Quanovo | Data Technologies | Liverpool

Predictive Maintenance

Predictive Maintenance


Predictive Maintenance solutions aim to predict equipment or machine failures before they happen. Previously companies would use Preventative Maintenance techniques instead of predictive ones. This involved mostly a strict schedule of maintenance that every key machine or piece of equipment would be subject to. This made two things inevitable, firstly that downtime had to occur and secondly that maintenance teams would need to be paid to do the maintenance. Now companies are utilising Predictive Maintenance solutions it means that they only need to take equipment or machinery offline when they system reports that a failure is likely to occur. This results in less downtime, less cost in maintenance resource deployment and because these systems report likely failures well ahead of time it means that plans can be put in place to minimise impact as well.

Using advanced algorithmic techniques it is possible to create predictive models that detect even minor anomalies and failure patterns that can indicate your assets are at risk of failure in the near future.

Our predictive solutions can be tailored to either work with your existing maintenance record data or with sensor data to provide a more accurate prediction or even a real-time overview of the condition of the equipment and machinery that is key to your business.




Failure Prediction

Monitor your equipment’s health to intervein before potential problems occur. Consolidate the untapped data created by your assets to create proactive maintenance schedules, decrease downtime, and improve retention of the equipment or machinery value.

Reduce Costs

Being able to predict when your equipment or machines will fail and also how they are likely to fail will allow you to optimise your maintenance resource allocation and even possibly reduce the number of maintenance resources you must maintain to keep your business operational.

Increased Uptime

Preventative Maintenance scheduling means that sometimes the maintenance your business carries out is not necessary at that time. Knowing when maintenance or repairs are necessary reduces the number of maintenance jobs and means that they occur on a schedule that works for you.

Real Time

Making use of the power of The Internet of Things (IoT) it is possible to combine our predictive models with streaming data from sensors and therefore instantly recognise warning signs to proactively initiate maintenance and repairs.




Large Payback Value

The expense involved in setting up a Predictive Maintenance solution is usually quickly recovered in increased machine efficiency and decreased down time.

Anticipate Issues

Gain the ability to plan and budget ahead of time for costly failures before they occur.

Reduce Spare Part Stockpiles

No longer will you need to incur the cost of stockpiling spare parts for your key machines as you will be able to order these parts in advance of failures.

Reduce Administrative Costs

Using sensors to monitor and report information about machinery or equipment and having a Predictive Maintenance solution schedule maintenance automatically means that you are able to reduce the administrative cost to your business.

Reduce Unnecessary Degradation

Using the correct sensors it is possible to create a Predictive Maintenance solution that can inform you if you equipment or machinery is heading for failure quicker than expected and why.

Improve Customer Satisfaction

Predictive Maintenance solutions allow you know about the chance of failure in advance meaning that you can reduce the impact of equipment failure on your customers. If failure is predicted you can plan around it to meet your customers’ demands in time.