Abstract: The invention provides methods, systems and computer programs for optimizing standard operating procedure for a control system. The invention comprises (i) recording a sequence of control system operator actions, (ii) identifying a control system process corresponding to the recorded sequence of control system operator actions, (iii) retrieving a standard operating procedure associated with the identified control system process, (iv) determining a first set of deviations between (a) the recorded sequence of control system operator actions and (b) the standard operating procedure, (v) determining a second set of deviations between (c) a set of KPI values associated with the recorded sequence of control system operator actions and (d) a set of KPI values associated with the standard operating procedure, and (vi) modifying the standard operating procedure to reduce deviation between (e) the recorded sequence of control system operator actions and (f) said standard operating procedure.

Abstract: The invention provides methods, systems and computer programs for optimizing standard operating procedure for a control system. The invention comprises (i) recording a sequence of control system operator actions, (ii) identifying a control system process corresponding to the recorded sequence of control system operator actions, (iii) retrieving a standard operating procedure associated with the identified control system process, (iv) determining a first set of deviations between (a) the recorded sequence of control system operator actions and (b) the standard operating procedure, (v) determining a second set of deviations between (c) a set of KPI values associated with the recorded sequence of control system operator actions and (d) a set of KPI values associated with the standard operating procedure, and (vi) modifying the standard operating procedure to reduce deviation between (e) the recorded sequence of control system operator actions and (f) said standard operating procedure.

Abstract: A method of model identification for a process with unknown initial conditions in an industrial plant, the method comprising collecting a set of manipulated variables and corresponding set of process variables from the process; obtaining a plurality of manipulated variables from the collected set of manipulated variables; for each of the plurality of manipulated variables, obtaining optimal model parameters of a model transfer function and computing a model fitting index for optimized simulated process variables generated by the model transfer function using the optimal model parameters; identifying a best model fitting index among the model fitting indices computed; selecting a manipulated variable associated with the best model fitting index as an initial steady state condition for the model transfer function; and selecting the optimal model parameters corresponding with the best model fitting index as the best model parameters of the model transfer function to tune the controller.

Abstract: A method of qualifying performance of a conventional control valve in a process plant, the valve being controlled by a controller, the method comprising a processor obtaining data samples from a database stored on a server of the process plant, each data sample comprising a process variable, a set-point, and a manipulated variable; the processor computing a non-linearity index from the data samples and determining if the non-linearity index is greater than a threshold value; if the non-linearity index is greater than the threshold value, the processor charting a plot of the process variable against the manipulated variable and determining if the plot has an elliptical or rectangular fit; and if the plot has an elliptical fit, the processor determining if a percentage of the total number of data samples lying within a theoretical ellipse encompassed within the elliptical fit is less than or equal to a preset percentage.

Abstract: A method of model identification for a process with unknown initial conditions in an industrial plant, the method comprising collecting a set of manipulated variables and corresponding set of process variables from the process; obtaining a plurality of manipulated variables from the collected set of manipulated variables; for each of the plurality of manipulated variables, obtaining optimal model parameters of a model transfer function and computing a model fitting index for optimized simulated process variables generated by the model transfer function using the optimal model parameters; identifying a best model fitting index among the model fitting indices computed; selecting a manipulated variable associated with the best model fitting index as an initial steady state condition for the model transfer function; and selecting the optimal model parameters corresponding with the best model fitting index as the best model parameters of the model transfer function to tune the controller.

Abstract: An apparatus for monitoring an industrial process comprising a plurality of variables. The apparatus comprises a defining module configured for defining a normal-condition data set may comprise data values of the variables when the industrial process is operating under a normal condition and for defining an abnormal-condition data set may comprise data values of the variables when the industrial process is operating under an abnormal condition; a modelling module configured for modelling a normal-condition model from the normal-condition data set and modelling an abnormal-condition model from the abnormal-condition data set; a plotting module configured for plotting a normal-condition plot from the normal-condition model and plotting an abnormal-condition plot from the abnormal-condition model; and an analysis module configured for analysing live data values of the variables for simultaneous display with the normal-condition plot and the abnormal-condition plot.

Abstract: A metric based performance monitoring a process control system is disclosed in which diagnostics are performed at multiple levels of the plant, results of the diagnostics converted into Key Performance Indicators and compared to predetermined benchmarks such that an integrated and overall determination of the plants' performance may be displayed.

Abstract: An apparatus for monitoring an industrial process comprising a plurality of variables. The apparatus comprises a defining module configured for defining a normal-condition data set may comprise data values of the variables when the industrial process is operating under a normal condition and for defining an abnormal-condition data set may comprise data values of the variables when the industrial process is operating under an abnormal condition; a modelling module configured for modelling a normal-condition model from the normal-condition data set and modelling an abnormal-condition model from the abnormal-condition data set; a plotting module configured for plotting a normal-condition plot from the normal-condition model and plotting an abnormal-condition plot from the abnormal-condition model; and an analysis module configured for analysing live data values of the variables for simultaneous display with the normal-condition plot and the abnormal-condition plot.

Abstract: A method for providing a system for establishing a control valve performance in a process operation. The system includes establishing an expected flow rate for a control valve by measuring a differential pressure between an upstream and downstream position of a control valve of interest and using the formula Q = Cv × ? ? ( x ) × ? ? ? P G , measuring an actual flow rate across the control valve, comparing the actual flow rate with the expected flow rate to determine the difference in value between the actual and expected flow rate, determining if the difference is within an acceptable range of values from the expected flow rate and establishing the performance of the control valve.

Abstract: A metric based performance monitoring A process control system is disclosed in which diagnostics are performed at multiple levels of the plant, results of the diagnostics converted into Key Performance Indicators and compared to predetermined benchmarks such that an integrated and overall determination of the plants' performance may be displayed.

Abstract: The invention is a system for assessing and diagnosing performance of a control loop, comprising a Data Collection Section which collects data of two parameters of the control loop for an installed valve. The data collected is processed in a Linear Regression Section to generate a linear regression. A User Setting Port is provided to define the tolerance band and the boundary points. The generated linear regression, together with the defined tolerance band and boundary points are processed in a Linear Approximation Section to generate an acceptable reference region.