Process Map

This function takes information about the process we want to represent and draw the Process Map, with its X's, x's, Y's and y's in each step of the process

ss.pMap(
  steps,
  inputs.overall,
  outputs.overall,
  input.output,
  x.parameters,
  y.features,
  main = "Six Sigma Process Map",
  sub,
  ss.col = c("#666666", "#BBBBBB", "#CCCCCC", "#DDDDDD", "#EEEEEE", "#FFFFFF", "#000000",
    "#000000")
)

Arguments

steps

A vector of characters with the name of the 'n' steps

inputs.overall

A vector of characters with the name of the overall inputs

outputs.overall

A vector of characters with the name of the overall outputs

input.output

A vector of lists with the names of the inputs of the \(i-{th}\) step, that will be the outputs of the \((i-1)-{th}\) step

x.parameters

A vector of lists with a list of the x parameters of the process. The parameter is a vector with two values: the name and the type (view details)

y.features

A vector of lists with a list of the y features of the step. The feature is a vector with two values: the name and the type (view details)

main

The main title for the Process Map

sub

Subtitle for the diagram (recommended the Six Sigma project name)

ss.col

A vector of colours for a custom drawing. At least five colours, sorted by descendant intensity (see details)

Value

A graphic representation of the Map Process.

Details

The type of the x parameters and y features can be: C(controllable), N(noise), Cr(Critical), P(Procedure). The default value for ss.col is c("#666666", "#BBBBBB", "#CCCCCC", "#DDDDDD", "#EEEEEE", "#FFFFFF", "#000000", "#000000") a grayscale style.You can pass any accepted color string.

Note

The process map is the starting point for a Six Sigma Project, and it is very important to find out who the x's and y'x are.

References

https://en.wikipedia.org/wiki/Business_Process_Mapping/

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. https://link.springer.com/book/10.1007/978-1-4614-3652-2/.

See also

ss.ceDiag

Author

EL Cano

Examples

inputs.overall<-c("operators", "tools", "raw material", "facilities")
outputs.overall<-c("helicopter")
steps<-c("INSPECTION", "ASSEMBLY", "TEST", "LABELING")
#Inputs of process "i" are inputs of process "i+1"
input.output<-vector(mode="list",length=length(steps))
input.output[1]<-list(c("sheets", "..."))
input.output[2]<-list(c("sheets"))
input.output[3]<-list(c("helicopter"))
input.output[4]<-list(c("helicopter"))

#Parameters of each process
x.parameters<-vector(mode="list",length=length(steps))
x.parameters[1]<-list(c(list(c("width", "NC")),list(c("operator", "C")),
list(c("Measure pattern", "P")), list(c("discard", "P"))))
x.parameters[2]<-list(c(list(c("operator", "C")),list(c("cut", "P")),
list(c("fix", "P")), list(c("rotor.width", "C")),list(c("rotor.length",
"C")), list(c("paperclip", "C")), list(c("tape", "C"))))
x.parameters[3]<-list(c(list(c("operator", "C")),list(c("throw", "P")),
list(c("discard", "P")), list(c("environment", "N"))))
x.parameters[4]<-list(c(list(c("operator", "C")),list(c("label", "P"))))
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"    
#> 
#> 

#Features of each process
y.features<-vector(mode="list",length=length(steps))
y.features[1]<-list(c(list(c("ok", "Cr"))))
y.features[2]<-list(c(list(c("weight", "Cr"))))
y.features[3]<-list(c(list(c("time", "Cr"))))
y.features[4]<-list(c(list(c("label", "Cr"))))
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.pMap(steps, inputs.overall, outputs.overall,
        input.output, x.parameters, y.features, 
        sub="Paper Helicopter Project")