APPLYING MULTIVARIATE BATCH MODELING TO REAL TIME PROCESS MONITORING

摘要

The amount of data measured during a typical manufacturing process is immense. To efficiently utilize this data without becoming overwhelmed with confusing, and often conflicting information is difficult to impossible when using traditional univariate methods. Batch processes in particular - where there is a start and a stop for a given product - require special handling so time-dependent process evolution information is not lost.rnMeasured variables are typically used for process control, but they are also useful for the overview of the process (process monitoring), for fault (upset) detection, comparing differences in processing equipment (equipment matching), predicting product or process properties (soft sensors or virtual metrology), and for improved process understanding. The use of multivariate analysis to accomplish these objectives is discussed and illustrated with a batch processing example from the semiconductor industry.