Batch Monitoring Through Common Subspace Models

Abstract

Abstract Multi-way statistical projection techniques have typically been applied in the development of monitoring models for single recipe or single grade production. As defined, implementation of these techniques in multi-product applications necessitates the development of a large number of process models. This issue can be overcome through the use of common sub-space models constructed by pooling the individual variance-covariance matrices. A second issue with multi-way approaches is the difficulty of interpreting multiway contribution plots. An alternative approach is the U2 statistic. In this paper an extension is proposed, the V2 statistic, based on the cumulative contribution of variables at each sample point. The methodologies are demonstrated on two industrial applications.