Honeywell International Inc.

Mandar Subhash Vartak

Sanjay Kantilal Dave

Sriram Hallihole

Andrew John Trenchard

Christopher J Webb

Matthew G Grizzle

Michael Niemiec

Ranganathan Srinivasan

Lucy Ning Liu

Ravi Kumar Ramamurthy

Gobinath Pandurangan

Madhukar Madhavamurthy Gundappa

Rajni Jain

Ward MacArthur

S Chandrakanth Vittal

Chris Webb

Venkata Krishna Prasad Reddy Vurubindi

Avijit Das

Sreesathya Sathyabhama Sreekantan

Roshan Yohannan

Navaneeth Vengallur

Andrew John Trenchart

Matt Grizzle

Michael Niemeic

A field device, method, and non-transitory computer readable medium provide for cost of lost opportunity to operators in real-time using an advance process control. The field device includes a memory and a processor operably connected to the memory. The processor receives current values and average values for controlled variables and manipulated variables; determines costs of lost opportunity for each of controlled variable variance issues, limit issues, model quality issues, inferential quality issues, and variable model issues based on the current values and the average values of the controlled variables; and stores the costs of lost opportunity for the field device.

Method and system to provide cost of lost opportunity to operators in real time using advance process control

A method includes obtaining data associated with operation of an industrial process controller and identifying impacts of operational problems of the industrial process controller. The method also includes generating a graphical display for a user, where the graphical display presents one or more recommended actions to reduce or eliminate at least one of the impacts of at least one of the operational problems. The method further includes triggering at least one of the one or more recommended actions based on input from the user. The method could also include executing one or more analytic algorithms to process the obtained data and identify the operational problems of the industrial process controller. Each of the one or more analytic algorithms could be instantiated as a container, and multiple containers could be instantiated and executed as needed. Results of executing the one or more analytic algorithms could be transformed into a standard format.

Apparatus and method for identifying, visualizing, and triggering workflows from auto-suggested actions to reclaim lost benefits of model-based industrial process controllers

A method includes obtaining data associated with operation of a model-based industrial process controller. The method also includes identifying at least one estimated impact of at least one operational problem of the industrial process controller, where each estimated impact is expressed in terms of a lost opportunity associated with operation of the industrial process controller. The method further includes presenting the at least one estimated impact to a user. The at least one estimated impact could include impacts associated with noise or variance in process variables used by the industrial process controller, misconfiguration of an optimizer in the industrial process controller, one or more limits on one or more process variables, a quality of at least one model used by the industrial process controller, a quality of one or more inferred properties used by the industrial process controller, or one or more process variables being dropped from use by the industrial process controller.

Apparatus and method for estimating impacts of operational problems in advanced control operations for industrial control systems

A method includes identifying one or more proxy limit variables to be used to define an operating envelope associated with an industrial process controller. The industrial process controller is associated with a number of process variables including the proxy limit variable(s). The method also includes maximizing and minimizing at least one of the proxy limit variable(s). The method further includes presenting maximum and minimum values of the at least one of the proxy limit variable(s) as the operating envelope in a graphical user interface to at least one user. A single proxy limit variable could be used, and maximum and minimum values of the single proxy limit variable can be presented in a one-dimensional representation of the operating envelope. Multiple proxy limit variables could also be used, and maximum and minimum values of the proxy limit variables can be presented in a multi-dimensional representation of the operating envelope.

Apparatus and method for using advanced process control to define real-time or near real-time operating envelope

A method includes obtaining data identifying values of one or more controlled variables associated with an industrial process controller. The method also includes identifying periods when at least one of the one or more controlled variables has been moved to an associated limit by the controller. The method further includes, for each identified period, (i) identifying a standard deviation of predicted values for the associated controlled variable and (ii) determining a control giveaway value for the associated controlled variable based on the standard deviation. The control giveaway value is associated with an offset between the associated controlled variable's average value and the associated limit. In addition, the method includes identifying variances in the one or more controlled variables using the control giveaway values and generating a graphical display identifying one or more impacts or causes for at least some of the variances.

Apparatus and method for identifying impacts and causes of variability or control giveaway on model-based controller performance

A method includes retrieving process variable values from a multivariable predictive controller. The multivariable predictive controller is executed on an embedded platform and is configured to control an industrial process. The method also includes simulating how the multivariable predictive controller would attempt to control the industrial process based on the process variable values. The method further includes transmitting simulated process variable values to the multivariable predictive controller.

Apparatus and method for performing process simulations for embedded multivariable predictive controllers in industrial process control and automation systems

A method includes obtaining parameter values for multiple process variables associated with at least one industrial process, where the parameter values for each process variable include low and high limits and a current value. The method also includes presenting a graphical display that includes radial lines each associated with a different one of the process variables, a first graphical indicator passing through the radial lines and identifying the low limits of the process variables, a second graphical indicator passing through the radial lines and identifying the high limits of the process variables, and third graphical indicators identifying the current values of the process variables along the radial lines.

Apparatus and method for generating smart visualizations for effective monitoring and control in industrial process control and automation systems

A method implemented using a server includes receiving, from a first application, a tag associated with an equipment, the tag indicating an event. The method also includes retrieving, from at least a second application, at least one of an action or context information linked to the event based on the tag. The method further includes transmitting the tag indicating the event and the action linked to event. In addition, the method includes displaying, on a plant graphic, a location of the event using the tag and the action linked to the event.

Method and system for co-operative intelligent HMIs for effective process operations

A method of dynamic model selection for hybrid linear/non-linear process control includes developing a plurality of process models including at least one linear process model and at least one non-linear process model from inputs including dynamic process data from a processing system that runs a physical process. At least two of the plurality of process models are selected based on a performance comparison based on at least one metric, wherein the selected process models number less than a number of the plurality of process models received. A multi-model controller is generated that includes the selected process models. The physical process is simulated using the multi-model controller by applying the selected process models to obtain closed loop performance test data for each of the selected models. The performance test data is compared. A selected process model is then selected.

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Karnataka, India

Mandar Subhash Vartak