Shell Predictive Maintenance Rotating Equipment

Detect rotating equipment anomalies early to improve availability and reduce maintenance cost of rotating equipment

Monitor the health of key rotating equipment classes including centrifugal pumps, centrifugal compressors, dry gas seals and turbines and mitigate their failure risk in advance through AI-driven alerts.
Leverage specialist knowledge by using codified rotating equipment expert insights to detect anomaly events in the process, equipment, and auxiliary systems, assess possible causes and recommend preventative measures.
Detect deviations from the baseline through AI alerts that indicate a potential fault in rotating equipment.
Deploy proven machine learning models tailored for rotating equipment with preconfigured algorithms, hyper-parameters, and thresholds to enable early detection and reduce false positives.
Understand rotating equipment health at enterprise scale, with a simple and extensible rotating equipment onboarding process, asset templates, documentation and monitoring tools.
Enable engineers to intervene before issues become uptime problems.
Improve turnaround efficiency and focus areas by using a data-driven approach that highlights deviations between target and actual behaviors to prioritize equipment and maintenance tasks.
Seamlessly embed insights on rotating equipment performance into BHC3 Reliability and exception based surveillance workflows.

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