Attribute Gage R&R

InstructionsAttribute Gage R & R EffectivenessInstructions:1)The following spreadsheet is used to calculate an Attribute GR&R Effectiveness, in which up to 100 samples can be evaluated, using 2 or 3 operators.2)In the Data Entry worksheet, fill in the appropriate information in the Scoring Report section and enter the type of Attributes you are evaluating in the Attribute Legend section. THE INFORMATION MUST BE ENTERED INTO THE ATTRIBUTE LEGEND SECTION OR THE SPREADSHEET WILL NOT WORK. The attributes can be either alpha or numeric, e.g. Yes, No; pass, fail; go, stop; or 1, 2. You must be consistent throughout the form and spell properly.3)If you or an expert has selected samples to be evaluated and you know what attributes these samples are (Good vs Bad), enter this information in the STANDARD column. This will enable you to determine how well each operator can evaluate a set of samples against a known standard. You do not need to enter information in this column for the spreadsheet to work, although you will not be able to assess the operators against known standards.4)You do not have to specify how many operators or the # of samples that you will be evaluating during the test. Simply enter the data into the spreadsheet under the specific operator. Remember the attributes must be spelled properly or the spreadsheet will not analyze the data correctly.5)To print a copy of the report click on the Print Report icon.6)To delete the data in the spreadsheet, click on the Delete Data icon.7)To see a Demo of the Attribute GR&R Effectiveness spreadsheet, click on the Demo icon. Move around the spread sheet to see the data. When you are finished, click the Delete Data icon to delete all data to begin entering your own data.NOTES:The 95% UCL and 95% LCL represent the 95% upper and lower confidence limits on the binomial distribution. The Calculated Score is the basic computation reported on the report page for % Appraiser and % Score vs Attribute. The 95% confidence interval represents the range within which the true Calculated Score lies given the uncertainty associated with limited sample sizes. As sample size increases (in this case, Total Inspected) the confidence interval will get smaller and smaller which indicates more reliable estimates of the true percentages. In the case of the Demo data, the true Calculated score for Operator 1 could be as low as 76.8% given that only 14 samples inspected, even though there was a 100% Appraiser value calculated. Also, even though Operator 2 had a lower score, Operators 1 and 3 cannot be distinguished from Operator 2 because the calculated score of #2 (78.6%) lies within the confidence limits for Operators 1 and 3.With a worksheet limitation of 100 samples, the best the lower 95% limit can be is 96.4%. Thus, we would have to say that the best an inspector could be is 96% efficient; even though they did not make any mistakes.Try different combinations of number of samples and number of matches to see the effects of sample size. EXAMPLE: a sample size of 30 with one non-match will yield a 17% confidence interval. In order to get reasonable reliability in estimates of efficiency, large sample sizes will be required.

Data EntryAttribute Gage R & R EffectivenessSCORING REPORTAll operators agree witin and between each otherAll Operators agree with standardAttribute Legend5DATE:(Must Enter Information)NAME:1PRODUCT:2BUSINESS:Optional: Enter Operator Name or use DefaultKnown PopulationOperator #1Operator #2Operator #3Y/NY/NSample #StandardTry #1Try #2Try #1Try #2Try #1Try #2AgreeAgree10020030040050060070080090010001100120013001400150016001700180019002000210022002300240025002600270028002900300031003200330034003500360037003800390040004100420043004400450046004700480049005000510052005300540055005600570058005900600061006200630064006500660067006800690070007100720073007400750076007700780079008000810082008300840085008600870088008900900091009200930094009500960097009800990010000% APPRAISER SCORE(1) ->0.00%0.00%0%% SCORE VS. ATTRIBUTE(2) ->KnownKnownKnownSCREEN % EFFECTIVE SCORE(3) ->0.00%SCREEN % EFFECTIVE SCORE vs. ATTRIBUTE (4) ->0.00%Note:(1)Operator agrees with him/herself on both trials(2)Operator agrees on both trials with the known standard(3)All operators agreed within and between themselves(4)All operators agreed within and between themselves AND agreed with the known standard(5)Enter Pass/Fail, Good/Bad, Accept/Reject or other labels which indicate status of inspection

DemoDelete Data

Statistical ReportStatistical Report - Attribute Gage R&R StudyDATE:31-Dec-1899NAME:0PRODUCT:0BUSINESS:0% Appraiser to Self1% Appraiser Vs Standard2SourceOperator #1Operator #2Operator #3Operator #1Operator #2Operator #3Total Inspected000000# Matched00000095% UCL0.0%0.0%0.0%0.0%0.0%0.0%Calculated Score0.0%0.0%0.0%0.0%0.0%0.0%95% LCL0.0%0.0%0.0%0.0%0.0%0.0%False Negative (operator biased toward rejection) Std = Pass000False Positive (operator biased toward acceptance) Std = Fail000Mixed (Operator accepts and rejects the same part)000Screen % Effective Score3Screen % Effective Score vs Standard4Total Inspected00# in Agreement0095% UCL0.0%0.0%Calculated Score0.0%0.0%95% LCL0.0%0.0%Notes1) Operator agrees with him/herself on both trials2) Operator agrees on both trials with the known standard3) All operators agreed within and between themselves4) All operators agreed within & between themselves AND agreed with the known standard

Statistical Report110.80719042670.9534206390.78571428570.4920244217110.8071904267

95% UCLCalculated Score95% LCL% Efficiency% Apprraiser to Self

Calculations0.9534206390.78571428570.49202442170.87240123750.64285714290.35138034820.91611051560.71428571430.418964386

95% UCLCalculated Score95% LCL% Efficiency% Appraiser Vs Standard

DemoKnown PopulationOperator #1Operator #2Operator #3Y/NY/NSample #AttributeTry #1Try #2withinknownTry #1Try #2withinknownTry #1Try #2withinknownAgreeAgree2323Known-1Known-2Known-3False NegFalse PosMixedFalse NegFalse PosMixedFalse NegFalse 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% Appraiser Score0.00%0.00%0.00%0.00%0.00%0.00%000000000

Print Report

19-Nov-2002Nickle MachiningpassWooden NicklefailWood NicklesOperator #1Operator #2Operator #31passpasspasspasspassfailfail2passpasspasspasspassfailfail3failfailfailfailpassfailfail4failfailfailfailfailfailfail5failfailfailpassfailfailfail6passpasspasspasspasspasspass7passfailfailfailfailfailfail8passpasspasspasspasspasspass9failpasspasspasspasspasspass10failpasspassfailfailfailfail11passpasspasspasspasspasspass12passpasspasspasspasspasspass13failfailfailfailfailfailfail14failfailfailpassfailfailfail