Logistics & Supply Chain
IoT and ML systems fitted to commercial vehicles that predict mechanical failures from engine telemetry — enabling proactive service before a breakdown disrupts operations.
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Industry overview
Fleet predictive maintenance systems that analyse engine telemetry and sensor data from commercial vehicles to forecast component failures — allowing proactive maintenance scheduling before roadside breakdowns occur.
At a glance
A commercial vehicle breakdown on a delivery route is one of the most disruptive and expensive events in logistics operations — combining vehicle recovery cost, cargo delay, customer impact, and driver downtime. Planned maintenance prevents some breakdowns but misses failures between service intervals. Engine telemetry provides the continuous monitoring that closes this gap.
We deploy telemetry data pipelines that collect engine diagnostic data, component wear indicators, and usage patterns from commercial vehicle fleets. Component failure prediction models use fleet-specific historical data to estimate remaining useful life for high-failure components — brakes, tyres, alternators, cooling systems. Maintenance scheduling integration creates workshop bookings at optimal times relative to route plans. Spare parts demand forecasting reduces workshop waiting time by ensuring parts are available when needed.
Key capabilities
Engagements are scoped to your business context — these are the core capabilities we bring to logistics & supply chain clients.
Engine telemetry and OBD-II data collection pipelines
Component failure prediction with remaining useful life estimation
Proactive maintenance scheduling integration with workshop systems
Fleet-specific model training on historical failure data
Spare parts demand forecasting for workshop inventory planning
Total cost of ownership modelling per vehicle and fleet segment
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