Automated generation of optimization model for system-wide plant optimization
AssigneeInternational Business Machines Corporation
InventorsDzung Tien Phan, Lam Nguyen, Pavankumar Murali, Nianjun Zhou
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Abstract
A computer implemented method for automatically generating an optimization model for site-wide plant optimization includes mapping a process flow diagram of a plant process to a graph comprising nodes and edges, wherein the nodes represent processes and the edges represent flows between processes. A behavior is learned for each node of the graph based at least on historic data of the plant process. One or more regression functions are modeled for each node to predict an output of each of the processes, wherein the one or more regression functions are modeled based on the learned behavior for each node.
Claims25
A computer implemented method, comprising:
- mapping a process flow diagram, of a plant process to a graph comprising nodes and edges, wherein the nodes represent processes and the edges represent flows between processes;
- learning a behavior for each node of the graph based at least on historic data of the plant process;
- and
- modeling one or more regression functions for each node to predict an output of each of the processes, wherein the one or more regression functions are modeled based on the learned behavior for each node.
A computer implemented method for automatically generating an optimization model for a site-wide optimization of a plant, comprising:
- defining a graphical representation for a process flow diagram of the plant;
- encoding a network topology of the graphical representation to generate an adjacency matrix for the graphical representation;
- automatically generating a set of equations defining the network topology;
- modeling one or more regression functions using a machine learning platform to predict an output of each process of the plant based on inputs received at each process;
- and
- generating an optimization model from the one or more regression functions for each node and the adjacency matrix, the optimization model providing setpoints for each process of the plant.
A non-transitory computer readable storage medium tangibly embodying a computer readable program code having computer readable instructions that, when executed, causes a computer device to carry out a method of improving computing efficiency of a computing device for automatically generating an optimization model for site-wide plant optimization, the method comprising:
- defining a graphical representation comprising nodes and edges for a process flow diagram of the plant processes, wherein the nodes of the graphical representation represent processes and the edges of the graphical representation represent flows between the plant processes;
- encoding network topology of the graphical representation by generating an adjacency matrix for the graph, the adjacency matrix identifying interconnected nodes;
- automatically generating a set of equations defining the network topology;
- modeling one or more regression functions using a machine learning platform to predict an output of each process of the plant processes based on inputs received at each process;
- and
- generating an optimization model from the one or more regression functions for each node and the adjacency matrix, the optimization model providing setpoints for each process of the plant.
Dependencies are inferred from the claim text.