Predicting when a specific machine or component or service may fail, based on the history of earlier failures, additional causal parameters like temperature, voltage, vibration, load or performance counters have many uses since it allows operation teams to take preventive actions e.g., procuring spare parts or performing other activities like checking electrical connections or wear or tear condition etc. Prediction typically reduces cost of maintenance and improves customer satisfaction. Prediction of failure is of huge importance when it relates to assets used for basic services like telecommunication, transportation, manufacturing, process industries etc.

Our patented universal prediction algorithm, simply provides fault and degradation prediction based on data as minimal as 3 to 6 months of historical alarms (faults). The same algorithm predicts faults for assets used in varied industries like Telecommunication, Data Center, manufacturing etc.