Updated platform launched for predictive maintenance of grinding machinery
ABB has released a new version of its Ability Predictive Maintenance service for grinding, which is now cloud based and includes a mobile application allowing real time notifications on fleet status.
The upgraded service supports the maintenance, assessment and analysis of gearless mill drive (GMD) systems used in mining and promises to help extend asset lifetime and avoid unforeseen downtime.
It provides easy access to GMD system parameters and allows visualisation of performance – considering past activity and real time data – as well as assessing future maintenance requirements.
The Grinding Connect mobile app, available for iOS and Android, means that mine operators can monitor performance at any time and from any place.
“A gearless mill drive is a major investment and its availability is essential for the process,” said ABB’s global product manager for grinding service in mining Angeles Fernandez. “Unscheduled shutdowns and system failures can lead to significant losses in production.”
He added: “ABB Ability Predictive Maintenance for grinding is a state-of-the-art service for analysing system data, assessing the current condition of the equipment and applying predictive methods.
“The new version is unique in the market and the new Grinding Connect app means you can check that your GMD is performing through your phone or tablet.”
The updated service is also said to facilitate greater data gathering. The data sample per mine is increased and analytics and trends are more reliably defined, it is claimed. ABB says the solution offers a new user experience with fully customizable dashboards, alarms and events all available on the mobile app.
GMDs are the preferred grinding solution at mines characterised by higher capacity production coupled with low ore grades. By eliminating bolt on mechanical components such as ring gears, pinions, couplings and gearboxes, GMDs offer ore producers unrivalled availability, efficiency and durability, while reducing OPEX.
