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Last data update: 2014.03.03

R: Loss Function Analysis

ss.lfa

R Documentation

Loss Function Analysis

Description

This function performs a Quality Loss Function Analysis, based in the Taguchi Loss Function for "Nominal-the-Best" characteristics.

Usage

ss.lfa(lfa.data, lfa.ctq, lfa.Delta, lfa.Y0, lfa.L0, lfa.size = NA,
  lfa.output = "both", lfa.sub = "Six Sigma Project")

Arguments

`lfa.data`	Data frame with the sample to get the average loss.
`lfa.ctq`	Name of the field in the data frame containing the data.
`lfa.Delta`	Tolerance of the process.
`lfa.Y0`	Target of the process (see note).
`lfa.L0`	Cost of poor quality at tolerance limit.
`lfa.size`	Size of the production, batch, etc. to calculate the total loss in a group (span, batch, period, ...)
`lfa.output`	Type of output (see details).
`lfa.sub`	Subtitle for the graphic output.

Details

lfa.output can take the values "text", "plot" or "both".

Value

`lfa.k`	Constant k for the loss function
`lfa,lf`	Expression with the loss function
`lfa.MSD`	Mean Squared Differences from the target
`lfa.avLoss`	Average Loss per unit of the process
`lfa.Loss`	Total Loss of the process (if a size is provided)

Note

For smaller-the-better characteristics, the target should be zero (lfa.Y0 = 0). For larger-the-better characteristics, the target should be infinity (lfa.Y0 = Inf).

Author(s)

EL Cano

References

Taguchi G, Chowdhury S,Wu Y (2005) Taguchi's quality engineering handbook. John Wiley

Cano, Emilio L., Moguerza, Javier M. and Redchuk, Andres. 2012. Six Sigma with R. Statistical Engineering for Process Improvement, Use R!, vol. 36. Springer, New York. http://www.springer.com/statistics/book/978-1-4614-3651-5.

Examples

ss.lfa(ss.data.bolts, "diameter", 0.5, 10, 0.001, 
		lfa.sub = "10 mm. Bolts Project", 
		lfa.size = 100000, lfa.output = "both")

Results


R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(SixSigma)
> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/SixSigma/ss.lfa.Rd_%03d_medium.png", width=480, height=480)
> ### Name: ss.lfa
> ### Title: Loss Function Analysis
> ### Aliases: ss.lfa
> ### Keywords: Taguchi function loss
> 
> ### ** Examples
> 
> ss.lfa(ss.data.bolts, "diameter", 0.5, 10, 0.001, 
+ 		lfa.sub = "10 mm. Bolts Project", 
+ 		lfa.size = 100000, lfa.output = "both")
$lfa.k
[1] 0.004

$lfa.lf
expression(bold(L == 0.004 %.% (Y - 10)^2))

$lfa.MSD
[1] 0.03372065

$lfa.avLoss
[1] 0.0001348826

$lfa.Loss
[1] 13.48826

> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>