Excel Sheet Download 6384 | Att R Amp R

Partial file snippet.

Sheet 1: Instructions

	
	
	
		Attribute Gage R & R Effectiveness
		
	
		Instructions:
		
	
		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.
	



Sheet 2: Data Entry

	
	
	
	
	
	
		

		Attribute Gage R & R Effectiveness
		
	
		
	
		
	
		

		

		

		

		SCORING REPORT
		

		

		

		

		

	
	
		

		

		

		

		

		

		

		All operators agree witin and between each other
		All Operators agree with standard
	
	
		
 
		
		Attribute Legend5
		

		DATE:
		

		

		
	
		(Must Enter Information)
		

		NAME:
		

		

		
	
		

		

		

		PRODUCT:
		

		

		
	
		

		2
		

		

		

		BUSINESS:
		

		

		
	
		

		

		

		

		

		

		

		

		

		

		

		
	
		

		

		

		Optional: Enter Operator Name or use Default
		

		

		
	
		

		Known Population
		Operator #1
		

		Operator #2
		

		Operator #3
		Y/N
		Y/N
	
	
		

		Sample #
		Standard
		Try #1
		Try #2
		

		Try #1
		Try #2
		

		Try #1
		Try #2
		Agree
		Agree
	
	
		

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		% APPRAISER SCORE(1) ->
		#DIV/0!
		

		

		#DIV/0!
		

		

		0%
		

		

	
	
		% SCORE VS. ATTRIBUTE(2) ->
		Known
		

		

		Known
		

		

		Known
		

		

	
	
		

		

		

		

		

		

		

		

		

		

		

		

		

	
	
		

		

		

		

		

		SCREEN % EFFECTIVE SCORE(3) ->
		#DIV/0!
		

	
	
		

		

		

		

		

		SCREEN % EFFECTIVE SCORE vs. ATTRIBUTE (4) ->
		#DIV/0!
	
	
		

		

		

		

		

		

		

		

		

		

		

		

		

	
	
		

		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

The words contained in this file might help you see if this file matches what you are looking for:

...Sheet instructions attribute gage r amp effectiveness the following spreadsheet is used to calculate an gr in which up samples can be evaluated using or operators data entry worksheet fill appropriate information scoring report section and enter type of attributes you are evaluating legend must entered into will not work either alpha numeric eg yes no pass fail go stop consistent throughout form spell properly if expert has selected know what these good vs bad this standard column enable determine how well each operator evaluate a set against known do need for although able assess standards have specify many that during test simply under specific remember spelled analyze correctly print copy click on icon delete see demo move around spread when finished all begin entering your own notes ucl lcl represent upper lower confidence limits binomial distribution calculated score basic computation reported page appraiser interval represents range within true lies given uncertainty associated w...

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Attribute Gage R & R Effectiveness
Instructions:
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.

		Attribute Gage R & R Effectiveness


				SCORING REPORT
				SCORING REPORT						All operators agree witin and between each other	All Operators agree with standard
		Attribute Legend5				DATE:
		(Must Enter Information)				NAME:
						PRODUCT:
	2					BUSINESS:

			Optional: Enter Operator Name or use Default
	Known Population		Operator #1			Operator #2		Operator #3		Y/N	Y/N
	Sample #	Standard	Try #1	Try #2		Try #1	Try #2	Try #1	Try #2	Agree	Agree
	1
	2
	3
	4
	5
	6
	7
	8
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	95
	96
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	98
	99
	100
% APPRAISER SCORE(1) ->				#DIV/0!			#DIV/0!		0%
% SCORE VS. ATTRIBUTE(2) ->				Known			Known		Known

					SCREEN % EFFECTIVE SCORE(3) ->					#DIV/0!
					SCREEN % EFFECTIVE SCORE vs. ATTRIBUTE (4) ->						#DIV/0!

	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

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