plot.rbcc {rbcc}R Documentation

Plot function for Risk-based Control Charts

Description

Plot function for Risk-based Univariate (shewhart, exponentially weighted moving average(EWMA) and moving average (MA))Control Charts

Usage

## S3 method for class 'rbcc'
plot(x, ...)

Arguments

x

an object of class 'rbcc'.

...

other graphical parameters.

Value

No return value, called for side effects

Author(s)

Aamir Saghir, Attila I. Katona, Zsolt T. Kosztyan*

e-mail: kzst@gtk.uni-pannon.hu

References

Katona, A. I., Saghir, A., Hegedűs, C., & Kosztyán, Z. T. (2023). Design of Risk-Based Univariate Control Charts with Measurement Uncertainty. IEEE Access, 11, 97567-97573.

Kosztyán, Z. T., & Katona, A. I. (2016). Risk-based multivariate control chart. Expert Systems with Applications, 62, 250-262.

See Also

data_gen, rbcc, rbcc_opt, rbcusumcc, rbcusumcc_opt, rbewmacc, rbewmacc_opt, rbmacc, rbmacc_opt, rbmcc, rbmcc_opt, summary.rbcc.

Examples

# Data Generation and Xbar chart.

## Example for generation of data vector X and measuremenet error vector UC.
obs <- 200                 # Total number of observations of a process.
mu_X <- c(0)               # Define data mean.
va_X  <- c(1)              # Define data standard deviation.
sk_X <- c(0)               # Define data skewness.
ku_X <- c(3)               # Define data kurtosis.
mu_UC <- c(0)              # Define mean of measurement errors.
va_UC <- c(1)              # Define standard deviation of measurement errors.
sk_UC <- c(0)              # Define skewness of measurement errors.
ku_UC <- c(3)              # Define kurtosis of measurement errors.

# Simulation of 200 obervations of 1 variable.
X <- data_gen (obs, mu_X, va_X, sk_X, ku_X)

# Simulation of 200 muasurement erros related to 1 variable.
UC <- data_gen(obs,mu_UC, va_UC, sk_UC, ku_UC)

# Construction of risk-based Xbar chart with default vector of decision costs
C <- c(1,1,1,1)                            # vector of decision costs
H <- rbcc(X, UC, C, n=3, type="xbar")      # for subgroups of size 3

# optimal risk-based xbar control chart
H_opt <- rbcc_opt(X, UC, C, n=3, type="xbar")
plot(H_opt)

[Package rbcc version 0.1.5 Index]