PLS Analysis block

Description

The PLS Analysis block is used to analyze the PLS model, which is a linear transformation of the input data set, to a required target output value.  The PLS Analysis block analyzes this model, and provides more information and greater understanding about the input variables of a data set, used to determine the effect on a target variable.

The Partial Least Squares Analysis block provides the following information for a pre-loaded PLS model:

  • the distance to model (D2Mod) value,

  • the scores of each input variable (tn value)  

  • the contribution of each variable to the total process variability, (VC_variable value).

The PLS Analysis block contains one input port, one parameter port and one output port.  

The PLS model itself is loaded from an XML file deployed from the Discrete & Batch Troubleshooter where the model is constructed.  

PLS calculations can be performed:

  • on every execute (continuous mode),

  • over a moving time window, or

  • at the start of each new batch.  

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PLS ANALYSIS block

Block Type

Rules and Models block (Model block / Moving window)

Input port

The input port will contain all the fields used in the PLS model which is constructed in and imported from the Discrete and Batch Troubleshooter.  Double click the PLS Analysis block to configure the properties of the block.

The input port may contain only double type fields and must contain all fields used in constructing the loaded PLS model.  These fields are selected when configuring the Properties page of the text source file. The input port must contain all fields used in constructing the loaded PLS model, and these input fields must be mapped to the required fields of the PLS model.

Parameter port

The parameter port is optional and is used when calculating values for batches.  A field is selected as a trigger signalling the start of a new batch, and the model then executes when the trigger field identifies the start of a new batch. If there is a lengthy delay between the end of the last batch, and the start of a new batch when the model executes, delays can be experienced in receiving model outputs as only when the trigger field value changes, will the PLS output values in the output port be calculated and updated.  BAD_QUALITY input samples are ignored for calculation triggers.  

The parameter port can contain fields of double, integer or string values.  

Output port

The output port will contain the following calculated values from the loaded PLS model:

  • Distance to model (D2MOD)

    The Distance to model values indicate how well the current inputs match the original data set on which the model was created.  Large Distance to model values indicate a poorly performing process, and low Distance to model values indicate a process that has been accurately modeled.  

  • Scores

    These fields are denoted by "tn" where n is the number of variables used in the model.  Values for these variables always indicate the scores for the current input fields.

  • Variable contributions (VC_)

    These fields denote the variable contributions of each field to the total Distance to model values. This is useful to determine which variable is the main cause of variation if the Distance to model value is large.

NOTE:  If the Calculation method is set to "Moving Window" or "Batch", these fields contain the average input values for each field over the window period or batch. D2MOD, t0 and VC output values will have used the averaged input values over the window / batch. However the Scores use the  current and specific  input values, not the window or batch average.  

Outputs can be illustrated by using probes which only show integer or double fields, or by inserting an output port showing integer, double and string fields. Output ports are found under General blocks.

Functions performed on tags

The input values are sent through the PLS Analysis block and the calculated output values from the model are placed in output fields of the PLS Analysis block.

  • On the Values: These output values have been discussed above, under output port.

  • On the Quality:

    • Continuous calculation method: any bad quality input value will result in a bad quality output value.

    • Moving Window and Batch calculation methods: If there is at least one good quality input value for a particular timestamp, the input values will be averaged and a good quality, averaged output value will result.  If there is not one good quality input value for a particular timestamp, bad quality output values will result.

  • On the Timestamp: It will be recorded at the model execute time.

Runnability

Minimum requirements for runnability on the PLS Analysis block:

    • Loaded and valid PLS XML model file.

    • Configured calculation method: Continuous, Moving Window or Batch.  

    • Properly configured and mapped model/input fields. The input port must contain all fields used in constructing the loaded PLS model, and these input fields must be mapped to the required fields of the PLS model.

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CSense 2023- Last updated: June 24,2025