stat_QC_Capability: Auto QC Capability Stat Function

In ggmtech/ggQC: Quality Control Charts for 'ggplot'

Description

Draws lines, lables and summary statistics. Works best with histogram and density plots.

Usage

stat_QC_Capability(LSL, USL, method = "xBar.rBar",
  show.lines = c("LSL", "USL"), line.direction = "v",
  show.line.labels = TRUE, line.label.size = 3,
  show.cap.summary = c("Cp", "Cpk", "Pp", "Ppk"), cap.summary.size = 4,
  px = Inf, py = -Inf, digits = 3)

Arguments

LSL	numeric, Customer's lower specification limit
USL	numeric, Customer's Upper specification limit
method	string, calling the following methods: Individuals Charts: XmR, Studentized Charts: xBar.rBar, xBar.rMedian, xBar.sBar, xMedian.rBar, xMedian.rMedian
show.lines	vector, indicating which lines to draw ie., c("LCL", "LSL", "X", "USL", "UCL") LCL: Lower Control Limit LSL: Lower Specification Limit X: Process Center USL: Upper Specification Limit UCL: Upper Control Limit
line.direction	string "v" or "h", specifies which direction to draw lines.
show.line.labels	boolean, if TRUE then draw.
line.label.size	numeric, control the size of the line labels.
show.cap.summary	vector, indicating which lines to draw ie., c("TOL","DNS", "Cp", "Cpk", "Pp", "Ppk", "LCL", "X", "UCL", "Sig"). The order given in the vector is the order presented in the graph. TOL: Tolerance in Sigma Units (USL-LSL)/sigma DNS: Distance to Nearest Specification Limit in Simga Units Cp: Cp (Within) Cpk: Cpk (Within) Pp: Pp (Between) Ppk: Ppk (Between) LCL: Lower Control Limit X: Process Center UCL: Upper Control Limit Sig: Sigma from control charts
cap.summary.size	numeric, control the size/scale of the summary text box.
px	numeric, x position for summary text box. Use Inf to force label to x-limit.
py	numeric, y position for summary text box. Use Inf to force label to y-limits. May also need vjust parameter.
digits	integer, how many digits to report.

Value

capability layer for histogram and density plots.

See Also

for more control over lines, labels, and capability data see the following functions:

• stat_QC_cap_vlabels

• stat_QC_cap_hlabels

• stat_QC_cap_vlines

• stat_QC_cap_hlines

• stat_QC_cap_summary

Examples

# Load Libraries ----------------------------------------------------------
require(ggQC)
require(ggplot2)
# Setup Data --------------------------------------------------------------
set.seed(5555)
Process1 <- data.frame(ProcessID = as.factor(rep(1,100)),
                      Value = rnorm(100,10,1),
                      Subgroup = rep(1:20, each=5),
                      Process_run_id = 1:100)
set.seed(5556)
Process2 <- data.frame(ProcessID = as.factor(rep(2,100)),
                      Value = rnorm(100,20, 1),
                      Subgroup = rep(1:10, each=10),
                      Process_run_id = 101:200)
df <- rbind(Process1, Process2)

######################
##  Example 1 XmR   ##
######################

##You may need to use the r-studio Zoom for these plots or make the size of the
##stat_QC_cap_summary smaller with size = some number"

# Normal Histogram XmR --------------------------------------------------------
EX1.1 <-  ggplot(df[df$ProcessID == 1,], aes(x=Value, QC.Subgroup=Subgroup)) +
geom_histogram(binwidth = 1, color="purple") +
 geom_hline(yintercept=0, color="grey") +
 stat_QC_Capability(LSL=5, USL=15, show.cap.summary = "all", method="XmR") +
 scale_x_continuous(expand =  expand_scale(mult = c(0.15,.8))) +
 ylim(0,45)
#Ex1.1

# Facet Histogram XmR -----------------------------------------------------
EX1.2 <- ggplot(df[order(df$Process_run_id),],
aes(x=Value, QC.Subgroup=Subgroup, color=ProcessID)) +
geom_histogram(binwidth = 1) +
 geom_hline(yintercept=0, color="grey") +
 stat_QC_Capability(LSL=5, USL=15, show.cap.summary = "all", method="XmR") +
 scale_x_continuous(expand =  ggplot2::expand_scale(mult = c(0.15,.8))) +
 facet_grid(.~ProcessID, scales = "free_x") + ylim(0,45)
#EX1.2

# Normal Density XmR --------------------------------------------------------
EX1.3 <- ggplot(df[df$ProcessID == 1,], aes(x=Value, QC.Subgroup=Subgroup)) +
geom_density(bw = .4, fill="purple", trim=TRUE) +
 geom_hline(yintercept=0, color="grey") +
 stat_QC_Capability(LSL=5, USL=15, show.cap.summary = "all", method="XmR") +
 scale_x_continuous(expand =  expand_scale(mult = c(0.15,.8)))  + ylim(0,.5)
#EX1.3

########################################
##  Example 2: xBar.rBar or xBar.sBar ##
########################################
# Single Histogram xBar.rBar ----------------------------------------------
EX2.1 <- ggplot(df[df$ProcessID==1,], aes(x=Value, QC.Subgroup=Subgroup)) +
 geom_histogram(binwidth = 1) +
 stat_QC_Capability(LSL=5, USL=15, method="xBar.rBar") +
 scale_x_continuous(expand =  ggplot2::expand_scale(mult = c(0.15,.8))) #+
#EX2.1

ggmtech/ggQC documentation built on Dec. 20, 2021, 10:43 a.m.