pbcc {pbcc}

Percentile-based control charts

Description

Create an object of class 'pbcc' to perform statistical quality control based on percentile-based designs (PL) approach. This object may then be used to plot percentile-based Shewhart charts either individual or joint, summary statistics and more with guaranted in-control performace.

Usage

pbcc(data,T1, p1, type=c("Xbar", "R", "S", "S2",
  "Xbar-R","Xbar-S","Xbar-S2"), sided="two",
  k=NULL, lp=NULL, up=NULL)

Arguments

data

A data frame, a matrix or a vector containing observed data for the variable to chart. Each row of a data frame or a matrix, and each value of a vector, refers to a sample or ”rationale group”.

T1

The desired in-control time to signal (a numeric value, defualt value is 100).

p1

The probability to signal in-control from a specified number (a numeric value, default value is 5%)

type

A character string specifying the type of Shewhart control chart either individual or joint.Available types are; "Xbar", "R", "S", "S2", "Xbar-R", "Xbar-S" and "Xbar-S2".

sided

A character string specifying the calculation of either one-sided or two-sided control limits of Shewhart dispersion charts based on PL approach (default type is two-sided).

k

The optimal control chart constant/multiplier to design the percentile-based X-bar control chart either individually or jointly.

lp

The optimal lower percentile point to calculate the lower control limits of the percentile-based dispersion control chart. or/and

up

The optimal upper percentile point to calculate the lower control limits of the percentile-based dispersion control chart.

Value

Returns an object of class 'pbcc' with "data.name", "type" and values of "sizes", "std.dev", "statistics" and "control limits" of individual or joint Shewhart control chart.

Author(s)

Aamir Saghir, Zsolt T. Kosztyan*

e-mail: [e-mail]

References

Faraz A, Saniga E, Montgomery D. (2019). Percentile-based control charts design with an application to Shewhart Xbar and S2 control charts. Quality and Reliability Engineering International, 35(1); 116-126.

See Also

odpbc, summary, plot.

Examples

#Calculation of the percentile-based control charts using "pbcc"" package for
# "diameter" of pistonrings data.
library(qcc)
data(pistonrings)
diameter = with(pistonrings, qcc.groups(diameter, sample))
T1=100      # Set the process in-control time to signal is at least 100 samples.
p1=0.05     # Set the probability of guaranteed in-control signals is 5%.

#Calculation of two-sided individual percentile-based Xbar control chart
#for diameter data.
Q11<- pbcc(diameter,T1, p1, type="Xbar")

# Calculation of One-sided individual percentile-based S2 control chart
# for diameter data.
Q12<- pbcc(diameter,T1, p1, type="S2", sided="one")

# Calculation of two-sided joint percentile-based Xbar and S control chart
#for diameter data.
Q13<- pbcc(diameter,T1, p1, type="Xbar-S", sided="two")