Gage R&R - Gage Repeatability and Reproducibility

Description

Performs a Gage R&R analysis for an object of class gageRR.

Usage

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gageRR(gdo, method = "crossed", sigma = 6, alpha = 0.25, DM = NULL,
       HM = NULL, tolerance = NULL, dig = 3, ...)

Arguments

gdo

needs to be an object of class gageRR.

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

numeric value giving the number of sigmas.
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’.

alpha

alpha value for discarding the interaction Operator:Part and fitting a non-interaction model. By default alpha is set to ‘0.25’.

DM

By default DM is set to ‘NULL’.

HM

By default HM is set to ‘NULL’.

tolerance

numeric value giving the tolerance for the measured parts. This is required to calculate the Process to Tolerance Ratio.
By default tolerance is set to ‘NULL’.

dig

numeric value giving the number of significant digits for format.
By default dig is set to ‘3’.

...

further graphical parameters(see par

Value

gageRR() returns an object of class gageRR and shows typical Gage Repeatability and Reproducibility Output including Process to Tolerance Ratios and the number of distinctive categories (i.e. ndc) the measurement system is able to discriminate with the tested setting.

Note

For an example in context which shows the usage of the function gageRR() 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

gageLin
cg
gageRRDesign
response
cg
http://www.r-qualitytools.org/html/Measure.html

Examples

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#create a crossed Gage R&R Design
gdo = 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(gdo) = y

#perform a Gage R&R
gdo = gageRR(gdo, tolerance = 5)

#summary
summary(gdo)

#standard graphics for Gage R&R
plot(gdo)


##create a crossed Gage R&R Design - 
##Vardeman, VanValkenburg 1999 - Two-Way Random-Effects Analyses and Gauge
#gdo = gageRRDesign(Operators = 5, Parts = 2, Measurements = 3, randomize = FALSE)
#
##Measurements
#weight = c(3.481, 3.448, 3.485, 3.475, 3.472,
#           3.258, 3.254, 3.256, 3.249, 3.241,
#           3.477, 3.472, 3.464, 3.472, 3.470,
#           3.254, 3.247, 3.257, 3.238, 3.250,
#           3.470, 3.470, 3.477, 3.473, 3.474,
#           3.258, 3.239, 3.245, 3.240, 3.254)
#
##set the response i.e. Measurements
#response(gdo) = weight
#
##perform a Gage R&R
#gdo = gageRR(gdo)
#
##summary
#summary(gdo)
#
##standard graphics for Gage R&R
#plot(gdo)
#

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