ABB uses QuasarDB as its predictive maintenance backend

11 March 2019

Should you wish to view the original article in French, please click here.

Together, TellMePlus (publisher of analytical platform Predictive Objects) and QuasarDB allow real-time comparison of data from multiple sources (sensors) with historical data, to anticipate previously unpredictable incidents. Today, Tellmeplus has integrated QuasarDB's time series database into its SaaS Predictive Objects platform, allowing predictive models to be deployed in any connected object or system.

"The integration of time-series oriented scalable data storage into our predictive analytics solution is the key to the effective deployment of predictive models on any type of object or platform," said Benoit Gourdon, CEO of Tellmeplus.

Tellmeplus demonstrates, the value of integrating QuasarDB into its Predictive Objects platform in a project for ABB.

ABB approaches predictive maintenance in two ways: by helping its customers avoid unexpected downtime of their equipment and by enabling its customer service to speed up breakdown diagnostics to identify the most appropriate action(s) once the equipment has broken down. It is on these aspects that Tellmeplus intervened, relying on QuasarDB.

Tellmeplus' Predictive Objects solution is now being implemented within ABB Drives for medium voltage equipment. ABB and Tellmeplus - with the help of QuasarDB - share a common goal: to create value for end customers and provide ABB with new innovative and agile solutions.

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