One City Global have just launched their Predictive Maintenance Solution which with its machine learning capabilities brings far more efficiency and accuracy to your maintenance systems.

Developed under the UK Government’s Innovate programme our Digital Twin based solution enables maintenance personnel to predict, and forecast potential downtime of your critical equipment.

The Predictive Analytics engine uses data analysis models and techniques which detect anomalies in your facilities and possible defects in equipment and processes so that they can be fixed before they fail.

The system includes a number of configurable dashboards that allow users a quick overview of the data to help make informed decisions or act quickly if a situation requiring rapid intervention occurs. For example, a list of activities assigned to a specific engineer.

Data can also be made available to be incorporated into existing maintenance systems.

Savings of around 10-30% reduction in inventory levels, and around 5-15 % reduction in downtime can be realised through minimising equipment maintenance time and lost production hours. In addition to this a reduction of around 3-5% in new equipment costs are achievable.

The system is currently deployed in monitoring and predicting failures in invertors deployed on solar farms, but is configurable to use any IoT data or connect to any SCADA data output.