AI for logistics: route optimisation and predictive fleet maintenance
WYnova applies artificial intelligence in logistics and transport to plan routes based on traffic and delivery windows, and to anticipate fleet breakdowns from telemetry.
Contact WYnovaCommon challenges in the sector
Routes planned by hand, without accounting for traffic or delivery windows.
Unplanned breakdowns that interrupt deliveries and jeopardise deadlines.
No real-time visibility of the fleet.
Route optimisation and predictive maintenance
Challenge
Complete more deliveries with fewer kilometres travelled and fewer vehicles off the road due to breakdowns.
Proposed approach
An optimisation engine recalculates routes based on traffic and delivery windows. A machine learning model reads each vehicle's telemetry and anticipates breakdowns. Both feed a single control tower, connected to the fleet management systems the company already uses.
Expected result
Fewer kilometres per delivery, fewer unplanned breakdowns and maintenance scheduled before failure, with the entire fleet visible in one dashboard.
Technical areas: ML, Data Eng, Integration, Telemetry
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Retail
Demand forecasting and automatic replenishment by store and SKU.