When productivity and performance are on the line, high-value, mission-critical equipment failure is not an option.
Prevent Costly Failure, Maintain Productivity
Reduce the likelihood of unexpected operational failure and downtime costs and extend the life of high-value equipment assets with an AI-based early warning system that detects early indicators of asset failure.
In a Fraction of the Time, at a Fraction of the Cost
Boon Logic’s Amber—an AI-based predictive maintenance and condition monitoring solution—can be trained and deployed in hours instead of months or years. That’s because Amber doesn’t require highly skilled, hard-to-find talent resources like traditional AI development methods.
“During a POC for a petro chemical company on a pump, I predicted vibration anomalies 1 day in advance. No other tool I work with can do this.”
“During a POC with a printing company’s $1M printer, Boon Nano predicted a paper jam two hours in advance of the event and a paper rip 30 minutes in advance.”
– Systems Engineer with a major IoT platform
As the most cost-effective solution of its kind, organizations can take advantage of this AI-based solution to proactively reduce operational failure that’s often tied directly to service level agreements or site-level uptime objectives.
Amber is flexible in its ability to train on historical data or streaming data, in the cloud or on-premise. Plus, it works with most user interfaces via a REST API for easy integration.
In a pilot test, Amber detected an anomaly in an oil and gas pump and provided a warning 90 days in advance of failure that would have cost the company $75k had it failed. With AMBER hedging the risk of failure, the company can avoid capital equipment redundancy costs of inventorying gas and oil pumps ($50,000-$80,000) to protect against the $20,000/day cost of downtime, which typically lasts 3-4 days.
