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This paper considers multivariate statistical monitoring of batch manufacturing processes. It is known that conventional monitoring approaches, e.g. principal component analysis (PCA), are not applicable when the normal operating conditions of the process cannot be sufficiently represented by a multivariate Gaussian distribution. To address this issue, Gaussian mixture model (GMM) has been prop...

Control charts are widely used for process monitoring. Software reliability process can be monitored efficiently by using Statistical Process Control (SPC). It assists the software development team to identify failures and actions to be taken during software failure process and hence, assures better software reliability. In this paper we propose a control mechanism based on the cumulative quant...

The monitoring, fault detection and visualization of defects are a strategic issue for product quality. This paper presents a novel methodology based on the integration of textural Multivariate image analysis (MIA) and multivariate statistical process control (MSPC) for process monitoring. The proposed approach combines MIA and p-control charts, as well as T 2 and RSS images for defect location...