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A regional logistics company with several hundred heavy trucks wanted to modernize its fleet management and reduce rig downtime.
Challenge
Mean-based schedule maintenance was undermining competitiveness as delivery times increased and margins decreased.
Management suspected that maintenance schedules were too frequent for some regional routes and not enough for others.
Solution
Devron collaborated with the business intelligence team to deploy and train machine learning models at the sensors on each rig.
Encrypted model artifacts from each location are sent back to Devron Central Authority to train the main ML model and develop a more nuanced picture of maintenance needs across routes and truck types.
Company moved from preventive to predictive maintenance which saw an over 35% reduction in downtime.