Technology Category
- Networks & Connectivity - Cellular
Applicable Industries
- Automotive
Applicable Functions
- Logistics & Transportation
Use Cases
- Vehicle Telematics
About The Customer
A global leading electronic car manufacturer
The Challenge
A global leading electronic car manufacturer needed to guarantee a seamless connectivity experience for its fleet of 50,000 vehicles as they are driven throughout Europe.
The Solution
Asavie IoT Connect delivers connectivity across multiple regions via a single global SIM, providing reliable secure network connectivity for each car.
Data Collected
Connectivity Status, Telematics data, Vehicle diagnostics , Vehicle Location Tracking, Vehicle Status
Operational Impact
Case Study missing?
Start adding your own!
Register with your work email and create a new case study profile for your business.
Related Case Studies.
Case Study
Integral Plant Maintenance
Mercedes-Benz and his partner GAZ chose Siemens to be its maintenance partner at a new engine plant in Yaroslavl, Russia. The new plant offers a capacity to manufacture diesel engines for the Russian market, for locally produced Sprinter Classic. In addition to engines for the local market, the Yaroslavl plant will also produce spare parts. Mercedes-Benz Russia and his partner needed a service partner in order to ensure the operation of these lines in a maintenance partnership arrangement. The challenges included coordinating the entire maintenance management operation, in particular inspections, corrective and predictive maintenance activities, and the optimizing spare parts management. Siemens developed a customized maintenance solution that includes all electronic and mechanical maintenance activities (Integral Plant Maintenance).
Case Study
Monitoring of Pressure Pumps in Automotive Industry
A large German/American producer of auto parts uses high-pressure pumps to deburr machined parts as a part of its production and quality check process. They decided to monitor these pumps to make sure they work properly and that they can see any indications leading to a potential failure before it affects their process.