| 主权项 |
1. A computer-implemented method for predicting prospective behavior of a batch-type manufacturing process with a finite duration, the method comprising:
receiving, by a computing device, measured values of a plurality of variables of the manufacturing process, including (i) measured values of the plurality of variables associated with at least one historical batch run and (ii) measured values of the plurality of variables associated with at least one current batch run representative of values measured up to a current maturity point in time, wherein the plurality of variables comprise at least one dependent variable that represents a process parameter whose value is dependent on one more process conditions; and using, by the computing device, a partial least squares (PLS) regression approach to estimate an unknown future value of the at least one dependent variable at a future point in time in the at least one current batch run, wherein using the PLS regression approach comprises:
creating, by the computing device, a X matrix including the measured values of the plurality of variables associated with the at least one historical batch run;creating, by the computing device, a Y matrix including the measured values of the at least one dependent variable associated with the at least one historical batch run;applying, by the computing device, the PLS regression approach to determine a relationship between the X matrix and the Y matrix, wherein the relationship is represented by a β matrix; andusing, by the computing device, the β matrix and the measured values of the plurality of variables for the at least one current batch run to estimate the unknown future value of the at least one dependent variable for the at least one current batch run; andusing, the β matrix to predict a plurality of future values of the at least one dependent variable at a plurality of future points in time after the current maturity point to the end of the finite duration of the at least one current batch run. |
