SixSigma (version 0.9-2)

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

Description

Performs Gage R&R analysis for the assessment of the measurement 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, ...)

lsl

Numeric value of lower specification limit used with USL to calculate Study Variation as %Tolerance

usl

Numeric value of upper specification limit used with LSL to calculate Study Variation as %Tolerance

sigma

Numeric value for number of std deviations to use in calculating Study Variation

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)

Value

• Analysis of Variance Table. Variance composition and %Study Var. Graphics.
• anovaTable
  The ANOVA table of the model
• varComp
  A matrix with the contribution of each component to the total variation
• studyVar
  A matrix with the contribution to the study variation
• ncat
  Number 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-bar and R control charts.

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.

See Also

ss.data.rr

Examples

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