Model Driven Multivariate Control Chart

Example 1

Summary: Create a Model-Driven Multivariate Control Chart for a Polyethylene Process. Functions used:_open, Model Driven Multivariate Control Chart, Process, Set Component, Historical Data End at Row, SendToReport, Dispatch, FrameBox, Grid Line Order, Reference Line Order.

Code:

// Open data table
dt = Open("$Sample_Data/Polyethylene Process.jmp");
// Model Driven Multivariate Control Chart
Model Driven Multivariate Control Chart(
    Process(
        :X Score 1 Formula,
        :X Score 2 Formula,
        :X Score 3 Formula,
        :X Score 4 Formula
    ),
    Set Component( 4 ),
    "Historical Data End at Row"(100),
    SendToReport(
        Dispatch(
            {"Monitor the Process",
            "T² for 4 Factors"},
            "Monitor the process",
            FrameBox( 3 ),
            {Grid Line Order( 1 ),
            Reference Line Order( 2 )}
        )
    )
);

Example 2

Summary: Generate a Model Driven Multivariate Control Chart (MDMCC) for the entire dataset, incorporating all identified process variables and including statistical prediction error and normalized DModX plots for comprehensive analysis.

Code:

// Open data table
dt = Open("$Sample_Data/Quality Control/Flight Delays.jmp");
// MDMCC with entire data
Model Driven Multivariate Control Chart(
    Process(
        :AA, :CO, :DL, :F9, :FL, :NW, :UA,
        :US, :WN
    ),
    Time ID( :Flight date ),
    Statistical Prediction Error Plot,
    Normalized DModX Plot
);

Example 3

Summary: Generate a model-driven multivariate control chart with principal component scores using historical data.

Code:

// Open data table
dt = Open("$Sample_Data/Quality Control/Flight Delays.jmp");
// PCA score with historical
Model Driven Multivariate Control Chart(
    Process( :Prin1, :Prin2, :Prin3 ),
    Historical Data End at Row( 16 ),
    T2 Plot,
    Statistical Prediction Error Plot,
    Normalized DModX Plot
);

Example 4

Summary: Create a Model-Driven Multivariate Control Chart using historical data.

Code:

// Open data table
dt = Open("$Sample_Data/Quality Control/Flight Delays.jmp");
// Original data with historical
Model Driven Multivariate Control Chart(
    Process(
        :AA, :CO, :DL, :F9, :FL, :NW, :UA,
        :US, :WN
    ),
    Time ID( :Flight date ),
    Historical Data End at Row( 16 ),
    Score Plot(
        Score Ellipse Coverage( 0.95 )
    )
);