Energy, Oil & Gas
Energy, Oil & Gas
Predict problems in advance with machine sensor data, using analytical models.
When there are problems, diagnose them with root cause cause analysis tools so that you can take corrective actions quickly.
Why this is important
The energy mining sector loses millions of dollars anually due to system failures, tube depressurisations, power loses or machine failure.
If the industry could predict failures in advance to take corrective and preventive measures, the associated costs would be significantly reduced by increasing the margin thanks to operational efficiencies.
a. ontrol of the result: Meet the deadlines and production volumes with fewer unplanned interruptions thanks to automated control panels and alarms that notify operational staff and managers, not only of failures that have occurred but also of future ones obtaining predictive ability to solve problems before they happen.
b. Optimize maintenance cycles: Progress towards predictive and prescriptive maintenance strategies by addressing the root causes of failures and predicting the degradation of productive performance that usually increases costs. Avoid parts replacement costs thanks to proactive maintenance and timely indicators of impending failures.
c. Digital world: Avoid investing time in correcting or repairing process elements that are not the root cause of the problem. Detect hidden patterns in the data to show the origin of future failures.
d. Reduce downtime: Avoid long periods of inactivity in the machines avoiding potential performance problems before they escalate to greater losses thanks to automated monitoring and predictive alerts. Manage research cases to proactively control future damages.