SixSigma package - Quality Control with R

In this section you can find links to the R package page at CRAN and the PDF manual. See examples of the functions in the package below.

Package examples

library(SixSigma)
packageVersion("SixSigma")
## [1] '0.9.3'
example("SixSigma-package")
## 
## SxSgm-> example(ss.ci)
## 
## ss.ci> ss.ci(len, data=ss.data.strings, alpha = 0.05,
## ss.ci+   sub = "Guitar Strings Test | String Length", 
## ss.ci+   xname = "Length")
## 	Mean = 950.016; sd = 0.267
## 	95% Confidence Interval= 949.967 to 950.064
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##       LL       UL 
## 949.9674 950.0640 
## 
## SxSgm-> example(ss.study.ca)
## 
## ss.st.> 	ss.study.ca(ss.data.ca$Volume, rnorm(40, 753, 3), 
## ss.st.+ 		LSL = 740, USL = 760, T = 750, alpha = 0.05, 
## ss.st.+  			f.sub = "Winery Project")
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## 
## SxSgm-> example(ss.rr)
## 
## ss.rr> ss.rr(time1, prototype, operator, data = ss.data.rr, 
## ss.rr+ 	sub = "Six Sigma Paper Helicopter Project", 
## ss.rr+ 	alphaLim = 0.05,
## ss.rr+ 	errorTerm = "interaction")
## Complete model (with interaction):
## 
##                    Df Sum Sq Mean Sq F value  Pr(>F)
## prototype           2 1.2007  0.6004  28.797 0.00422
## operator            2 0.0529  0.0265   1.270 0.37415
## prototype:operator  4 0.0834  0.0208   0.974 0.44619
## Repeatability      18 0.3854  0.0214                
## Total              26 1.7225                        
## 
## alpha for removing interaction: 0.05 
## 
## 
## Reduced model (without interaction):
## 
##               Df Sum Sq Mean Sq F value   Pr(>F)
## prototype      2 1.2007  0.6004  28.174 8.56e-07
## operator       2 0.0529  0.0265   1.242    0.308
## Repeatability 22 0.4688  0.0213                 
## Total         26 1.7225                         
## 
## Gage R&R
## 
##                     VarComp %Contrib
## Total Gage R&R    0.0218823    25.38
##   Repeatability   0.0213088    24.71
##   Reproducibility 0.0005735     0.67
##     operator      0.0005735     0.67
## Part-To-Part      0.0643389    74.62
## Total Variation   0.0862212   100.00
## 
##                       StdDev  StudyVar %StudyVar
## Total Gage R&R    0.14792667 0.8875600     50.38
##   Repeatability   0.14597534 0.8758520     49.71
##   Reproducibility 0.02394786 0.1436872      8.16
##     operator      0.02394786 0.1436872      8.16
## Part-To-Part      0.25365114 1.5219068     86.38
## Total Variation   0.29363447 1.7618068    100.00
## 
## Number of Distinct Categories = 2
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## 
## SxSgm-> example(ss.lf)
## 
## ss.lf> #Example bolts: evaluate LF at 10.5 if Target=10, Tolerance=0.5, L_0=0.001
## ss.lf> ss.lf(10.5, 0.5, 10, 0.001)
## [1] 5e-04
## 
## SxSgm-> example(ss.lfa)
## 
## ss.lfa> ss.lfa(ss.data.bolts, "diameter", 0.5, 10, 0.001, 
## ss.lfa+ 		lfa.sub = "10 mm. Bolts Project", 
## ss.lfa+ 		lfa.size = 100000, lfa.output = "both")
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## $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
## 
## 
## SxSgm-> example(ss.ceDiag)
## 
## ss.cDg> effect <- "Flight Time"
## 
## ss.cDg> causes.gr <- c("Operator", "Environment", "Tools", "Design", 
## ss.cDg+   "Raw.Material", "Measure.Tool")
## 
## ss.cDg> causes <- vector(mode = "list", length = length(causes.gr))
## 
## ss.cDg> causes[1] <- list(c("operator #1", "operator #2", "operator #3"))
## 
## ss.cDg> causes[2] <- list(c("height", "cleaning"))
## 
## ss.cDg> causes[3] <- list(c("scissors", "tape"))
## 
## ss.cDg> causes[4] <- list(c("rotor.length", "rotor.width2", "paperclip"))
## 
## ss.cDg> causes[5] <- list(c("thickness", "marks"))
## 
## ss.cDg> causes[6] <- list(c("calibrate", "model"))
## 
## ss.cDg> ss.ceDiag(effect, causes.gr, causes, sub = "Paper Helicopter Project")
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## 
## SxSgm-> example(ss.pMap)
## 
## ss.pMp> inputs.overall<-c("operators", "tools", "raw material", "facilities")
## 
## ss.pMp> outputs.overall<-c("helicopter")
## 
## ss.pMp> steps<-c("INSPECTION", "ASSEMBLY", "TEST", "LABELING")
## 
## ss.pMp> #Inputs of process "i" are inputs of process "i+1"
## ss.pMp> input.output<-vector(mode="list",length=length(steps))
## 
## ss.pMp> input.output[1]<-list(c("sheets", "..."))
## 
## ss.pMp> input.output[2]<-list(c("sheets"))
## 
## ss.pMp> input.output[3]<-list(c("helicopter"))
## 
## ss.pMp> input.output[4]<-list(c("helicopter"))
## 
## ss.pMp> #Parameters of each process
## ss.pMp> x.parameters<-vector(mode="list",length=length(steps))
## 
## ss.pMp> x.parameters[1]<-list(c(list(c("width", "NC")),list(c("operator", "C")),
## ss.pMp+ list(c("Measure pattern", "P")), list(c("discard", "P"))))
## 
## ss.pMp> x.parameters[2]<-list(c(list(c("operator", "C")),list(c("cut", "P")),
## ss.pMp+ list(c("fix", "P")), list(c("rotor.width", "C")),list(c("rotor.length",
## ss.pMp+ "C")), list(c("paperclip", "C")), list(c("tape", "C"))))
## 
## ss.pMp> x.parameters[3]<-list(c(list(c("operator", "C")),list(c("throw", "P")),
## ss.pMp+ list(c("discard", "P")), list(c("environment", "N"))))
## 
## ss.pMp> x.parameters[4]<-list(c(list(c("operator", "C")),list(c("label", "P"))))
## 
## ss.pMp> x.parameters
## [[1]]
## [[1]][[1]]
## [1] "width" "NC"   
## 
## [[1]][[2]]
## [1] "operator" "C"       
## 
## [[1]][[3]]
## [1] "Measure pattern" "P"              
## 
## [[1]][[4]]
## [1] "discard" "P"      
## 
## 
## [[2]]
## [[2]][[1]]
## [1] "operator" "C"       
## 
## [[2]][[2]]
## [1] "cut" "P"  
## 
## [[2]][[3]]
## [1] "fix" "P"  
## 
## [[2]][[4]]
## [1] "rotor.width" "C"          
## 
## [[2]][[5]]
## [1] "rotor.length" "C"           
## 
## [[2]][[6]]
## [1] "paperclip" "C"        
## 
## [[2]][[7]]
## [1] "tape" "C"   
## 
## 
## [[3]]
## [[3]][[1]]
## [1] "operator" "C"       
## 
## [[3]][[2]]
## [1] "throw" "P"    
## 
## [[3]][[3]]
## [1] "discard" "P"      
## 
## [[3]][[4]]
## [1] "environment" "N"          
## 
## 
## [[4]]
## [[4]][[1]]
## [1] "operator" "C"       
## 
## [[4]][[2]]
## [1] "label" "P"    
## 
## 
## 
## ss.pMp> #Features of each process
## ss.pMp> y.features<-vector(mode="list",length=length(steps))
## 
## ss.pMp> y.features[1]<-list(c(list(c("ok", "Cr"))))
## 
## ss.pMp> y.features[2]<-list(c(list(c("weight", "Cr"))))
## 
## ss.pMp> y.features[3]<-list(c(list(c("time", "Cr"))))
## 
## ss.pMp> y.features[4]<-list(c(list(c("label", "Cr"))))
## 
## ss.pMp> y.features
## [[1]]
## [[1]][[1]]
## [1] "ok" "Cr"
## 
## 
## [[2]]
## [[2]][[1]]
## [1] "weight" "Cr"    
## 
## 
## [[3]]
## [[3]][[1]]
## [1] "time" "Cr"  
## 
## 
## [[4]]
## [[4]][[1]]
## [1] "label" "Cr"   
## 
## 
## 
## ss.pMp> ss.pMap(steps, inputs.overall, outputs.overall,
## ss.pMp+         input.output, x.parameters, y.features, 
## ss.pMp+         sub="Paper Helicopter Project")
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## 
## SxSgm-> example(ss.ca.yield)
## 
## ss.c.y> ss.ca.yield(c(3,5,12),c(1,2,4),1915)
##       Yield       FTY       RTY DPU     DPMO
## 1 0.9895561 0.9859008 0.9859563  20 10443.86
## 
## SxSgm-> example(ss.ca.z)
## 
## ss.c.z> ss.ca.cp(ss.data.ca$Volume,740, 760)
## [1] 1.584136
## 
## ss.c.z> ss.ca.cpk(ss.data.ca$Volume,740, 760)
## [1] 1.546513
## 
## ss.c.z> ss.ca.z(ss.data.ca$Volume,740,760)
## [1] 3.139539
## 
## SxSgm-> example(ss.ca.cp)
## 
## ss.c.c> ss.ca.cp(ss.data.ca$Volume,740, 760)
## [1] 1.584136
## 
## ss.c.c> ss.ca.cpk(ss.data.ca$Volume,740, 760)
## [1] 1.546513
## 
## ss.c.c> ss.ca.z(ss.data.ca$Volume,740,760)
## [1] 3.139539
## 
## SxSgm-> example(ss.ca.cpk)
## 
## ss.c.c> ss.ca.cp(ss.data.ca$Volume,740, 760)
## [1] 1.584136
## 
## ss.c.c> ss.ca.cpk(ss.data.ca$Volume,740, 760)
## [1] 1.546513
## 
## ss.c.c> ss.ca.z(ss.data.ca$Volume,740,760)
## [1] 3.139539
## 
## SxSgm-> example(ss.cc)
## 
## ss.cc> ss.cc("mr", ss.data.pb1, CTQ = "pb.humidity")
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## Phase I limits:
##      LCL       CL      UCL 
## 0.000000 1.569483 5.126767 
## 
## Out of control Moving Range:
## None
## 
## ss.cc> testout <- ss.data.pb1
## 
## ss.cc> testout[31,] <- list(31,17)
## 
## ss.cc> ss.cc("mr", testout, CTQ = "pb.humidity")
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## Phase I limits:
##      LCL       CL      UCL 
## 0.000000 1.728600 5.646528 
## 
## Out of control Moving Range:
## [1] 30
## 
## SxSgm-> example(plotProfiles)
## 
## pltPrf> plotProfiles(profiles = ss.data.wby,
## pltPrf+     x = ss.data.wbx)
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## 
## SxSgm-> example(plotControlProfiles)
## 
## pltCnP> wby.phase1 <- ss.data.wby[, 1:35]
## 
## pltCnP> wb.limits <- climProfiles(profiles = wby.phase1,
## pltCnP+     x = ss.data.wbx,
## pltCnP+     smoothprof = TRUE,
## pltCnP+     smoothlim = TRUE)
## 
## pltCnP> wby.phase2 <- ss.data.wby[, 36:50]
## 
## pltCnP> wb.out.phase2 <- outProfiles(profiles = wby.phase2,
## pltCnP+     x = ss.data.wbx,
## pltCnP+     cLimits = wb.limits,
## pltCnP+     tol = 0.8)
## 
## pltCnP> plotControlProfiles(wb.out.phase2$pOut, tol = 0.8)
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© Emilio L. Cano, Javier M. Moguerza and Mariano Prieto Corcoba 2015-2016 | authors@qualitycontrolwithr.com

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