Predictive Maintenance Software
Through Oneserve’s diverse integration capabilities, our job management solution can be paired with your predictive maintenance provider of choice to offer you a complete repairs and maintenance management solution.
Key benefits of Predictive Maintenance Software
Optimise machine performance
Through integrating with a predictive maintenance partner, Oneserve can alert you to when a part within a machine is likely to fail before any downtime has occurred. This means that you can continue to carry out any essential maintenance and operate with minimal disruption.
Manage critical assets remotely
Predictive maintenance enables you to continually monitor your assets through alerting your schedulers if a fault occurs. This allows a site visit to be arranged to resolve the problem before it has any impact.
Maximise KPI performance
Predictive maintenance leverages big data, AI (Artificial Intelligence) and IoT (Internet of Things) to continually monitor assets and learn from job histories. This enables you to predict problems or potential failures before they happen, to significantly increase efficiencies.
Key features of predictive maintenance software
Failures are identified
A resolution is booked
Information is continually used
Trusted by...
Islington Council
An overview of Predictive Maintenance
Traditionally, your repair work will have been reliant on a part failing or a tenant notifying you of a problem. Without this, you wouldn’t have even known there was an issue to resolve. This process means that whatever has failed, has already had an impact on your service delivery and the cost to rectify the issue can quickly escalate.
Oneserve’s job management software can easily connect with your predictive maintenance solution, whether that uses Internet of Things (IoT) or Artificial Intelligence (AI) learning as it’s source, to ensure your organisation can be proactive rather than reactive in its approach to identifying repairs.
FAQs
What is predictive maintenance software used for in buildings?
Predictive maintenance software uses the Internet of Things (IoT) or Artificial Intelligence (AI) to monitor the efficiency of an asset based on the data that is collected. Anomalies in asset performance can be identified so that processes can be put in place to fix them before they result in asset failure.
What are examples of predictive maintenance?
From the perspective of building maintenance, the Internet of Things (IoT) uses connected devices and sensors to monitor asset performance. This provides precise, real-time data, which helps us identify anomalies and trends in asset performance, and gives us the insight needed to make the most informed and proactive maintenance decisions. This predictability and asset visibility, lowers the overall amount of downtime and reduces maintenance costs.
How can predictive maintenance help improve performance?
Predictive maintenance reduces unscheduled asset downtime that has been caused by a fault or system failure. With less asset downtime, your operatives will spend less time completing emergency repairs so their time can be utilised more effectively. Your organisation costs associated to preventative asset maintenance will be reduced and the lifespan of ageing assets can be increased as real-time monitoring will highlight any issues before they evolve into major, costly problems.
