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Machine Learning Model for Predicting Asset Failure

By: Nokia
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.

Tags : machine learning, nokia, asset management, power & energy, power asset management, energy asset management, substation, electrical substation, energy automation, power automation, energy analytics, infrastructure, internetworking hardware, network architecture, business activity monitoring, business analytics, business management, analytical applications, power and cooling
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Published:  Sep 18, 2018
Length:  8
Type:  White Paper