BS ISO 22514-3-2008 Statistical methods in process management - Capability and performance - Machine performance studies for measured data on discrete parts《过程管理的统计方法 能力和性能 离散部件测量数.pdf

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1、BRITISH STANDARDBS ISO 22514-3:2008Statistical methods in process management Capability and performance Part 3: Machine performance studies for measured data on discrete partsICS 03.120.30g49g50g3g38g50g51g60g44g49g42g3g58g44g55g43g50g56g55g3g37g54g44g3g51g40g53g48g44g54g54g44g50g49g3g40g59g38g40g51

2、g55g3g36g54g3g51g40g53g48g44g55g55g40g39g3g37g60g3g38g50g51g60g53g44g42g43g55g3g47g36g58BS ISO 22514-3:2008This British Standard was published under the authority of the Standards Policy and Strategy Committee on 30 April 2008 BSI 2008ISBN 978 0 580 56896 1National forewordThis British Standard is t

3、he UK implementation of ISO 22514-3:2008. The UK participation in its preparation was entrusted to Technical Committee SS/4, Statistical process control.A list of organizations represented on this committee can be obtained on request to its secretary.This publication does not purport to include all

4、the necessary provisions of a contract. Users are responsible for its correct application.Compliance with a British Standard cannot confer immunity from legal obligations.Amendments/corrigenda issued since publicationDate CommentsReference numberISO 22514-3:2008(E)INTERNATIONAL STANDARD ISO22514-3Fi

5、rst edition2008-02-15Statistical methods in process management Capability and performance Part 3: Machine performance studies for measured data on discrete parts Mthodes statistiques dans la gestion de processus Aptitude et performance Partie 3: tudes de performance de machines pour des donnes mesur

6、es sur des parties discrtes BS ISO 22514-3:2008ii iiiContents Page Foreword iv Introduction v 1 Scope . 1 2 Symbols and abbreviations . 1 3 Pre-conditions for application. 2 4 Data collection 3 5 Analysis . 4 6 Reporting . 14 7 Actions following a machine performance study 16 Annex A (informative) T

7、ables and worksheets . 17 Annex B (informative) Computer analysis of data 20 Bibliography . 23 BS ISO 22514-3:2008iv Foreword ISO (the International Organization for Standardization) is a worldwide federation of national standards bodies (ISO member bodies). The work of preparing International Stand

8、ards 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 ta

9、ke 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 i

10、s 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 possibili

11、ty 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 22514-3 was prepared by Technical Committee ISO/TC 69, Applications of statistical methods, Subcommittee SC 4, Applications of stati

12、stical methods in process management. ISO 22514 consists of the following parts, under the general title Statistical methods in process management Capability and performance: Part 1: General principles and concepts Part 3: Machine performance studies for measured data on discrete parts Part 4: Proce

13、ss capability estimates and performance measures Technical Report In the future, it is planned to revise ISO 21747:2006 (Statistical methods Process performance and capability statistics for measured quality characteristics) as Part 2. NOTE ISO 22514-3 was initially prepared as ISO/DIS 13700. It was

14、 renumbered before publication to include it in the ISO 22514 series. BS ISO 22514-3:2008vIntroduction This part of ISO 22514 has been prepared to provide guidance in circumstances where a study is necessary to determine if the output from a machine, for example, is acceptable according to some crit

15、eria. Such circumstances are common in engineering when the purpose for the study is part of an acceptance trial. These studies may also be used when diagnosis is required concerning a machines current level of performance or as part of a problem solving effort. The method is very versatile and has

16、been applied to many situations. Machine performance studies of this type provide information about the behaviour of a machine under very restricted conditions such as limiting, as far as possible, external sources of variation that are commonplace within a process, e.g. multi-factor and multi-level

17、 situations. The data gathered in a study might come from items made consecutively, although this may be altered according to the study requirements. The data are assumed to have been, generally, gathered manually. The study procedure and reporting will be of interest to engineers, supervisors and m

18、anagement wishing to establish whether a machine should be purchased or put in for maintenance, to assist in problem solving or to understand the level of variation due to the machine itself. BS ISO 22514-3:2008blank1Statistical methods in process management Capability and performance Part 3: Machin

19、e performance studies for measured data on discrete parts 1 Scope This part of ISO 22514 prescribes the steps to be taken in conducting short-term performance studies that are typically performed on machines where parts produced consecutively under repeatability conditions are considered. The number

20、 of observations to be analysed will vary according to the patterns the data produce, or if the runs (the rate at which items are produced) on the machine are low in quantity. The methods are not recommended where the sample size produced is less than 30 observations. Methods to be used for handling

21、 the data and carrying out the calculations are described. In addition, machine performance indices and the actions required at the conclusion of a machine performance study are described. The document is not applicable when tool wear patterns are expected to be present during the duration of the st

22、udy, nor if autocorrelation between observations is present. The situation where a machine has captured the data, sometimes thousands of data points collected in a minute, is not considered suitable for the application of this part of ISO 22514. 2 Symbols and abbreviations Pmmachine performance inde

23、x Pmkminimum machine performance index PmkLlower machine performance index PmkUupper machine performance index f frequency f cumulative frequency i subscript used to identify values of a variable L lower specification limit N total sample size X % % distribution fractile Xiith value in a sample BS I

24、SO 22514-3:20082 standard deviation, population S standard deviation, sample statistic, ()211NiiXXSN=U upper specification limit zfractile of the standardized normal distribution from to population mean value in relation to the machine location X arithmetic mean value, sample, 1NiiXXN=GRR gauge repe

25、atability and reproducibility 2 fractile of the Chi-square distribution 3 Pre-conditions for application 3.1 General The pre-conditions given below are the minimum and may be exceeded when needed. In this type of study, it is important to maintain constant all factors, other than the machine, which

26、will influence the results, if the study is to properly represent the machine itself, e.g. the same operator, same batch of material, etc. 3.2 Number of parts to be used in the study The number specified will usually be 100. However, if the pattern of variation is expected to form a non-normal distr

27、ibution, the number of parts should be at least 100. The methods given within this part of ISO 22514 may also be used when conducting audits of a process, in which case the number of measurements taken might be less than the above number, e.g. 50. NOTE 1 This is to ensure that a reasonably narrow co

28、nfidence interval can be calculated for the machine performance indices when a normal distribution has been used. The interval will be approximately 12 % of the estimated index with a confidence of 90 % for samples of 100. Some machines have very slow cycle times and a “run” cannot produce 100 parts

29、. In such circumstances, it will be necessary to proceed with available data. The minimum number that this part of ISO 22514 recommends with the methods described herein is 30. NOTE 2 Special techniques beyond the scope of this part of ISO 22514 exist for circumstances when there are fewer samples.

30、By contrast, a machine that produces parts at a very high rate, e.g. a rivet-making machine, the sampling strategy may require alteration since 100 parts will be produced in a few seconds. In circumstances such as these, several studies may be required each allowing a different sampling approach to

31、examine the machines behaviour. BS ISO 22514-3:200833.3 Materials to be used Ensure all input materials to be used in the study have been checked, conform to specifications and belong to the same batches. It is not advised that a study be conducted with materials that are outside specification since

32、 this could lead to unrepresentative results. Care should be exercised not to introduce any other sources of variation other than those to be studied. A typical example is where a machine run has to change to another batch of a particular material within a single process batch, and batch material va

33、riation is not included in the study. In this instance, only data taken while the first batch of that particular material was in use should be used in the analysis. 3.4 Measurement system Ensure the measurement system to be used during the study has adequate properties, is calibrated and the measure

34、ment system variation has been quantified and minimized. Special studies on the measurement system should be undertaken to establish the amount of variation present due to measuring. The measurement system should ideally have a combined gauge repeatability and reproducibility (GRR) of less than 10 %

35、 of the process spread of the characteristic that the machine study is to investigate as determined through a properly conducted measurement system analysis. This analysis should address issues of bias, stability, linearity and discrimination, as well as GRR. It may be appropriate to express the GRR

36、 as a percentage of a given specification tolerance. If the measurement system has between 10 % and 30 % GRR, it may still be regarded as acceptable dependant upon application. If it exceeds 30 %, the measurement system should be regarded as inappropriate. In addition, the measurement system should

37、have a measurement uncertainty appreciably less than the tolerance or of the expected total variation of the characteristic, if known, as indicated above. Should a study be performed using a measurement system with a performance worse than these requirements, some erroneous conclusions to the study

38、might be reached. 3.5 Running the study Ensure an uninterrupted run takes place, under normal operating conditions. This will include any warm-up time for the machine necessary to bring it up to its usual operating condition and with the machine set at nominal for the characteristic to be studied. I

39、f the machine is stopped during the study for whatever reason, either re-run the study again or analyse the data collected, as long as sufficient data has been collected and as long as the repeatability conditions have not been violated. Under no circumstance should less than 30 results be used. 3.6

40、 Special circumstances In a multiple fixture set-up, multiple-cavity or multi-stream situation, each station, fixture, cavity or stream should be treated as a separate machine for machine performance purposes since those streams may violate the repeatability conditions. In the case of a multiple-cav

41、ity tool, some extra studies may be performed to examine the between-cavity and within-cavity variation. Consecutive observations from all cavities may be used in the study so as to examine the total machine performance. Other statistical techniques may be employed, e.g. analysis of variance (ANOVA)

42、, to assist with the analysis of such circumstances. 4 Data collection 4.1 Traceability of data It is important for all data to be traceable so that unexpected values can be investigated. The collection sequence should be preserved so that a time series can be plotted of the data that might indicate

43、 unexpected variations. Such occurrences should be explained and a decision taken about the admissibility of such data. A “log-book” would be suitable for recording all machine settings including any prior work on the machine, e.g. maintenance, and for recording all events during the study, such as

44、adjustments. BS ISO 22514-3:20084 4.2 Retention of specimens Unless the tests performed are destructive in their nature, all specimens should be retained so that all necessary examinations can be made. They should only be disposed of once the study is complete and all conclusions determined. 4.3 Dat

45、a recording Data should be clearly recorded either electronically or on the appropriate analysis sheet in numerical form to the appropriate number of significant digits. This should be determined prior to the measuring process and will be dependent on the resolution of the measuring instrument. 5 An

46、alysis 5.1 General The analysis of the data generated in the study may be done manually, an example of which is given within this clause, or by means of computer programs an example of which is in given in Annex B. 5.2 Run chart 5.2.1 Purpose When conducting a machine study, it is important to under

47、stand whether the data collected form a single and stable pattern or not. There will be occasions when the conditions within the machine under study will lead to a drift in its settings that will influence the pattern of data produced. There might be occasions when an unauthorized adjustment has bee

48、n made to the machine or data have been mixed in some way. Such an event should stop the study and a new study should be begun. A run chart will be helpful to identify such circumstances. The pattern on the run chart in Figure 1 might have been caused by such an adjustment or something might have go

49、ne wrong with the machine itself or it is being used wrongly. If a change such as that indicated in Figure 1 occurs, it will be necessary to take special measures according to the circumstances. These might range between repeating the whole study to analysing the data in its separate parts or eliminating certain results. A manual graphical approach or a suitable software tool may be used to construct the run chart. ISO 7873 contains guidance about the application of control charts and their associated statistical tests that should be a