CASE STUDY

Sensor Analytics Reduces Vehicle Breakdown and Delivers USD 6 Million Savings for a Logistics Company

Sep 23, 2016

Business Challenge

Proactive vehicle maintenance for better asset utilization

A freight and logistics company wanted to set up a statistical model for predictive vehicle maintenance and improve vehicle life.

Situation: Setting up predictive model for proactive vehicle maintenance

Client wanted to set up a predictive model for monitoring the utilization of its road fleet, and the health and lifecycle of the vehicles, in order to ensure on-time maintenance scheduling and improvement in performance, reduce vehicle breakdown chances and improve the asset lifecycle.

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Solution

Sensor data analytics, vehicle performance measurement and asset utilization analytics

We extracted the sensor data from all vehicles, utilized Fourier & SVM algorithm for data transformation, and further analyzed them through real-time monitoring, asset utilization analytics and predictive modeling, for alerts on the vehicle performance, upcoming maintenance, and servicing and scheduling preventive maintenance.

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Impact

Reduction in vehicle breakdown by 70%

The client utilized our predictive monitoring system tracking of all its vehicles’ usage and received real-time alerts on any potential vehicle breakdown, which enabled it to schedule preventive processes for maintenance & repairs. The client reduced vehicle breakdown by 70% and realized USD 6 million in savings.

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