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Home > White Papers > Nokia > Machine Learning Model for Predicting Asset Failure

Machine Learning Model for Predicting Asset Failure

By: Nokia

This paper examines the benefits of using advanced machine learning models in predictive maintenance software for asset-intensive industries. It discusses how the latest predictive maintenance software solutions go beyond condition-based maintenance (CBM) models where asset replacement is based on average engineering-determined condition thresholds for replacing assets in the same class.

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Published:  Sep 18, 2018
Length:  8
Type:  White Paper
Tags : 
machine learning, nokia, asset management, power & energy, power asset management, energy asset management, substation, electrical substation

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