Predictive maintenance: the ALSTEF Group achieves 99.9% availability of equipment at Zagreb airport thanks to BL.Predict!
It is now strengthening its CMMS project with the deployment of the BL.Predict predictive maintenance solution , a new Internet of Things (IoT) platform in which all equipment data (conveyors, carousels) is collected and processed. through artificial intelligence.
For several years, ALSTEF's predictive maintenance strategy has been based on R&D co-managed with CARL Berger-Levrault in order to:
- Monitor the maintenance of its client sites using indicator monitoring.
- Optimize processes.
- Establish preventive maintenance ranges.
- Achieving a level of excellence on the sites of airport customers.
As part of a continuous improvement approach , ALSTEF is now also equipped with the CARL Touch mobile CMMS solution to facilitate field interventions. The application assists technicians in their daily tasks, from smartphone notification, geolocation of intervention sites, access to the history of operations carried out on the equipment to the report at the foot of the machine.
For ALSTEF, CMMS occupies a strategic place in its business model . The combination of CARL Source , CARL Touch mobility and the BL Predict predictive maintenance platform optimizes the quality of service provided to ALSTEF customers by improving the lifespan of equipment, team activity, inventory management and reducing maintenance costs . This is why the specialist in automated solutions intends to extend the CARL Berger-Levrault solutions to all of its sites, starting with the Mexico City airport site in the coming months.
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