How Carolina Cat is Using AI to Scale Machine Monitoring Capacity and Drive Revenue

For today’s heavy equipment dealerships, connecting machines, ingesting alerts and filtering those alerts for service sales leads is a huge growth opportunity. See how one Caterpillar dealership leveraged new technology to monitor its machines at scale.

Since 1926, Carolina Cat has delivered superior service, parts and new machine sales for construction, power generation and highway truck equipment. Carolina Cat is an innovative dealership that’s always looking for ways to keep bringing exceptional service to its customers.

One way Carolina Cat does that is by implementing new technologies that enable the dealership to drive even greater value from its assets.

Using AI to Scale Digital Processes

Carolina Cat excels at using digital technologies to help boost the value being delivered by its machines. But that’s much easier said than done. The dealership’s digital processes have created an overabundance of machine alerts, making it very challenging to separate signal from noise and maximize the value of its digitally connected assets.

To improve its ability to filter through alerts and create cases more efficiently, Carolina Cat turned to artificial intelligence (AI) to amplify its analytics program. The goal was to empower its existing team to cover even more alerts using automated case recommendations.

By adding Uptake’s AI-driven asset performance management (APM) application, Asset IO, Carolina Cat sought to:

  • Refine the firehose of raw, low-quality machine fault code alerts into a pipeline of targeted, high-quality insights — improving its 1% reviewed-in-case rate.
  • Automate the creation of repeatable cases.
  • Extend its monitoring capacity to cover additional machines, eventually being able to monitor all connected machines in the field.

Using industrial data science, Uptake Asset IO generates insights that help improve machine health and financially optimize maintenance strategies. See how Carolina Cat was able to use the power of AI to dramatically improve its machine monitoring and maintenance across 6,000 assets dispatched in the field:

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