[PDF] Report Example: Gage R&R Nested ANOVA Report





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Through this GR&R laboratory exercise students learned the concept of variation in measurements





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Report Example: Gage R&R ANOVA Report

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Report Example: Gage R&R ANOVA Report

Gage R&R. 0.0914. 1.46%. Repeatability. 0.0400. 0.64%. Reproducibility. 0.0515. 0.82%. Operator. 0.0515. 0.82%. Part-to-Part. 6.159. 98.54%. Total Variance.



Report Example: Gage R&R Nested ANOVA Report

% Gage R&R > 9%: measurement system is not acceptable. Source. Standard. Deviation. (SD). Study Var. (6SD). % Study Var.



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Report Example: Gage R&R Nested ANOVA Report - SPC for Excel

The R chart shows the results for the repeated measurements for each operator for each sample It is a check of the consistency of the measurement process between the operators There are 0 out of control points on the R chart The ranges are consistent There are 26 5 degrees of freedom associated with the average range



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The Gage R&R Study (Crossed) command in the Assistant is designed to analyze data from typical measurement system studies It adopts the most common approach of fitting the measurement data with an ANOVA model and estimates different sources of variation in the measurement system using the variance components in the model

What does a gage R&R study look like?

  • An example of a Gage R&R study using the Xbar and R chart method Three appraisers measure ten parts at random over two trials. The averages and ranges of each appraiser’s measurements are taken for each part. Here’s a snapshot of the data from the MoreSteam Gage R&R spreadsheet template:

What is type I gage study?

  • In that case, a different format of GRR study is recommended known as Type I gage study or precision to tolerance ratio (P/T ratio). In simple terms, a Type I gage study is used to understand the precision and accuracy of measurement system without considering other sources of variation such as operators or parts.

What is the P/T ratio of an Instron® Gage?

  • The P/T value indicated by the parameter “%Var (Repeatability)” is 7.12%. Based on guidelines from AIAG, the P/T ratio is below 10% and therefore it can be concluded that the gage is capable of measurement. This concludes the detailed overview of the GRR studies that are important when understanding an Instron® system’s measurement capabilities.

Date: 7/27/2018Process Sigma: 2

Gage: My GageUSL: 125

Characteristic: ThicknessLSL: 115

Operators: 3Analyzed by: Bill

Batches: 10

Samples/Batch: 2

SourcedfSSMSFp Value

Operator22.6681.3340.2820.7563

Batch (Operator)27127.94.73721.7220.0000

Repeatability306.5430.218

Total59137.1

Source: the source of the variation.

df (degrees of freedom) = a measure of how much information you have for each SS. SS (sum of squares) = a measure of variation of squared deviations around an average. MS (mean square) = estimate of the variance for the source based on the degrees of freedom.

F: the statistic is used to determine whether the sources of variation are statistically significant.

p-value: is the probability that the source of variation is not statistically significant. Sources with low p values have a statistically significant impact on the results.

Red p values are less than 0.05.

SourceVariance% Contr.

Gage R&R0.2185.45%

Repeatability0.2185.45%

Reproducibility0.0000.00%

Batch-to-Batch3.78294.55%

Total Variance4.000100.00%

Table provides the % variance due to each source based on the total variance. Total variance based on process sigma entered by user.

AIAG Guidelines for Total Gage R&R:

% Gage R&R& < 1%: measurement system is acceptable. % Gage R&R 1% to 9%: measurement system may be acceptable for some applications. % Gage R&R > 9%: measurement system is not acceptable.

Source

Standard

Deviation

(SD)

Study Var

(6SD)% Study Var% Tolerance (SV/Tol)

Gage R&R0.4672.80223.35%28.02%

Repeatability0.4672.80223.35%28.02%

Reproducibility0.0000.0000.00%0.00%

Batch-to-Batch1.94511.6797.24%116.68%

Total Variation2.00012.00100.00%120.00%

Table gives the % of spread consumed by each source based on the total variation. Total variation based on process sigma entered by user.

AIAG Guidelines for Gage R&R:

% Gage R&R& < 10%: measurement system is acceptable. % Gage R&R 10% to 30%: measurement system may be acceptable for some applications. % Gage R&R > 30%: measurement system is not acceptable. NDC represents the ability of the measurement systems to distinguish between batches.

AIAG Guidelines: NDC greater than or equal to 5.

Number of Distinct Categories (NDC) = 5

Description of Output

Print out of information entered by the user

The Analysis of Variance table is given; the

sources are defined below the table. The column to focus on is the p Value column. Values less than 0.05 are considered statistically significant and are turned red.

Each source's variance is calculated and the %

contribution of each source is determined. The % contribution is the % of the total variance. If the process sigma is entered by the user, it is used to determine the total variance. If not, the batches and samples used in the study are used to determine the total variance.

AIAG guidelines are used to determine if the

measurement system is acceptable.

The standard deviation from each source is

calculated. The study variation is calculated as 6 times the standard deviation. The % of total study variation is calculated for each source. If the process sigma is entered by the user, it is used for the total variation standard deviation.

If not, the batches and the samples used in the

study are used to determine the total variation standard deviation.

AIAG guidelines are used to determine if the

measurement system is acceptable.

Report Example: Gage R&R Nested ANOVA Report

ANOVA Table

% Contribution Based on Variance % Based on Standard Deviation

Number of Distinct Categories

Variance Components Chart

The number of distinct categories is the number

of data classifications that can be reliably distinguished by the resolution of the test method.

The % of variance and variation are plotted for

each source. This is a chart of the results in the two tables above. 94.5%

23.4%23.4%

97.2%

28.0%28.0%

116.7%

40%
60%
80%
100%
120%
140%
% Contr. % Study Var % Tolerance (SV/Tol) ิChart for Operator-Batch Averages

R Chart for Operator-Batch Ranges

Control Chart Calculations

ิChartճLCL = ճ- A2ิUCL = ճ+ A2ิ

120.5119.5121.5

R ChartิLCL = D3ิUCL = D4ิ

0.535-1.749

where A2, D3, and D4 are control chart constants depending on subgroup size.

A2D3D4

1.881-3.267

ิChart Analysis The ิchart shows the average value for each operator for each batch. The control limits on the ิchart are based on the average range. The average range is representative of measurement error. The ิchart control limits represent the variation obscured by measurement error. The relative utility of the measurement system increases: * The more out of control points there on are on the ิchart. * The further the out of control points are away from the control limits.

16 out of 30 points are out of control on the chart.

R Chart Analysis

The R chart shows the results for the repeated measurements for each operator for each sample. It is a check of the consistency of the measurement process between the operators.

There are 0 out of control points on the R chart.

The ranges are consistent.

There are 26.5 degrees of freedom associated with the average range. It is recommended to have at least 10 degrees of freedom. Look for the effects of operators on variation and for outliers. The ิchart is analyzed. The control limits on this chart are based on the average range from the range chart. This average range represents measurement variability. If the test method is good, the measurement variability should be small. So, the average range should be small and the control limits should be tight around the average. The more out of control points the better.

Operator-Batch Control Charts

Run Chart by Operator

The % of variance and variation are plotted for

each source. This is a chart of the results in the two tables above. The ิchart is a plot of the subgroup averages for the operator-batch number combinations.

The first subgroup is made up the results that

Operator "1" got for batch 21. This operator ran

two samples from this batch.

The average and control limits are calculated

and added to the chart. The control limits on this chart depend on the average range from the range chart (see below). The R chart is a plot of the range of values within each operator-batch number subgroup. Each range value is a measure of the repeatability of the test method. The average range and control limits are calculated and added to the chart.

The control chart calculations are given.

The R chart is analyzed. This checks the

consistency between the operators. There should be no out of control points. If there are, the reason should be found and eliminated and the study repeated.

The study should contain sufficient data

(degrees of freedom). This is checked here. This chart is optional. The plots the results for each operator. The average of each operator is connected by the blue line. Look for outliers and differences between operators.

5.5%5.5%0.0%

23.4%23.4%

0.0%

28.0%28.0%

0.0%0%

20% 40%
Gage R&RRepeatabilityReproducibilityBatch-to-Batch

AvgUCL

LCL

116117118119120121122123124

123

Average

Operator-Part Number

Avg UCL

00.20.40.60.811.21.41.61.8

123
Range

Operator-Part Number

122
124
Look at variation within a subgroup and differences in operators.

Run No.OperatorBatchSampleResult

411211118.89

421212118.67

431221122.91

441222123.31

451231121.45

461232120.27

471241120.17

481242120.11

491251120.37

501252119.83

511261120.31

521262121.25

531271118.05

541272118.91

551281121.64

561282121.24

571291122.23

581292121.78

591301119.68

601302119.41

212111122.22

222112122.46

232121119.25

242122119.68

252131120.14

262132119.79

272141120.2

282142121.66

292151115.95

302152117.32

312161122.21

322162121.52

332171122.3

342172121.05

352181119.41

362182119.98

372191119.35

Run Chart by Batch(Operator)

Data

Optional Data Table

This chart is optional. The plots the results for each operator. The average of each operator is connected by the blue line. Look for outliers and differences between operators.

This chart is optional. It plots the individual

sample results and subgroup averages (blue triangles connected by lines). Look for variation within subgroups and difference in operators. 114
116
118
120
122
123
Value

Operator

114
116
118
120
122
124
123
Value

Operator-Batch

382192119.58

392201121.11

402202120.53

1311118.44

2312118.32

3321118.9

4322118.42

5331120.07

6332119.86

7341122.02

8342121.76

9351121.48

10352121.17

11361123.26

12362122.92

13371121.82

14372122.72

15381120.23

16382120.1

17391120.68

18392120.64

193101121.22

203102122

quotesdbs_dbs11.pdfusesText_17
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