Statistical data modeling based on partial least squares: Application to melt index predictions in high density polyethylene processes to achieve energy-saving operation

We propose two parameter update schemes which employ recursive update of partial Least Squares (PLS) model parameters as well as a model bias update to the process data. These update schemes have been applied to the successful prediction of Melt Index (MI) in grade-change operations of High Density Polyethylene (HDPE) plants. The lack of sophisticated software support hinders the recurrent use of these techniques. This paper also presents user-friendly, easy to use, graphical user interface to raise the usability and accessibility of the approach of online update of the PLS models.