Paper web breakage prediction using bootstrap aggregation of classification and regression trees

A system for predicting a web break in a paper machine located about a paper mill, comprising:

• a paper mill database containing a plurality of measurements obtained from the paper mill, each of the plurality of measurements relating to a predetermined paper machine variable;
• a processor for processing each of the plurality of measurements into break sensitivity data;
• and
• an aggregated break predictor responsive to the processor for predicting a web break sensitivity within the paper machine from the plurality of processed measurements, wherein the aggregated break predictor comprises an aggregated classification and regression tree model.

A method for predicting a web break in a paper machine located about a paper mill, comprising:

• obtaining a plurality of measurements from the paper mill, each of the plurality of measurements relating to a predetermined paper machine variable;
• processing each of the plurality of measurements into break sensitivity data;
• and
• predicting a web break sensitivity within the paper machine from the plurality of processed measurements using an aggregated break predictor.

A method for predicting a web break in paper machine located about a paper mill, comprising:

• obtaining a plurality of measurements from the paper mill, each of the plurality of measurements relating to a predetermined paper machine variable;
• processing each of the plurality of measurements into break sensitivity data;
• and
• predicting a web break sensitivity within the paper machine from the plurality of processed measurements using a break predictor comprising an average of a plurality of predictive models each derived from a historical web breakage data set.