InstructionsAttribute Gage R & R
EffectivenessInstructions:1)The following spreadsheet is used to
calculate an Attribute GR&R Effectiveness, in which up to100
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 andenter the type of Attributes you are evaluating
in the Attribute Legend section. YOU MUST ENTERTHE INFORMATION IN
THE ATTRIBUTE LEGEND SECTION OR THE SPREADSHEETWILL 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 thesesamples are, enter this
information in the Attribute sample column. This will enable you to
determinehow well each operator can evaluate a set of samples
against a known standard. You do notneed to enter information in
this column for the spreadsheet to work although you willnot 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 evaluatingduring the test. Simply enter the data into the
spreadsheet under the specific operator. Rememberthe 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 delete all and begin a new test, click on the
Delete All icon8)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 All iconto delete all data to begin entering your own
data.The 95% UCL and 95% LCL represent the 95% upper and lower
confidence limits on thebinomial distribution. The Calculated Score
is the basic computation reported on the reportpage for % Appraiser
and % Score vs Attribute. The 95% confidence interval representsthe
range within which the true Calculated Score lies given the
uncertainty associated withlimited sample sizes. As sample size
increases (in this case, Total Inspected) theconfidence interval
will get smaller and smaller which indicates more reliable
estimates ofthe true percentages. In the case of the Demo data, the
true Calculated score for Operator 1could 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 3cannot be distinguished from Operator
2 because the calculated score of #2 (78.6%) lies withinthe
confidence limits for Operators 1 and 3.With a worksheet limitation
of 100 samples, at best a lower 95% limit of 96.4% can be
calculated.Thus, we would have to say that an inspector could be as
bad as 96% efficient, even though he/shemissed no calls.Sample
Size30< Try out different combinations of number of samples and
number of matches# Matches30< to see the effects of sample size.
In this case, a sample size of 30 with95% UCL100.0%< one
non-match will yield a 17% confidence interval. In order to get
reasonableCalculated Score100.0%< reliability in estimates of
efficiency, large sample sizes will be required.95% LCL88.4%
Data EntryAttribute Gage R & R EffectivenessSCORING
REPORTDATE:10/06/2004Attribute Legend5 (used in
computations)NAME:Final Inspection1PRODUCT:TyresAll
operators2BUSINESS:agree within andAll Operatorsbetween eachagree
withOtherstandardKnown PopulationOperator #1Operator #2Operator
#3Y/NY/NSample #AttributeTry #1Try #2Try #1Try #2Try #1Try
#2AgreeAgree1FMPGFCFCLBDLBDLBDLBDYN2OKOKOKOKOKOKOKYY3LSDLSDLSDLSDLSDLSDLSDYY4ILBILBILBOKOKOKOKNN5KBKBKBKBKBDBLKBNN6OKFMPGFMPGOKOKOKOKNN7LBLBLBLBLBLBLBYY8OKOKOKOKOKTBWTBWNN9LTLTLTLTLTLTLTYY10OKLBDLBDLTOKLBDLBDNN11FMPFMPFMPFMPFMPFMPFMPYY12BBBBBBOKBBBBBBNN13DFBTBTDFDFDFTDFTNN14OKOKOKOKOKOKOKYY15FMSTFMSTFMSTLBDFMSTFMCFMCNN16LBDLBDOKLBDLBDLBDLBDNN17OKLBDLBDOKLBDOKOKNN18OKOKOKOKOKOKOKYY19CTCTCTCTFMPCTLCTLNN20AIAIAIAIAIAIAIYY21OKOKOKOKOKOKOKYY22NBDMDMOKRBNBNBNN23DFTFMFMDFTDFTDFTDFTNN24UCTBWTBWTBWTBWUCUCNN25OKOKOKOKOKOKOKYY26CFCDMDMOKCFCCFCCFCNN27FCFCFCFCFCFCFCYY28CTTCTTCTTOKOKOKDMNN29OKDMDMTBOKTBWTBWNN30FMLRFMLRFMLRFMLRFMLRFMLRFMLRYY31003200330034003500360037003800390040004100420043004400450046004700480049005000510052005300540055005600570058005900600061006200630064006500660067006800690070007100720073007400750076007700780079008000810082008300840085008600870088008900900091009200930094009500960097009800990010000%
APPRAISER SCORE(1) ->96.67%76.67%96.67%% SCORE VS. ATTRIBUTE(2)
->63.33%60.00%66.67%SCREEN % EFFECTIVE SCORE(3)
->43.33%SCREEN % EFFECTIVE SCORE vs. ATTRIBUTE (4)
->40.00%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
Delete DataLoad DemoDelete AllPrint ReportPrint Statistics
WData6/24/15 6:546/24/15 6:546:00:00
ReportAttribute Gage R & R EffectivenessSCORING
REPORTDATE:10/06/2004Attribute LegendNAME:Final
Inspection10PRODUCT:TyresAll operators20BUSINESS:0agree within
andAll Operatorsbetween eachagree withOtherstandardKnown
PopulationOperator #1Operator #2Operator #3Y/NY/NSample
#AttributeTry #1Try #2Try #1Try #2Try #1Try
#2AgreeAgree1FMPGFCFCLBDLBDLBDLBDYN2OKOKOKOKOKOKOKYY3LSDLSDLSDLSDLSDLSDLSDYY4ILBILBILBOKOKOKOKNN5KBKBKBKBKBDBLKBNN6OKFMPGFMPGOKOKOKOKNN7LBLBLBLBLBLBLBYY8OKOKOKOKOKTBWTBWNN9LTLTLTLTLTLTLTYY10OKLBDLBDLTOKLBDLBDNN11FMPFMPFMPFMPFMPFMPFMPYY12BBBBBBOKBBBBBBNN13DFBTBTDFDFDFTDFTNN14OKOKOKOKOKOKOKYY15FMSTFMSTFMSTLBDFMSTFMCFMCNN16LBDLBDOKLBDLBDLBDLBDNN17OKLBDLBDOKLBDOKOKNN18OKOKOKOKOKOKOKYY19CTCTCTCTFMPCTLCTLNN20AIAIAIAIAIAIAIYY21OKOKOKOKOKOKOKYY22NBDMDMOKRBNBNBNN23DFTFMFMDFTDFTDFTDFTNN24UCTBWTBWTBWTBWUCUCNN25OKOKOKOKOKOKOKYY26CFCDMDMOKCFCCFCCFCNN27FCFCFCFCFCFCFCYY28CTTCTTCTTOKOKOKDMNN29OKDMDMTBOKTBWTBWNN30FMLRFMLRFMLRFMLRFMLRFMLRFMLRYY%
APPRAISER SCORE(1) ->96.67%76.67%96.67%% SCORE VS. ATTRIBUTE(2)
->63.33%60.00%66.67%SCREEN % EFFECTIVE SCORE(3)
->43.33%SCREEN % EFFECTIVE SCORE vs. ATTRIBUTE(4)
->40.00%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
Statistical ReportStatistical Report - Attribute Gage R&R
StudyDATE:10/06/2004NAME:Final
InspectionPRODUCT:TyresBUSINESS:12/31/99% Appraiser1%Score vs
Attribute2SourceOperator #1Operator #2Operator #3Operator
#1Operator #2Operator #3Total Inspected303030303030#
Matched292329191820False Negative (operator biased toward
rejection)000False Positive (operator biased toward
acceptance)191820Mixed17195%
UCL99.9%90.1%99.9%80.1%77.3%82.7%Calculated
Score96.7%76.7%96.7%63.3%60.0%66.7%95%
LCL82.8%57.7%82.8%43.9%40.6%47.2%Screen % Effective Score3Screen %
Effective Score vs Attribute4Total Inspected3030# in
Agreement131295% UCL62.6%59.4%Calculated Score43.3%40.0%95%
LCL25.5%22.7%Notes(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 & between themselves AND agreed with
the known standard
CalculationsKnown 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 Score96.67%63.33%76.67%60.00%96.67%66.67%019101870201
DemoData3/10BMGpassDemo DatafailInspectionOperator #1Operator
#2Operator
#31passpasspasspasspassfailfail2passpasspasspasspassfailfail3failfailfailfailpassfailfail4failfailfailfailfailfailfail5failfailfailpassfailfailfail6passpasspasspasspasspasspass7passfailfailfailfailfailfail8passpasspasspasspasspasspass9failpasspasspasspasspasspass10failpasspassfailfailfailfail11passpasspasspasspasspasspass12passpasspasspasspasspasspass13failfailfailfailfailfailfail14failfailfailpassfailfailfail
Sheet1
