Predictive Maintenance leverages your existing data to pinpoint risks of failure, alert the appropriate user of that risk and guide them through a series of steps to prevent the failure from happening. This delivers value in three key areas:
1. Prevents downtime of expensive, revenue-generating equipment;
2. Reduces risk of potentially dangerous or hazardous equipment failures; and
3. Reduces operational costs by replacing time-based proactive equipment replacements with
“just in time” maintenance.
With Predixion, you can analyze your historical maintenance logs and data streaming from devices to find patterns in your data that cannot hide from machine learning, but could easily hide from the human eye. Then you can deploy that analytic model in real time in a variety of environments – either in the Cloud, on the gateway, or directly on the device – to analyze your current data and warn you in advance of potential failures and risks. The result is lower operational cost and improved efficiencies.
Here's how it works:
- Gather and pre-process data from equipment sensors and maintenance logs into predictors
- Quickly build predictive model using Predixion Insight platform
- Deploy production-ready model pushed into a variety of environments, such as Complex Event Processing (CEP) servers, databases or applications
- Continuous processing of event streams from multiple sources
- Thousands of predictions scored per second in memory with near-zero latency
- Reports in real-time on potential failures
- Pushes alerts to the front lines where the information is most actionable
Predixion is the only advanced analytics vendor that is capable of deploying predictive models either in the Cloud, on the gateway or directly on to a device or a machine—so we can best support the unique requirements of organizations dealing with the data deluge produced by the Internet of Things (IoT)—where automated actions are often required to be “close to the edge” or “on the edge.”
To find out more, please contact us.