QC_Capability: Calculate Summary of Quality Performance Parameters

Description

function to report listing of quality performance parameters

Usage

QC_Capability(data = NULL, value = NULL, grouping = NULL,
  formula = NULL, method = "xBar.rBar", na.rm = FALSE, LSL = NULL,
  USL = NULL, digits = 2)

Arguments

data

vector or dataframe, as indicated below for each chart type

Individuals (XmR): vector of values;
Studentized: dataframe

value

string, Studentized Charts, name of numeric vector in dataframe with values of interest.

grouping

string, Studentized Charts, name of single factor/variable to split the dataframe "values" by

formula

Studentized Charts: a formula, such as y ~ x1 + x2, where the y variable is numeric data to be split into groups according to the grouping x factors/variables

method

string, calling one of the following methods:

Individuals Charts: XmR,
Studentized Charts: xBar.rBar, xBar.rMedian, xBar.sBar, xMedian.rBar

na.rm

a logical value indicating whether NA values should be stripped before the computation proceeds.

LSL

numeric, Customer's lower specification limit

USL

numeric, Customer's Upper specification limit

Proc. Tolerance (sigma): Describes the number of your process sigma (from QC charting) that can fit in your customer's specification window (the larger the better).
DNS (sigma): Distance to Nearest Specification (DNS) limit. Measure of how centered your process is and how close you are to the nearest process limit in sigma units.
Cp: Describes how many times your 6 sigma process window (from QC charting) can fit in your customer's specification window (the larger the better)
Cpk: Describes how centered your process is relative to customer specifications. How many times can you fit a 3 sigma window (from QC charting) between your process center and the nearest customer specification limit.
Pp: Describes how many times your 6 sigma process window (overall standard deviation) can fit in your customer's specification window (the larger the better)
Ppk: Describes how centered your process is relative to customer specifications. How many times can you fit a 3 sigma window (overall standard deviation) between your process center and the nearest customer specification limit.

digits

integer, how many digits to report.

Value

data frame , listing of metric labels and value