© 2016 by Jay Arthur QI Macros Example Book80

Gage R&R

A gage R&R (repeatability and reproducibility)study evaluates your measurement system and not your products. In fact, you need bad parts to do a good gage R&R study.

qimacros.com/training/videos/gagerr-study

The QI Macros contains these gage R&R studies:

• Gage R&R Study: Measurement systems analysis (MSA) using Average & Range Method, along with the ANOVA Method

• Type 1 Gage R&R: 1 part x 1 appraiser x 50 measurements

• Range Method: Provides quick approximation of overall measurement variability

• Bias: Calculates the “bias” of your gage, using a “target” or “reference” value that you input

• Linearity: Calculates whether a gage over-reads or under- reads across a range of different sized parts

• Attribute Gage Worksheet: For Pass/Fail gages• Analytic Attribute Method: To assess the amount of repeatability and bias of a measurement sys-

tem

All of the gage R&R methods listed above can be accessed from the gage R&R worksheet tabs:Measurement System Analysis (MSA)

Measurement system analysis (MSA) involves gage R&R (repeatability and reproducibility) studies to evaluate your measurement systems.

qimacros.com/training/videos/msa-gagerr-qimacros-video

Gage R&R studies are usually performed on variable data - height, length, width, diameter, weight, viscosity, etc.

When you manufacture products, you want to monitor the output of your machines to make sure that they are producing products that meet your customer’s specifications. This means that you have to measure samples coming off the line to determine if they are meeting your customer’s requirements.

When you measure, three factors come into play:

1. Part variation (differences between individual pieces manufactured)2. Appraiser variation (aka, reproducibility) - Can two different people get the same measurement

using the same gage?3. Equipment variation (aka, repeatability) - Can the same appraiser get the same measurement

using the same gage on the same part in two or more trials?

© 2016 by Jay Arthur QI Macros Example Book81

Gage R&R MSA (Continued) You want most of the variation to be between the parts, and less than 10% of the variation to be caused by the appraisers and equipment. If the appraiser can’t get the same measurement twice, or two appraisers can’t get the same measurement, then your measurement system becomes a key source of error.To Conduct a Gage R&R Study, You Will Need:1. Five to ten parts (# each part) that span the distance between the upper and lower spec limits

The parts should represent the actual or expected range of process variation. Rule of thumb: Ifyou’re measuring to 0.0001, the range of parts should be 10 times the resolution (e.g., 0.4995 to0.5005).

2. Two appraisers (people who measure the parts)3. One measurement tool or gage4. A minimum of two measurement trials, on each part, by each appraiser

Here are samples of the gage R&R template input sheet and results sections using sample data from the AIAG Measurement Systems Analysis Third Edition:

Gage R&R System Acceptability

% R&R<10%: Gage system okay (most variation caused by parts, not people or equipment)

% R&R<30%: May be acceptable based on importance of appli-cation and cost of gage or repair

% R&R>30%: Gage system needs im-provement (people and equipment cause over 1/3 of variation)

NDC (Number of Distinct Categories) must be ≥ 5 to get a valid % gage R&R.

© 2016 by Jay Arthur QI Macros Example Book82

Gage R&R MSA (Continued) What To Look ForRepeatability: Percent equipment variation (%EV) — Can the same appraiser using the same gage measure the same thing consistently? If you look at the measurements, can each appraiser get the same result on the same part consistently, or is there too much variation?Example (looking at measurements from one appraiser only):

• No equipment variation: (Part 1: 0.65, 0.65; Part 2: 0.66, 0.66)• Equipment variation: (Part 1: 0.65, 0.67; Part 2: 0.67, 0.65)

If repeatability (equipment variation) is larger than reproducibility (appraiser variation), reasons in-clude:

1. Gage needs maintenance (gages can get corroded)2. Gage needs to be redesigned to be used more accurately3. Clamping of the part or gage, or where it’s measured needs to be improved (Imagine measuring

a baseball bat at various places along the tapered contour; you’ll get different results.)4. Excessive within-part variation (Imagine a steel rod that’s bigger at one end than the other. If you

measure different ends each time, you’ll get widely varying results.)Reproducibility: percent appraiser variation (% AV) — Can two appraisers measure the same thing and get the same answer?Example (looking at measurements of the same part by two appraisers):

• No appraiser variation: (Appraiser 1, Part 1: 0.65, 0.65; Appraiser 2, Part 1: 0.65, 0.65)• Appraiser variation: (Appraiser 1, Part 1: 0.65, 0.65; Appraiser 2, Part 1: 0.66, 0.66)

If you look at the line graph of appraiser performance, you’ll be able to tell if one appraiser over-reads or under reads the measurement. If reproducibility (appraiser variation) is larger than repeatability (equipment variation), reasons include:

1. Operators need to be better trained in a consistent method for using and reading the gage2. Calibrations on gage are unclear3. Fixture required to help the operator use gage more consistently

Mistakes People Make1. Forgetting that the gage R&R study is evaluating their measurement system and not their prod-

ucts. (Gage R&R does not care about how good your products are, it only cares about how well you measure your products.)

2. Using only one part (If you only use one part, there can’t be any part variation, so people and equipment are the only source of variation.)

3. Using the one part measurement for all 10 parts (Again, there won’t be any part variation, so it all falls on the people and equipment.)

4. Using too many trials (If you use five trials, you have more opportunity for equipment variation.)5. Using too many appraisers (If you use all three, you have more opportunity for appraiser varia-

tion.)6. Using fake data (Try using the AIAG SPC data the QI Macros loads on your computer at c:\

qimacros\testdata.)7. Using a gage that measures in too much detail (If your part is 74mm +/- 0.05, then you don’t

need a gage that measures to a thousandth of an inch (0.001), you only need one that measures to the hundredth of an inch (0.01).)

ConclusionYour goal is to minimize the amount of variation and error introduced by measurement, so that you can focus on part variation. This, of course, leads you back into the other root causes of variation: process, machines, and materials.

© 2016 by Jay Arthur QI Macros Example Book83

Gage R&RType 1

A typical gage R&R study uses 10 parts, 2–3 appraisers and 2–3 trials (3x3x10). A type 1 gage R&R study uses only one part, one appraiser, one gage and 50 trials (1x1x50).

To conduct a type 1 gage RR study using the QI Macros, open the type 1 template and enter the measurements, tolerance and reference value into the appropriate cells. The part must have a known reference value (measured independently to a high degree of accuracy) and USL, LSL or tolerance.

The QI Macros type 1 template will calculate the capability of the gage (Cg) and bias (Cgk). Values greater than 1.33 are considered acceptable. If values are less than 1.33, the measurement system needs improvement.

Your goal is to minimize the amount of variation and error introduced by measurement, so that you can focus on part variation. This, of course, leads you back into the other root causes of variation: process, machines, and materials.

© 2016 by Jay Arthur QI Macros Example Book84

Gage R&RRange Method (Short Form)

The range method provides a “quick approximation” of measurement variability. It will detect unac-ceptable measurement variation 80% of the time with five samples.

To conduct a gage R&R range method study, you will need:

• Five parts (# each part) that span the distance between the upper and lower spec limits. The partsshould represent the actual or expected range of process variation. Rule of thumb: If you’re measuring to 0.0001, the range of parts should be 10 times the resolution (e.g., 0.4995 to 0.5005).

• Two appraisers (people who measure the parts)

• One measurement tool or gage

• Two measurement trials, on each part, by each appraiser

Here is an example of the gage R&R range template input sheet and results sections using sample data from the AIAG’s Measurement Systems Analysis, Third Edition: Gage R&R System Acceptability

• % R&R<10% - Gage system okay (Most variation caused by parts, not people or equipment)

• % R&R<30% - May be acceptable based on importance of application and cost of gage or repair

• % R&R>30% - Gage system needs improvement (People and equipment cause over 1/3 of varia-tion)

If the %R&R is greater than 10%, use the long form gage R&R to determine if it’s an appraiser or an equipment issue.

© 2016 by Jay Arthur QI Macros Example Book85

Gage R&RBias and Linearity

Bias and linearity are two factors that can affect the accuracy of your measurement system.

Bias: Does your gage tend to over-read or under-read the same size part? (Imagine measuring the length or diameter of a steel rod with known dimensions.)

If you want to know the “bias” of your gage, simply input the “target” or “reference” value for the parts being measured into B2 and your measure-ments into column A. The QI Macros gage R&R template will calculate the bias of the gage (plus or minus).

Linearity: Does your gage over-read or under-read across a range of different sized parts? (Imagine using the gage on tin cans of various diameters, from small, 6 oz. juice cans to 64 oz., family-sized cans.)

To conduct a linearity study, you will need five parts of different sizes that have been accurately measured.

• Have each of the five parts mea-sured 12 times.

• Input the data into the QI Macros gage R&R linearity template.

• Input the accurate measurements for each part as reference values in row 16.

• Analyze the linearity using the line graph on the worksheet.

Ideally, there shouldn’t be any change in bias from small to large. If you look at the line graph, it should be a horizontal line. More often, however, a gage may over-read the small and under-read the large. If there is too much slope to the line (too much bias), you may want to use the gage in its opti-mal range and find other gages to measure where this gage’s bias is too large.

Your goal is to minimize the amount of variation and error introduced by measurement so that you can focus on part variation. This, of course, leads you back into the other root causes of variation: process, machines, and materials. If you manufacture anything, measurement system analysis can help you improve the quality of your products.

© 2016 by Jay Arthur QI Macros Example Book86

Gage R&RAttribute

The QI Macros attribute gage R&R template is compatible with the AIAG MSA, 4th Edition.

Perform an attribute gage R&R study:• When the measurement value has only two possible results: go/no go, pass/fail, etc.• This differs from a variables measurement system when you can have any number of possible

results.

To perform an attribute gage R&R study using the QI Macros:

1. Determine the upper and lower spec limits. Enter these in cells N3:O3 of the QI Macros template:

2. Select 10 parts and measure them accurately to get a reference value for each. Enter the ref-erence values in column L. If you do not have reference values to input (column L), you may specify 1 or 0 for each part.

Important: The 10 parts must have an actual reference value spanning unacceptable low to unacceptable high.

3. Have three appraisers accept/reject 10+ parts with at least three trials.

4. Enter pass/fail in columns B-J. 1 = pass (the value is between the spec limits) and 0 = Fail (value is outside of the spec limits).

Use the analytic attribute method to assess the amount of repeatability and bias of a measurement system.