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Use CaseOperationsManufacturing & Industrials / Machinery, equipment and components

Predict maintenance requirements

Improve preventative maintenance and Maintenance, Repair and Overhaul (MRO) performance with greater predictive accuracy to the component and part-level. Predictive maintenance predicts when certain products or devices are in need of maintenance what sort of maintenance, the likely maintenance and replacement materials, and technician skill sets.

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Operational

Operational - Increased machine uptime

£

Cost

Cost - Optimise resource allocation

£

Cost

Cost - Asset uptime optimisation

Description

Predict maintenance requirements

Linked Case Studies

Siemens Gamesa Renewable Energy

Siemens Gamesa Renewable Energy reduces inspection time of wind turbine blades by 75% by using non-destructive testing

IBM launches Equipment Maintenance Assistant to predict equipment maintenance requirements and aid technicians in diagnosis and repair using machine learning

EDF Energy wishes to monitor power station conditions in real time and predict maintenance requirements using machine learning

Enedis reduces high-tension electrical grid outage with predictive maintenance using supervised learning

Origin achieved 80% accuracy in identifying low production wells and $50M in savings using machine learning applications from C3 IoT

Big River Steel

Big River Steel predicts and optimises the maintenance of its machinery and equipment using machine learning.

Enel Green Power North America and Raptor Maps streamline solar facilities’ faults detection using machine learning

NASA successfully researchers detection of anomalies in rocket propulsion using machine learning

San Diego County

San Diego plans to implement predictive building management and maintenance software from Site 1001 to improve operations efficiency

Shell predicts maintenance requirements for its equipment with the use of machine learning

Rolls Royce to identify operational issues in advance using machine learning analytics

Dubai Airport enhances customer experience by doing predictive maintenance using machine learning

London Fire Brigade

The London Fire Brigade identifies the areas prone to fires in ducting systems to provide targeted maintenance using natural language processing

Deutsche Bahn reduces maintenance cost by 25% and delay-causing failures using machine learning

Rolls Royce plans to predict maintenance requirements for jet engines to improve aircraft efficiency using Microsoft Azure''s machine learning

US Army plans to test machine learning for predictive maintenance on combat vehicles

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Source: kaggle.com · Editor: original-sdg