Abstract: A system and method of monitoring and diagnosing on-line multivariate process variable. Multivariate process data includes multiple process variables each having a multiple observations. On-line process data is collected from a process control system when the process is on-line. The on-line process data includes multiple observations of multiple process variables. A multivariate statistical analysis represents the operation of the process based on a set of the on-line process data. The representation a result. The representation and the set of on-line process data are stored. An output is generated based on a parameter of the representation. The parameter includes a result generated by the representation of the operation of the process, a process variable used to generate the representation of the operation of the process and/or the set of collected on-line process data.

Abstract: Methods and systems to detect steady-state operations in a process of a process plant include collecting process data. The collected process data is generated from a plurality of process variables of the process. A multivariate statistical model of the operation of the process is generated using the process data. The multivariate statistical model may be generated from a principal component analysis. The model is executed to generate outputs corresponding to the most significant variations in the process. Statistical measures of the outputs are generated and used to determine whether a steady-state or unsteady-state is related to the process.

Abstract: A number of techniques are disclosed to facilitate process data collection and monitoring. The techniques may involve and support the selection of process parameters to be monitored, including scanning techniques for automated identification of such parameters. The techniques may also involve the management of data storage and archiving operations to facilitate continued process data collection arising from an on-line process. In these and other ways, the disclosed techniques are well-suited for process data collection and monitoring in connection with diagnostic elements of a process control system and other contexts involving process status indicators and the underlying process variables.

Abstract: A system and method of monitoring and diagnosing on-line multivariate process variable data in a process plant, where the multivariate process data comprises a plurality of process variables each having a plurality of observations, includes collecting on-line process data from a process control system within the process plant when the process is on-line, where the collected on-line process data comprises a plurality of observations of a plurality of process variables, performing a multivariate statistical analysis to represent the operation of the process based on a set of collected on-line process data comprising a measure of the operation of the process when the process is on-line, where the representation of the operation of the process is adapted to be executed to generate a result, storing the representation of the operation of the process and the set of collected on-line process data, and generating an output based on a parameter of the representation of the operation of the process, where the parameter

Abstract: A number of techniques are disclosed to facilitate process data collection and monitoring. The techniques may involve and support the selection of process parameters to be monitored, including scanning techniques for automated identification of such parameters. The techniques may also involve the management of data storage and archiving operations to facilitate continued process data collection arising from an on-line process. In these and other ways, the disclosed techniques are well-suited for process data collection and monitoring in connection with diagnostic elements of a process control system and other contexts involving process status indicators and the underlying process variables.