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.
library(SixSigma) 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
## 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")
## ## 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
## ## 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")
## $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")
##
## 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")
##
## 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")
## 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")
## 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)
## ## 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)
