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Intel Case Studies Predictive Maintenance Drives Smarter Fleet Management

Predictive Maintenance Drives Smarter Fleet Management

Intel
Predictive Maintenance Drives Smarter Fleet Management
Heavy Vehicle
Maintenance
Predictive Maintenance (PdM)

Fleet managers are turning to predictive analytics to stay on top of maintenance and mitigate part failures before they happen. However, managing the large amount of new data generated by vehicle sensors is challenging.

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Any organization that relies on vehicles in its daily operations understands how critical it is to keep them up and running. Whether it’s a delivery company, a school district, a telecommunications provider, or a municipality, productivity can come to a screeching halt if a vehicle so much as blows out a tire. In the new data-driven economy, predictive analytics can help businesses compete and government organizations lower costs.

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Predixion Insight* can analyze data either in the cloud or edge devices, reducing the volume of information that needs to be transmitted. Sensors on fleet vehicles collect data about tire pressure, hydraulics, and other parts. The data is sent to Intel®-based IoT gateways on the vehicle, which then process data at the edge for immediate alerts, or send it to the cloud for longer-term analysis. The integrated Wind River Helix* Device Cloud delivers centralized remote management with a cloud-based platform.

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Inventory Levels, Mileage, Parts Quality, Tire Pressure, Hydraulics
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IOT
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Fleet managers can reduce the costs associated with maintenance, while gaining control of scheduling and inventory.

There are also smaller, but important, losses that can result from deferred maintenance—for example, reduced gas mileage due to low tire pressure.

Data from these sources can be analyzed in real time on the industrial gateway in the truck to alert drivers of imminent failures, or pushed via the gateway to the cloud, for analysis by corporate headquarters and operations.

Reducing data transmission costs

It processes and analyzes data in real time to provide immediate predictions as to pending failures.

Reduce downtime and slash maintenance costs

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