Maintenance when it is needed, not when it is due
Predictive maintenance – the scheduling of maintenance based on indications from different systems – is a valuable asset for any business that depends on advanced equipment. It minimizes the risk of unplanned downtime or even business threatening calamities.
By employing predictive models, maintenance assignments can be based on the following data:
- Asset condition;
- Asset usage;
- Assets failure modes; and
- Asset failures.
UREASON provides its customers with data extraction capabilities and data science knowledge, which allows for round the clock condition monitoring and early warnings about faults before they develop.
From data to knowledge, from knowledge to action and from action to results.
Raw asset data is complex and often not well structured. Our process steps after data extraction, are processing, cleaning and analyzing the data by using several data science techniques, with the goal of discovering useful information.
With the right data we start modelling and tuning until we have a reliable result. UREASON is unique in this hybrid approach, which can be applied to historical and real-time data.
UREASON’s data analysis results have a proven accuracy of over 90%.
How can UREASON help you?
We start with a Feasibility Study: a one-day program during which we determine with you the assets focus and the data availability in order to ascertain whether a Predictive Maintenance Program is feasible.
If feasible, we take the next step – Proof of Value – another small step to determine the value of failure prevention for the selected assets. Based on this we work with you to roll-out the predictive maintenance program(s) at your site/for your facilities.
Manage Maintenance • Do not allow it to control Operations!
Predictive Maintenance does not achieve reliability, it preserves reliability!