Method for online service policy tracking using optimal asset controller

A method and system of providing customizable service for an asset. The method including generating a predictive model for each asset of a fleet, each predictive model based on an operational profile for the asset and including a probability density function associated with the operational durabilit...

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Bibliographische Detailangaben
Hauptverfasser:	Vrabie, Draguna, Frewen, Thomas A, Chen, Mei, Mostafa, Hala, Erdinc, Ozgur
Format:	Patent
Sprache:	eng
Schlagworte:	ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDEDFOR ELSEWHERE CALCULATING CHECKING-DEVICES COMPUTING COUNTING DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES GENERATING RANDOM NUMBERS MEASURING PHYSICS REGISTERING OR INDICATING THE WORKING OF MACHINES SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR TESTING TESTING STATIC OR DYNAMIC BALANCE OF MACHINES ORSTRUCTURES TESTING STRUCTURES OR APPARATUS NOT OTHERWISE PROVIDED FOR TIME OR ATTENDANCE REGISTERS VOTING OR LOTTERY APPARATUS
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Beschreibung
Zusammenfassung:	A method and system of providing customizable service for an asset. The method including generating a predictive model for each asset of a fleet, each predictive model based on an operational profile for the asset and including a probability density function associated with the operational durability of the asset, establishing a maintenance strategy associated with the asset, and combining each of the predictive models to generate a compound fleet performance model, the fleet performance model including a combined probability density function. The method also includes collecting actual asset performance and maintenance data to generate actual asset metrics, determining a fleet performance profile based on the actual asset metrics indicative of a health assessment of the fleet, comparing the predicted fleet performance with the actual fleet performance, and ascertaining actionable choices for managing the assets based on a deviation of the predicted and actual fleet performance.