cv30_dar_car_mic_ppu {CleaningValidation}

Calculate DAR, CAR, and Mic Ppu Values and Identify the Overall Minimum

Description

This function calculates Ppu values for DAR, CAR, and Mic using the KDE method provided by the 'cv12_kde_ppu' function. It then uses the 'cv29_mic_ppu' function to calculate combined Ppu for Mic and extract the method with the minimum Ppu value. The function assumes the availability of the datasets 'Eq_DAR', 'Eq_CAR', and 'Eq_Mic' that conform to expected column naming conventions and data structures. It is reliant on the results of the 'cv12_kde_ppu' and 'cv29_mic_ppu' functions being consistent and correctly formatted.

Usage

cv30_dar_car_mic_ppu(
  dar_data,
  dar_residue_col,
  dar_cleaning_event_col,
  dar_usl_col,
  car_data,
  car_residue_col,
  car_cleaning_event_col,
  car_usl_col,
  mic_data,
  mic_residue_col,
  mic_cleaning_event_col,
  mic_usl_col
)

Arguments

dar_data

A dataframe containing DAR data.

dar_residue_col

The name of the DAR residue column.

dar_cleaning_event_col

The name of the DAR cleaning event identifier column.

dar_usl_col

The name of the DAR Upper Specification Limit column.

car_data

A dataframe containing CAR data.

car_residue_col

The name of the CAR residue column.

car_cleaning_event_col

The name of the CAR cleaning event identifier column.

car_usl_col

The name of the CAR Upper Specification Limit column.

mic_data

A dataframe containing Mic data.

mic_residue_col

The name of the Mic residue column.

mic_cleaning_event_col

The name of the Mic cleaning event identifier column.

mic_usl_col

The name of the Mic Upper Specification Limit column.

Value

A dataframe with Ppu values for DAR, CAR, and Mic, along with the Overall Minimum Ppu.

Author(s)

Chan, Mohamed, Lou, Wendy, Yang, Xiande [xiande.yang at gmail.com]

Examples

Eq_DAR <- cv03_usl_unification(data = Eq_DAR, cleaning_event_col = "CleaningEvent", 
 residue_col = "DAR", usl_col = "USL")
 Eq_CAR <- cv03_usl_unification(data = Eq_CAR, cleaning_event_col = "CleaningEvent", 
 residue_col = "CAR", usl_col = "USL")
  df1 <- cv30_dar_car_mic_ppu(
    dar_data = Eq_DAR, 
    dar_residue_col = "DAR_Pct", 
    dar_cleaning_event_col = "CleaningEvent", 
    dar_usl_col = "USL_Pct",
    car_data = Eq_CAR, 
    car_residue_col = "CAR_Pct", 
    car_cleaning_event_col = "CleaningEvent", 
    car_usl_col = "USL_Pct",
    mic_data = Eq_Mic, 
    mic_residue_col = "Mic", 
    mic_cleaning_event_col = "CleaningEvent", 
    mic_usl_col = "USL")