gageRRDesign: Gage R&R - Gage Repeatability and Reproducibility
In qualityTools: Statistical Methods for Quality Science
Description
Usage
Arguments
Value
Note
Author(s)
See Also
Examples
Description
Creates a Gage R&R design.
Usage
1
2
gageRRDesign(Operators = 3, Parts = 10, Measurements = 3, method = "crossed",
sigma = 6, randomize = TRUE)
Arguments
Operators
numeric value giving a number or a character vector defining the Operators.
By default Operators is set to ‘3’.
Parts
a number or character vector defining the Parts.
By default parts is set to ‘10’.
Measurements
a number defining the measurements per part.
By default Measurments is set to ‘3’.
method
“crossed” which is the typical design for performing a Measurement Systems
Analysis using Gage Repeatability and Reproducibility or “nested” which is used
for destructive testing (i.e. the same part cannot be measured twice). Operators
measure each a different sample of parts under the premise that the parts of each
batch are alike.
By default method is set to “crossed”.
sigma
For sigma=6 this relates to 99.73 percent representing the full spread of a normal distribution function (i.e. pnorm(3) - pnorm(-3)).
Another popular setting sigma=5.15 relates to 99 percent (i.e. pnorm(2.575) - pnorm(-2.575)).
By default sigma is set to ‘6’.
randomize
logicalvalue. ‘TRUE’ (default) randomizes the gageRR design.
Value
gagRRDeign returns an object of class gageRR.
Note
For an example in context which shows the usage of the function gageRRDesign()
please read the vignette for the package qualityTools at http://www.r-qualitytools.org/html/Measure.html.
Author(s)
Thomas Roth thomas.roth@tu-berlin.de
See Also
gageRR
http://www.r-qualitytools.org/html/Measure.html
Examples
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#create a Gage R&R Design
temp = gageRRDesign(3,10, 2, randomize = FALSE)
#set the response i.e. Measurements
y = c(23,22,22,22,22,25,23,22,23,22,20,22,22,22,24,25,27,28,23,24,23,24,24,22,
22,22,24,23,22,24,20,20,25,24,22,24,21,20,21,22,21,22,21,21,24,27,25,27,
23,22,25,23,23,22,22,23,25,21,24,23)
response(temp) = y
#perform a Gage R&R
gdo = gageRR(temp)
#summary
summary(gdo)
#standard graphics for Gage R&R
plot(gdo)
Example output
Loading required package: Rsolnp
Loading required package: MASS
Attaching package: 'qualityTools'
The following object is masked from 'package:stats':
sigma
AnOVa Table - crossed Design
Df Sum Sq Mean Sq F value Pr(>F)
Operator 2 20.63 10.317 8.597 0.00112 **
Part 9 107.07 11.896 9.914 7.31e-07 ***
Operator:Part 18 22.03 1.224 1.020 0.46732
Residuals 30 36.00 1.200
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
----------
AnOVa Table Without Interaction - crossed Design
Df Sum Sq Mean Sq F value Pr(>F)
Operator 2 20.63 10.317 8.533 0.000675 ***
Part 9 107.07 11.896 9.840 2.39e-08 ***
Residuals 48 58.03 1.209
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
----------
Gage R&R
VarComp VarCompContrib Stdev StudyVar StudyVarContrib
totalRR 1.664 0.483 1.290 7.74 0.695
repeatability 1.209 0.351 1.100 6.60 0.592
reproducibility 0.455 0.132 0.675 4.05 0.364
Operator 0.455 0.132 0.675 4.05 0.364
Operator:Part 0.000 0.000 0.000 0.00 0.000
Part to Part 1.781 0.517 1.335 8.01 0.719
totalVar 3.446 1.000 1.856 11.14 1.000
---
* Contrib equals Contribution in %
**Number of Distinct Categories (truncated signal-to-noise-ratio) = 1
Operators: 3 Parts: 10
Measurements: 2 Total: 60
----------
AnOVa Table - crossed Design
Df Sum Sq Mean Sq F value Pr(>F)
Operator 2 20.63 10.317 8.597 0.00112 **
Part 9 107.07 11.896 9.914 7.31e-07 ***
Operator:Part 18 22.03 1.224 1.020 0.46732
Residuals 30 36.00 1.200
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
----------
AnOVa Table Without Interaction - crossed Design
Df Sum Sq Mean Sq F value Pr(>F)
Operator 2 20.63 10.317 8.533 0.000675 ***
Part 9 107.07 11.896 9.840 2.39e-08 ***
Residuals 48 58.03 1.209
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
----------
Gage R&R
VarComp VarCompContrib Stdev StudyVar StudyVarContrib
totalRR 1.664 0.483 1.290 7.74 0.695
repeatability 1.209 0.351 1.100 6.60 0.592
reproducibility 0.455 0.132 0.675 4.05 0.364
Operator 0.455 0.132 0.675 4.05 0.364
Operator:Part 0.000 0.000 0.000 0.00 0.000
Part to Part 1.781 0.517 1.335 8.01 0.719
totalVar 3.446 1.000 1.856 11.14 1.000
---
* Contrib equals Contribution in %
**Number of Distinct Categories (truncated signal-to-noise-ratio) = 1
qualityTools documentation built on May 2, 2019, 10:21 a.m.
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Description Usage Arguments Value Note Author(s) See Also Examples
Description
Creates a Gage R&R design.
Usage
1 2 | gageRRDesign(Operators = 3, Parts = 10, Measurements = 3, method = "crossed",
sigma = 6, randomize = TRUE)
|
Arguments
Operators |
numeric value giving a number or a character vector defining the Operators. |
Parts |
a number or character vector defining the Parts. |
Measurements |
a number defining the measurements per part.
By default |
method |
“crossed” which is the typical design for performing a Measurement Systems
Analysis using Gage Repeatability and Reproducibility or “nested” which is used
for destructive testing (i.e. the same part cannot be measured twice). Operators
measure each a different sample of parts under the premise that the parts of each
batch are alike. |
sigma |
For sigma=6 this relates to 99.73 percent representing the full spread of a normal distribution function (i.e. pnorm(3) - pnorm(-3)). |
randomize |
logicalvalue. ‘TRUE’ (default) randomizes the gageRR design. |
Value
gagRRDeign returns an object of class gageRR.
Note
For an example in context which shows the usage of the function gageRRDesign()
please read the vignette for the package qualityTools at http://www.r-qualitytools.org/html/Measure.html.
Author(s)
Thomas Roth thomas.roth@tu-berlin.de
See Also
gageRR
http://www.r-qualitytools.org/html/Measure.html
Examples
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 | #create a Gage R&R Design
temp = gageRRDesign(3,10, 2, randomize = FALSE)
#set the response i.e. Measurements
y = c(23,22,22,22,22,25,23,22,23,22,20,22,22,22,24,25,27,28,23,24,23,24,24,22,
22,22,24,23,22,24,20,20,25,24,22,24,21,20,21,22,21,22,21,21,24,27,25,27,
23,22,25,23,23,22,22,23,25,21,24,23)
response(temp) = y
#perform a Gage R&R
gdo = gageRR(temp)
#summary
summary(gdo)
#standard graphics for Gage R&R
plot(gdo)
|
Example output
Loading required package: Rsolnp
Loading required package: MASS
Attaching package: 'qualityTools'
The following object is masked from 'package:stats':
sigma
AnOVa Table - crossed Design
Df Sum Sq Mean Sq F value Pr(>F)
Operator 2 20.63 10.317 8.597 0.00112 **
Part 9 107.07 11.896 9.914 7.31e-07 ***
Operator:Part 18 22.03 1.224 1.020 0.46732
Residuals 30 36.00 1.200
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
----------
AnOVa Table Without Interaction - crossed Design
Df Sum Sq Mean Sq F value Pr(>F)
Operator 2 20.63 10.317 8.533 0.000675 ***
Part 9 107.07 11.896 9.840 2.39e-08 ***
Residuals 48 58.03 1.209
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
----------
Gage R&R
VarComp VarCompContrib Stdev StudyVar StudyVarContrib
totalRR 1.664 0.483 1.290 7.74 0.695
repeatability 1.209 0.351 1.100 6.60 0.592
reproducibility 0.455 0.132 0.675 4.05 0.364
Operator 0.455 0.132 0.675 4.05 0.364
Operator:Part 0.000 0.000 0.000 0.00 0.000
Part to Part 1.781 0.517 1.335 8.01 0.719
totalVar 3.446 1.000 1.856 11.14 1.000
---
* Contrib equals Contribution in %
**Number of Distinct Categories (truncated signal-to-noise-ratio) = 1
Operators: 3 Parts: 10
Measurements: 2 Total: 60
----------
AnOVa Table - crossed Design
Df Sum Sq Mean Sq F value Pr(>F)
Operator 2 20.63 10.317 8.597 0.00112 **
Part 9 107.07 11.896 9.914 7.31e-07 ***
Operator:Part 18 22.03 1.224 1.020 0.46732
Residuals 30 36.00 1.200
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
----------
AnOVa Table Without Interaction - crossed Design
Df Sum Sq Mean Sq F value Pr(>F)
Operator 2 20.63 10.317 8.533 0.000675 ***
Part 9 107.07 11.896 9.840 2.39e-08 ***
Residuals 48 58.03 1.209
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
----------
Gage R&R
VarComp VarCompContrib Stdev StudyVar StudyVarContrib
totalRR 1.664 0.483 1.290 7.74 0.695
repeatability 1.209 0.351 1.100 6.60 0.592
reproducibility 0.455 0.132 0.675 4.05 0.364
Operator 0.455 0.132 0.675 4.05 0.364
Operator:Part 0.000 0.000 0.000 0.00 0.000
Part to Part 1.781 0.517 1.335 8.01 0.719
totalVar 3.446 1.000 1.856 11.14 1.000
---
* Contrib equals Contribution in %
**Number of Distinct Categories (truncated signal-to-noise-ratio) = 1
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