Attribute Gage R&R - ASQ-1302

Attribute Gage R&R 

An Overview 

Presented to ASQ Section 1302 

August 18, 2011 

by Jon Ridgway 

Copyright: JC Quality Business Solutions LLC

Overview 

• What is an Attribute Gage R&R? 

• Why is it worth the work? 

• What are the caveats? 

• How do I perform it? 

• How do I understand the results? 


My Attribute Gage R&R Experience 

• First Data 

– Credit Card mailings (“packages”) 

• Airlite Plastics: 

– Mold & Print Quality 

– Print Quality, Cup & Lid Decoration 


WHY conduct a Gage R&R???? 

• Some processes require subjective decision 

making: 

– Inspection 

– Validation 

• Subjectivity creates the potential for variation 

• Measurement System variation impacts process 

capability: 

– Type I Errors 

– Type II Errors 


So, Why Conduct a Gage R&R? 

• To understand: 

– How likely Appraiser will agree with himself / herself: 

• WITHIN / Repeatability 

– How likely all Appraisers will agree with each other: 

• BETWEEN / Reproducibility 

• Understanding R&R allows you to: 

– Predict probability (%) of agreement / disagreement 

– Implement training to improve that probability 

– Reduce Type I and Type II Errors = $$$ 


MSA 

• The Foundation of everything in Quality is 

measurement 

• Measure for two primary reasons: 

– To make a decision 

– As the basis for process improvement 

• Can we trust our measurement system to 

give us reliable data? 

– CONFIDENCE 


Ultimate purpose of the Attribute 

Agreement Analysis 

• To determine if your measurement system 

can distinguish between a good & bad part 

• Accuracy & Precision: 

– Accuracy: 

• Absence of bias, or agreeing with the standard. 

– Precision: 

• Ability of different Appraisers to reach the same 

conclusion several times. 


Accurate, But Not Precise 


Precise, But Not Accurate 


Which is Easier to Remedy? 

Accurate, but not Precise 

Precise, but not Accurate 


Gage R&R Review 

• Measurement System Analysis (MSA) 

– 1 st R: Repeatability 

– 2 nd R: Reproducibility 

• Data in General: 

– Continuous / Variables 

– Attribute / Discrete 


Attribute vs. Continuous 

• Attribute Data: 

–Categorical, named only, arbitrary scales 

–Also known as Discrete Data 

• Continuous Data: 

–Allows for infinitely finer sub-divisions 

–Also known as Variables Data 


• Nominal: 

– Literally, “name” 

– Represents categories 

• Ordinal: 

– Ordered or ranked data 

– Not scaled 

Basic Data Types 

• Interval: 

– Measured / scaled data: Each position equidistant 

– 0 can be relevant (temperature) 

• Ratio: 

– Numbers compared as multiples of one another 


Hierarchy of Data Types 

Nominal Ordinal Interval Ratio 

Classified Data 

Quantified Data 

DISCRETE / ATTRIBUTE 

Non-parametric 

CONTINUOUS / VARIABLE 

Parametric 


2 Main Attribute Gage R&R Types 

1) Binary / Nominal 

– GO / NO GO 

– Data are Categorical and mutually exclusive 

– Kappa statistic is relevant 

2) Ordinal 

– Rank, not categorical 

– Data are not mutually exclusive 

– Kendall’s statistic more relevant than Kappa 


Kappa Statistic 

• Proportion of agreement between 

evaluators after chance agreement has 

been removed: 

– Kappa = P observed – P chance / P chance 

• Expressed as a number: 

– From 0 (expected by chance) 

– Up to +1 (complete agreement) 


Kendall’s Statistics 

• Two different Kendall’s for different tests: 

– Kendall’s Coefficient of Concordance: 

• Rankings without a known Standard 

– Kendall’s Correlation Coefficient: 

• Rankings with a known Standard 

– Expressed as 0 (weaker agreement) to +1 

(stronger agreement) 


• Kappa: 

Kappa & Kendall’s Summary 

– Nominal / Binary Only 

– Match or No Match 

• Kendall’s Coefficient of Concordance: 

– Ordinal but not using a known Standard 

• Kendall’s Correlation Coefficient: 

– Ordinal and using a known Standard 


Attribute Gage R&R Considerations 

• Study Purpose 

• Destructiveness 

• Precision vs. Time 

• Binomial / Nominal vs. Ordinal 


MSA Factors Impacting Variation 

• Gage 

• Appraiser 

• Method 

• Part 

• Environment 


• Ideally: 

Controlling MSA Factors 

1. Use the same Assessment Method 

2. Require all Appraisers to assess the same 

dimension / feature / sample 

3. Conduct the study under the normal 

assessment conditions 


Controlling MSA Factors, Cont. 

1) Appraisers: Select from group that 

normally appraises the part. 

2) Number of parts should cover the entire 

range of variation. 

3) More than one appraisal per Appraiser 

should be done. 

4) The presentation of the samples within 

the Trial should be randomized. 


Nominal / Binary Study 

• Two Appraisers 

• 50 Parts 

• 2 Trials 




Output: Within 


Output: Within vs. Standard 


Assessment Agreement 

Date of study: 

Reported by: 

Name of product: 

Misc: 

Within Appraisers 

Appraiser vs Standard 

100 

95.0% C I 

Percent 

100 

95.0% C I 

Percent 

95 

95 

Percent 

90 

Percent 

90 

85 

85 

80 

Lee 

Fred 

80 

Lee 

Fred 

Appraiser 

Appraiser 


Output: Between 


Output: Between vs. Standard 


Ordinal Case Study: Print Quality 


What did we want to know? 

• Do all Appraisers of Print Quality: 

– Agree consistently with Themselves? 

– Agree consistently with Each Other? 

– Given our world, we have an ordinal system: 

• Accept 

• Accept but Adjust 

• Reject 


How was it Done? 

• 10 samples, Good & Bad 

• Random Order, Same for All 

• 2 Trials per person 

• All people in the study 

• Environment 


Ensure Gage R&R Consistency 


Spanish Version 


Vietnamese Version 


Trial Order 

My Checklist 



Results 

Sample QA1-1 QA1-2 QA2-1 QA2-2 QA4-1 QA4-2 Standard 

1 1 1 2 2 2 2 2 

2 2 2 2 2 3 3 3 

3 1 1 2 2 2 2 2 

4 2 2 3 3 2 2 3 

5 2 1 3 3 2 3 2 

6 1 1 2 2 2 2 2 

7 2 1 3 3 3 3 3 

8 2 2 2 2 2 2 3 

9 1 1 2 2 3 3 1 

10 1 1 1 1 2 2 1 


False Alarms & Misses 

• Assess “Fail” when Standard = Pass: 

– False Alarm 

– Type I Error 

• Assess “Pass” when Standard = Fail: 

– Miss 

– Type II Error 


Results 

False 

Alarms 

Sample QA1-1 QA1-2 QA2-1 QA2-2 QA4-1 QA4-2 Standard 

1 1 1 2 2 2 2 2 

2 2 2 2 2 3 3 3 

3 1 1 2 2 2 2 2 

4 2 2 3 3 2 2 3 

MISSES 

5 2 1 3 3 2 3 2 

6 1 1 2 2 2 2 2 

7 2 1 3 3 3 3 3 

8 2 2 2 2 2 2 3 

9 1 1 2 2 3 3 1 

10 1 1 1 1 2 2 1 


Minitab 15 

• Four Results: 

1. Within 

2. Within vs. Standard 

3. Between 

4. Between vs. Standard 


Check Here 




Assessment Agreement 

Date of study: 

Reported by: 

Name of product: 

Misc: 

Within Appraisers 

Appraiser vs Standard 

100 

95.0% C I 

Percent 

100 

95.0% C I 

Percent 

80 

80 

Percent 

60 

40 

Percent 

60 

40 

20 

20 

0 

QA-1 

QA-2 

Appraiser 

QA-4 

0 

QA-1 

QA-2 

Appraiser 

QA-4 




Two Big Lessons 

• You can’t trust your data until it is proven 

to be trustworthy. 

• A single, one-time Gage R&R study is 

not enough 


Questions? 

• Thank You!

Attribute Gage R&R - ASQ-1302

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