Condition-based maintenance
Changing from use-based to condition-driven maintenance of compressors and turbines gives 80% increase in time between outages and 60% decrease in outage duration.
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Filtering cooling water
Keeping cooling water clean with full-flow filters improves equipment reliability.
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Modernizing turbine controls
A new system improves turbine reliability and availability, consolidates data reporting and archiving, and offers plant-wide, single-interface control.
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Prevent catastrophic motor failures with current signature analysis
Online and offline analysis using standard tests including current signature analysis (CSA) and demodulated current spectrum analysis (DCSA) identify incipient failures in time to prevent catastrophic failures and unplanned downtime.

Several example facilities saved as much as $280,000 in motor repair/replacement and downtime costs.
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Increase quality production by identifying underperforming process control assets
Using real-time data directly from existing control systems, software focuses attention on underperforming components of the control system.

By exceeding expected production targets and discovering hidden process performance opportunities, a cracker operation is on track for a full return on investment within six months of start-up.
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Reduce downtime by coordinating maintenance activities with reliability software
A steel company was able to bring together a wide range of equipment condition data, including maintenance inspections, operator rounds and online information, using reliability software. The more complete picture of equipment health and performance, online in real time, allows automatic tracking and alarming on asset condition, triggering online or email alerts and driving corrective work orders into the CMMS.

Significant improvements in asset performance include an 88% reduction in downtime at the company’s rod mill and a 30% increase in meltshop throughput.
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Improve refinery reliability with alarm rationalization
Years of configuring alarms at multiple levels without rationalization led to more than 5,000 tags configured with alarms, each having as many as six or more alarms. Managing alarms was becoming increasingly time-consuming and problematic for the process control team.

Instead of embedding alarm management in a new DCS, the plant implemented a separate system to manage alarms for both new and existing DCSs. The plant performance level went from stable/reactive to robust in four months, with 261 tags rationalized.
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