IMPROVING THE REAL-TIME OPERATION OF AN INDUSTRIAL FACILITY USING A MACHINE LEARNING BASED SELF-ADAPTIVE SYSTEM

IMPROVING THE REAL-TIME OPERATION OF AN INDUSTRIAL FACILITY USING A MACHINE LEARNING BASED SELF-ADAPTIVE SYSTEM

The disclosure provides a method and system of improvement in the real-time operation of a terminal station in an industrial facility using a machine learning-based self-adaptive system comprising obtaining real-time operations data and historical data stored in a local database or at a cloud-storag...

Ausführliche Beschreibung

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Bibliographische Detailangaben
Hauptverfasser: SUBRAMANYA, Srikanth Olety, RAO, Parag Ravindra, KISHORE, Koyalkar Raman, SUMANTH, Pachipulusu Lingesh, RAMEGOWDA, Yogesha Aralakuppe
Format: Patent
Sprache:eng ; fre ; ger
Schlagworte:
CALCULATING
COMPUTING
COUNTING
DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES
PHYSICS
SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR
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Beschreibung
Zusammenfassung:The disclosure provides a method and system of improvement in the real-time operation of a terminal station in an industrial facility using a machine learning-based self-adaptive system comprising obtaining real-time operations data and historical data stored in a local database or at a cloud-storage. The data relates to input parameters of the terminal station. The method includes inputting the input parameter to a machine learning configurable module of the machine learning-based self-adaptive system and analyzing the input parameter using dynamic machine learning models and algorithms to identify patterns to each of the input parameters. The method further includes evaluating the identified pattern against the real-time operations data obtained from the terminal station and predicting at least one output parameter based on the input parameter and the identified pattern against the real-time operations. Based on the prediction, adjusting the output parameter of the real-time operations data.