussionIn the strict sense, a process being in a state of s

28、tatistical control implies that successive values of the characteristic have thestatistical character of a sequence of observations drawn independently from a common distribution.3.1.24 statistical process control (SPC), nset of techniques for improving the quality of process output by reducing vari

29、abilitythrough the use of one or more control charts and a corrective action strategy used to bring the process back into a state of statisticalcontrol.3.1.25 subgroup, nset of observations on outputs sampled from a process at a particular time.3.1.26 u chart, ncontrol chart that monitors the count

30、of occurrences of an event in variable intervals of time or space, oranother continuum.3.1.27 upper control limit (UCL), nmaximum value of the control chart statistic that indicates statistical control.3.1.28 variables data, nobservations or test results defined on a continuous scale.3.1.29 warning

31、limits, nlimits on a control chart that are two standard errors below and above the centerline.3.1.30 X-bar chart, ncontrol chart that monitors the average of observations within a subgroup.3.2 Definitions of Terms Specific to This Standard:3.2.1 average count c!, narithmetic average of subgroup cou

32、nts.3.2.2 average moving range MR!, narithmetic average of subgroup moving ranges.3.2.3 average proportion p!, narithmetic average of subgroup proportions.3.2.4 average range R!, narithmetic average of subgroup ranges.3.2.5 average standard deviation s!, narithmetic average of subgroup sample standa

33、rd deviations.3.2.6 grand average (X=), naverage of subgroup averages.3.2.7 inspection interval, na subgroup size for counts of events in a defined interval of time space or another continuum.3.2.7.1 DiscussionExamples are 10 000 metres of wire inspected for insulation defects, 100 square feet of ma

34、terial surface inspected for blemishes,the number of minor injuries per month, or scratches on bearing race surfaces.3.2.8 moving range (MR), nabsolute difference between two adjacent subgroup observations in an I chart.3.2.9 observation, na single value of a process output for charting purposes.3.2

35、.9.1 DiscussionThis term has a different meaning than the term defined in Terminology E456, which refers there to a component of a test result.3.2.10 overall proportion, naverage subgroup proportion calculated by dividing the total number of events by the total numberof objects inspected (see averag

36、e proportion).3.2.10.1 DiscussionThis calculation may be used for fixed or variable sample sizes.3.2.11 process, nset of interrelated or interacting activities that convert input into outputs.3.2.12 subgroup average (Xi ), naverage for the ith subgroup in an X-bar chart.3.2.13 subgroup count (ci), n

37、count for the ith subgroup in a c chart.3.2.14 subgroup individual observation (Xi), nvalue of the single observation for the ith subgroup in an I chart.3.2.15 subgroup moving range (MRi), nmoving range for the ith subgroup in an MR chart.3.2.15.1 DiscussionE2587 123If there are k subgroups, there w

38、ill be k-1 moving ranges.3.2.16 subgroup proportion ( pi), nproportion for the ith subgroup in a p chart.3.2.17 subgroup range (Ri), nrange of the observations for the ith subgroup in an R chart.3.2.18 subgroup size (ni), nthe number of observations, objects inspected, or the inspection interval in

39、the ith subgroup.3.2.18.1 DiscussionFor fixed sample sizes the symbol n is used.3.2.19 subgroup standard deviation (si), nsample standard deviation of the observations for the ith subgroup in an s chart.3.3 Symbols:A2 = Factor for converting the average range to three standard errors for the X-bar c

40、hart (Table 1)A3 = Factor for converting the average standard deviation to three standard errors of the average for the X-bar chart (Table1)B3, B4 = Factors for converting the average standard deviation to three-sigma limits for the s chart (Table 1)ci = Counts of the observed occurrences of events

41、in the ith subgroup (10.2.1)c = Average of the k subgroup counts (10.2.1)c4 = Factor for converting the average standard deviation to an unbiased estimate of sigma (see ) (Table 1)d2 = Factor for converting the average range to an estimate of sigma (see ) (Table 1)D3, D4 = Factors for converting the

42、 average range to three-sigma limits for the R chart (Table 1)k = Number of subgroups used in calculation of control limits (6.2.1)MRi = Absolute value of the difference of the observations in the (i-1)th and the ith subgroups in a MR chart (8.2.1)MR! = Average of the subgroup moving ranges (8.2.2.1

43、)n = Subgroup size, number of observations in a subgroup (5.1.3)ni = Subgroup size, number of observations (objects inspected) in the ith subgroup (9.1.2)pi = Proportion of the observed occurrences of events in the ith subgroup (9.2.1)p = Average of the k subgroup proportions (9.2.1)Ri = Range of th

44、e observations in the ith subgroup for the R chart (6.2.1.2)R = Average of the k subgroup ranges (6.2.2)si = Sample standard deviation of the observations in the ith subgroup for the s chart (7.2.1)sz = Standard error of the EWMA statistic (11.2.1.2)s = Average of the k subgroup standard deviations

45、(7.2.2)ui = Counts of the observed occurrences of events in the inspection interval divided by the size of the inspection intervalfor the ith subgroup (10.4.2)Xi = Single observation in the ith subgroup for the I chart (8.2.1)Xij = The jth observation in the ith subgroup for the X-bar chart (6.2.1)X

46、i = Average of the ith subgroup observations for the X-bar chart (6.2.1)X = Average of the individual observations over k subgroups for the I chart (8.2.2)X= = Average of the k subgroup averages for the X-bar chart (6.2.2)Yi = Value of the statistic being monitored by an EWMA chart at time i (11.2.1

47、)Zi = Exponentially-weighted average (EWMA) statistic at time i (11.2.1)zi = The standardized statistic for the ith subgroup (9.4.1.3) = Factor (0 1) which determines the weighing of data in the EWMA statistic (11.2.1) = Estimated common cause standard deviation of the process (6.2.4)c = Standard er

48、ror of c, the number of observed counts (10.2.1.2)p = Standard error of p, the proportion of observed occurrences (9.2.2.4)TABLE 1 Control Chart FactorsforX-Bar andRCharts forX-Bar andSChartsn A2 D3 D4 d2 A3 B3 B4 c42 1.880 0 3.267 1.128 2.659 0 3.267 0.79793 1.023 0 2.575 1.693 1.954 0 2.568 0.8862

49、4 0.729 0 2.282 2.059 1.628 0 2.266 0.92135 0.577 0 2.114 2.326 1.427 0 2.089 0.94006 0.483 0 2.004 2.534 1.287 0.030 1.970 0.95157 0.419 0.076 1.924 2.704 1.182 0.118 1.882 0.95948 0.373 0.136 1.864 2.847 1.099 0.185 1.815 0.96509 0.337 0.184 1.816 2.970 1.032 0.239 1.761 0.969310 0.308 0.223 1.777 3.078 0.975 0.284 1.716 0.9727Note: for larger numbers of n, see Ref. (11).E2587 1244. Significance and Use4.1 This practice describes the use of control charts as a tool for use in statistic