Abstract: The present invention relates to a method and a system for production accounting in process industries using Artificial Intelligence (AI). More particularly the present invention relates to fault detection in a plurality of measuring instruments and process equipment in a process plant. A plurality of measured signals from the measuring instruments is received by the process control system and noise is extracted from the plurality of measured signals. The extracted noise is correlated with a noise extracted from a plurality of reference signals using an AI based data analysis technique. Further, the process control system identifies deviations in the one or more parameters. The process control system detects the faults the plurality of measuring instruments or the process equipment using the correlated noises and the identified deviations of the one or more parameters.

Abstract: The present invention relates to a method and a system for controlling a process of a process plant. Hie system is configured to control a process in the process plant by recommending control operations and perform the control operations. The system obtains the control operations and detects availability of control room operators using historical data related to actions performed by the control room operators, sensory parameters of the control room operators and a status associated with the process. The system provides queries related to the control operations, the plant parameters, status of the process to the control room operators upon detecting the availability. Hie queries are validated by the control room operators. The system thereafter autonomously controls tire control room based on the validated data.

Abstract: In an embodiment, the present disclosure discloses a method and a module for controlling data transfer in a manufacturing plant. The IoT module is configured to receive a request for a plurality of parameters from a second application from one or more applications. The request is made by a first application from the one or more applications. The IoT module determines status of the requested parameters. The status indicates if the requested parameters are authorized for sharing. Further, the IoT module transfers only the authorized parameters to the first module based on the status. Thus, the present disclosure provides a method and a IoT module for sharing data securely within the manufacturing plant.

Abstract: A method and system are disclosed for optimizing load scheduling for a power plant having one or more power generator units. An exemplary method and corresponding system can involve detecting an event indicative of a need for adapting one or more constraints for an objective function used in load scheduling. On such detection, the objective function is analysed to determine adaptive constraint values for the one or more constraints for optimally solving the objective function. These adaptive constraint values can be used to solve the objective function and the solution of the objective function with the one or more adapted constraint values can be used to operate the one or more power generation units of the power plant.

Abstract: The present invention discloses a method for controlling a process using a plurality of regulatory controllers (160) connected to a remote supervisory controller (120) over a communication link (155) and to a local supervisory controller (130) over a process bus (170). The remote supervisory controller (120) controls the regulatory controllers (160) over the communication link (155) with the use of a remote process model. During operation of the plant a local process model is configured in the local supervisory controller (130) with control data send on the communication link (155). Upon failure of the communication link (155) the local supervisory controller (130) takes over the control through the process bus (170), acting as a redundant or a backup controller.

Abstract: A method is disclosed for optimization of continuous digestion process. Exemplary embodiments can control a delignification process in a continuous pulp digester in an optimal way for different pulp grades taking into account process disturbances and model uncertainties. This can be achieved by customizing a generic mathematical model for a continuous digestion process which runs through a software application on a dedicated electronic device. The model can be updated periodically based on on-line information, and used with a plant optimization component involving multi-objective optimization to evaluate optimal set points for the controllers. A system is also disclosed for optimizing control of a continuous pulp digester.

Abstract: A method and control system are disclosed for optimizing load scheduling for a power plant having one or more generation units. The method can include analyzing the operating state of one or more components of generation units in terms of one or more risk indices associated with one or more components of generation units; updating an objective function that reflects the state of one or more components of generation units; solving the objective function to optimize a schedule of the one or more generation units and operating state of one or more components of generation units; and operating the one or more generation units at optimized schedule and operating state.

Abstract: The present invention discloses a method for controlling a process using a plurality of regulatory controllers (160) connected to a remote supervisory controller (120) over a communication link (155) and to a local supervisory controller (130) over a process bus (170). The remote supervisory controller (120) controls the regulatory controllers (160) over the communication link (155) with the use of a remote process model. During operation of the plant a local process model is configured in the local supervisory controller (130) with control data send on the communication link (155). Upon failure of the communication link (155) the local supervisory controller (130) takes over the control through the process bus (170), acting as a redundant or a backup controller.

Abstract: Exemplary embodiments relate to a method and system for updating a model in a model predictive controller. The system executing a method that includes assessing the deviation of the operating performance level from the desired performance level of the process plant, and diagnosing the model predictive control for the model plant mismatch by updating the model in a model predictive controller. The step of diagnosing the model predictive controller includes determining the model prediction error in relation to model plant mismatch, quantifying the model plant mismatch, and updating the model in the model predictive controller.

Abstract: An exemplary energy auditing system and a method for obtaining a validated performance solution for a plant are provided. An exemplary system and method includes at least one processor that obtains plant data for calculating one or more performance metrics. An initial benchmark is generated using performance metrics, a tunable process model and an optimizer. A rules engine is used for applying rules based on a dynamic input on the initial benchmark and current performance metrics, and for generating an output. A decision analysis module is used for validating if the output meets the specifications of the dynamic input using a what-if analysis. If the specifications are met, then the output is provided as a validated performance solution. If the specifications are not met, then the benchmark is evolved and the validating steps are repeated.

Abstract: A method and system are disclosed for optimizing load scheduling for a power plant having one or more power generator units. An exemplary method and corresponding system can involve detecting an event indicative of a need for adapting one or more constraints for an objective function used in load scheduling. On such detection, the objective function is analysed to determine adaptive constraint values for the one or more constraints for optimally solving the objective function. These adaptive constraint values can be used to solve the objective function and the solution of the objective function with the one or more adapted constraint values can be used to operate the one or more power generation units of the power plant.

Abstract: A method and control system are disclosed for optimizing load scheduling for a power plant having one or more generation units. The method can include analyzing the operating state of one or more components of generation units in terms of one or more risk indices associated with one or more components of generation units; updating an objective function that reflects the state of one or more components of generation units; solving the objective function to optimize a schedule of the one or more generation units and operating state of one or more components of generation units; and operating the one or more generation units at optimized schedule and operating state.

Abstract: A method is disclosed for optimization of continuous digestion process. Exemplary embodiments can control a delignification process in a continuous pulp digester in an optimal way for different pulp grades taking into account process disturbances and model uncertainties. This can be achieved by customizing a generic mathematical model for a continuous digestion process which runs through a software application on a dedicated electronic device. The model can be updated periodically based on on-line information, and used with a plant optimization component involving multiobjective optimization to evaluate optimal set points for the controllers. A system is also disclosed for optimizing control of a continuous pulp digester.

Abstract: A thermoplastic composition comprising, based on the total weight of the thermoplastic composition, from 0.1 to 30 weight percent of an inorganic filler composition comprising an inorganic filler-polyorganosiloxane composite; up to 80 weight percent of a polycarbonate; and from 1 to 25 weight percent of an impact modifier. Methods of preparing the compositions and articles comprising the compositions are described.

Abstract: A thermoplastic composition comprising, based on the total weight of the thermoplastic composition, from 0.1 to 30 weight percent of an inorganic filler composition comprising an inorganic filler-polyorganosiloxane composite; up to 80 weight percent of a polycarbonate; and from 1 to 25 weight percent of an impact modifier. Methods of preparing the compositions and articles comprising the compositions are described.