The present paper contributes to the issues of batch process modelling and monitoring by proposing a time-varying state space (TVSS) model for the evaporative sugar crystallization industrial process. The study is focused on issues of on-line detection of changes in crystallization process operation, the early warning of process malfunctions and potential production failures; problems that have...

In this expository paper we give an overview of some statistical methods for the monitoring of social networks. We discuss the advantages and limitations of various methods as well as some relevant issues. One of our primary contributions is to give the relationships between network monitoring methods and monitoring methods in engineering statistics and public health surveillance. We encourage ...

In some statistical process control applications, the process data are not Normally distributed and characterized by the combination of both variable and attributes quality characteristics. Despite different methods which are proposed separately for monitoring multivariate and multi-attribute processes, only few methods are available in the literature for monitoring multivariate-attribute proce...

Structural health monitoring is described in the context of a statistical process control paradigm. This paper demonstrates the application of various statistical process control techniques such as the Shewhart, the exponentially weighted moving average, and the cumulative sum control charts to vibration-based damage diagnosis. The control limits are first constructed based on the measurements ...

Standard multivariate statistical process control (SPC) techniques, such as Hotelling’s T 2, cannot easily handle large-scale, complex process data and often fail to detect out-of-control anomalies for such data. We develop a computationally efficient and scalable Chi-Square (χ2) Distance Monitoring (CSDM) procedure for monitoring large-scale, complex process data to detect out-of-control anoma...

The objective of the current paper is to present an intelligent system for complex process monitoring, based on artificial intelligence technologies. This system aims to realize with success all the complex process monitoring tasks that are: detection, diagnosis, identification and reconfiguration. For this purpose, the development of a multi-agent system that combines multiple intelligences su...

Control charts are powerful tools to monitor quality characteristics of services or production processes. However, in some processes, the performance of process or product cannot be controlled by monitoring a characteristic; instead, they require to be controlled by a function that usually refers as a profile. This study suggests employing exponentially weighted moving average (EWMA) and range ...