ss.rr: Gage R & R (Measure System Assessment)

Description

Performs Gage R&R analysis for the assessment of the measure system of a process. Related to the Measure phase of the DMAIC strategy of Six Sigma.

Usage

ss.rr(var, part, appr, lsl = NA, usl = NA, sigma = 5.15,
  data = "stop('Data' is required for lattice graphics)",
  main = "Six Sigma Gage R&R Study", sub = "")

Arguments

var

Measured variable

part

Factor for parts

appr

Factor for appraisers (operators, machines, ...)

data

Data frame containing the variates

main

Main title for the graphic output

sub

Subtitle for the graphic output (recommended the name of the project)

lsl

Numeric value of lower specification limit used with USL to calculate Study Variation as KCL 2014-02-11

usl

Numeric value of upper specification limit used with LSL to calculate Study Variation as KCL 2014-02-11

sigma

Numeric value for number of std deviations to use in calculating study variation. KCL 2014-02-11

Value

Analysis of Variance Table. Variance composition and %Study Var. Graphics.
anovaTableThe ANOVA table of the model
varCompA matrix with the contribution of each component to the total variation
studyVarA matrix with the contribution to the study variation
ncatNumber of distinct categories

Details

Performs an R&R study for the measured variable, taking into account part and appraiser factors. It outputs the sources of Variability, and six graphs: bar chart with the sources of Variability, plots by appraiser, part and interaction and x-mean and R control charts. Updates to code by Kevin C Limburg 2014-02-11 1. Input of tolerance to calculate variance as a percent of tolerance and adding that to the Components of Variation bar chart. 2. Adjustment of the study variation sigma level (currently set to 5.15) by passing it as an argument in the function that is defaulted to 5.15 3. Allow support for single appraiser

References

Allen, T. T. (2010). Introduction to Engineering Statistics and Lean Six Sigma - Statistical Quality Control and Design of Experiments and Systems (Second Edition ed.). London: Springer. Automotive Industry Action Group. (2010). Measurement Systems Analysis (Fourth Edition). AIAG. 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. Montgomery, D. C. (2008). Introduction to Statistical Quality Control (Sixtth Edition ed.). New York: Wiley & Sons, Inc.

Examples

Run this code

data(ss.data.rr)
ss.rr(time1, prototype, operator, data=ss.data.rr,
	sub="Six Sigma Paper Helicopter Project")

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