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Machine Learning Model for Predicting Asset Failure

Published By: Nokia
Nokia
Published:  Sep 18, 2018
Length:  8 pages

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.



Tagsmachine learning, nokia, asset management, power & energy, power asset management, energy asset management, substation, electrical substation, energy automation, power automation, energy analytics