In unprecedented times like these, every organisation is responsibly working towards reducing person to person contact time, as well as creating contingencies for businesses to operate with limited personnel and remotely located staff.

Typically industrial maintenance has been carried out by large teams of maintenance crews and engineers. As a result of COVID-19 a large number of our clients have reduced the size of their personnel on-site to 50% normal operating levels, whilst needing to maintain the same, if not higher, production levels.

The VROC Platform with its AI predictive analytics functionality provides our clients with remote access to monitor their assets health and provide advance warnings so maintenance can be prioritised, safely scheduled and production optimised even with limited personnel. The insights obtained from the artificial intelligence modelling is specific enough to identify the exact area of fault and therefore the skill-set required to perform the maintenance, for example an electrical engineer or mechanical engineer. This removes the manual checking on equipment and the need for large teams on-site, as staff can access critical data from their mobile or tablet globally.

In one example, VROC went up against a team of reliability engineers who took 4000 man-hours to identify the root cause of a failure. The VROC platform took 90 minutes, validating the root-cause 2000x faster. The VROC platform removes manual processing and guessing, freeing up subject matter experts to do more critical tasks, limiting exposure to risk and increasing safety.

With the ability to be deployed in just a matter of days, if you are looking to maximise the value of your limited site resources please get in touch and let VROC support the focused application of your Maintenance and Reliability Teams.

Useful Resources

You might be interested in

Comparison of DataHUB+ and OSIsoft PI

Compare OSIsoft PI System to VROC's DataHUB+ and see how the two stack up against one another

Read Article

Choosing The Right Predictive Maintenance Solution

Four factors to consider when choosing a predictive maintenance solution for your manufacturing or process plant

Read Article