IoT-based predictive maintenance for the energy sector

IoT-based predictive maintenance for the energy sector

Optimising equipment can be hugely beneficial to all sectors – but in energy, where the value of projects is often so high, this is especially important. It’s estimated that an hour of downtime can cost more than $2mn – so having in place a system that can enable robust predictive maintenance has a huge return on investment potential. 

Not only is uptime critical for end users, but increasingly so for equipment manufacturers themselves. Where equipment fails, those hiring it may not get paid – while users miss out on the required service.  

A lose-lose situation, and a very expensive one at that.  

Remotely monitoring equipment and collecting the data required to build a predictive maintenance tool, application or digital twin is paramount – but in areas with patchy connectivity, there’s no guarantees.  

Krucial CONNECT – ultra resilient connectivity 

Krucial CONNECT harnesses the power of IoT and satellite technology to provide continuous insights into asset health.  

Its hybrid connectivity system utilises cellular and multiple satellite backhauls to transmit IoT data to the cloud – switching automatically depending on availability – meaning if cellular goes down, data still flows.  

On remote sites, this is critical, and can be the difference between downtime and uptime – and millions of dollars. 

Proactivity is key 

The proactive nature of IoT predictive maintenance is its cornerstone. Through the establishment of customisable thresholds and alerts, decision-makers gain the ability to anticipate potential issues before they escalate, facilitating timely interventions and minimising downtime. 

From a broader perspective, the implications of IoT predictive maintenance extend beyond individual assets to encompass entire energy platforms and sites. By aggregating data from diverse sources and centralising monitoring through a single system such as Krucial CONNECT, users can simplify IoT deployments and ensure they have the most efficient solution possible.  

To learn how Krucial CONNECT can support predictive maintenance models for the energy sector get in touch.


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