Technical Inspection Scheduling

Predictive maintenance for enterprise fleets

The technical inspection scheduling module uses machine learning algorithms to estimate the optimal service time, based on operating hours, distance traveled, and driving style. Integration with partner workshop calendars enables automatic slot booking, and proactive notifications prevent penalties for exceeding inspection deadlines. Companies thus reduce maintenance costs by up to 30% and extend vehicle lifespan.

What Fleet Operators Say

Real feedback from companies using Logistica Mobilitatii for enterprise fleet management

Gabriel Baciu

Fleet Manager, 350 vehicles

predictive maintenance

„We reduced maintenance costs by 28% in the first 6 months. The inspection planning algorithm flagged gearbox issues before they became major breakdowns. Without this system, we would have lost at least 3 vehicles per month.”

Carla Szekely

Logistics Director, 220 light commercial vehicles

route optimization

„Route optimization reduced our monthly mileage by 17% and diesel consumption by 12%. We eliminated 4 inefficient routes that generated overhead costs of over 8,000 lei per month. The dashboard is intuitive, and geofencing alerts have reduced our operational risks.”

Mihai Popescu

Mixed Fleet Manager, 180 vehicles

real-time monitoring

„Real-time monitoring gave us complete visibility over the mixed fleet. We identified drivers who systematically exceeded the speed limit and reduced the number of incidents by 40%. Integration with CAN-bus sensors provided precise data on instantaneous consumption.”

Andreea Ionescu

Operations Coordinator, 280 vehicles

operational leasing

„Managing operational leasing contracts was a nightmare until we implemented the solution. Now we have all inspection deadlines and penalties centralized. We reduced administrative costs by 35% and no longer miss return deadlines.”

Radu Dumitrescu

Logistics Manager, 420 vehicles

technical wear

„The technical wear calculation allowed us to plan vehicle replacement at the optimal time, not when they broke down. We extended the fleet's lifespan by an average of 14 months. The machine learning algorithm accurately estimates service timing based on driving style.”

Ioana Marinescu

Fleet Department Head, 190 vehicles

cost reduction

„Corporate overhead expenses decreased by 22% after implementation. Route optimization and inspection planning freed up resources for other projects. Proactive notifications for missed inspection deadlines saved us from fines.”

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