Trucking is a distance business, yet profitability for truckload and less-than-truckload operations is not a simple cost-per-mile calculation. Even if two distances are equal, the cost per mile will differ by the customer, vehicle, shipment or driver.
The reason? Time, more than miles, determines fleet productivity and profitability. Any time assets are not moving is lost revenue and added cost. To maximize the uptime of assets, fleets will need to know in advance what systems and components will fail, and when and why, to proactively schedule repairs for drivers and assets to keep rolling.
A solution to the uptime challenge is predictive maintenance. Fleets have traditionally equated this with remote diagnostics services from Original Equipment Manufacturers (OEMs) that decipher fault codes and help fleets schedule over-the-road repairs. Although big strides have been made with remote diagnostics, predictive maintenance doesn’t stop there.
New advancements can deliver predictive insights on vehicle problems before fault codes appear. With this information, fleets can proactively manage equipment to prevent more breakdowns and unplanned maintenance events.
Reaching the Limits
Telematics systems can monitor data in the controlled area network (CAN) of vehicles to detect and transmit engine fault codes. Starting in 2010, OEMs began using telematics to launch remote diagnostics services for their customers.
When fault codes appear, OEMs send fleets an email notification that links to a Web portal that provides information about the problem and services to locate nearby dealers and schedule repairs if needed.
Remote diagnostics have come a long way but have limitations that include:
Information overload. Even with OEM assistance, the volume of fault codes that fleets have to manage can be overwhelming. Larger fleets may encounter hundreds or even thousands of fault codes per day.
Missed opportunities. Some fault codes require immediate action. Others are less critical. Having to sift through all the noise can make it difficult to plan and schedule vehicle repairs during upcoming PM services.
Not seeing the big picture. Fleets are managing information from one truck at a time. Many outliers can only be identified by analyzing data to find developing trends for certain makes and models to correct problems before they become critical.
Ignoring the root cause. A fault code is a symptom of the problem. Finding the root cause often requires further analysis to understand how a vehicle is being operated.
Putting Insights into Action
New developments in predictive maintenance systems take fleets beyond remote diagnostics. Advanced data models give comprehensive insights from analyzing past repair data from work orders as well as analyzing granular vehicle data from real-time sensor readings and fault codes.
The vehicle sensor data is obtained through integrations with telematics providers, such as Geotab, and from factory-installed OEM telematics platforms. The advanced data models use algorithms to normalize vehicle data, such as engine load and operating temperatures, to detect anomalies.
The outputs of the predictive models are insights that can be used by maintenance managers to confidently schedule work to prevent breakdowns and over-the-road repairs. Also, operations managers can use insights to maximize uptime and truck availability while controlling costs.
Predictive insights can help fleets prevent breakdowns, such as those that happen when vehicles have malfunctions in their emission systems. Problems can be detected before fault codes appear by monitoring for abnormal readings coming from a NOx sensor, for example.
When a NOx sensor begins to fail it produces faulty temperature readings that cause an engine to burn excess fuel, which increases the risk of a truck going into a derate state that requires a tow.
Besides identifying problems at the earliest stage, insights help fleets determine the root cause by providing robust data analytics. Armed with this information, fleets can determine which items need more immediate attention, and which items can safely be added to a vehicle’s next PM schedule — such as adding a pressure check of the cooling system for vehicles that have anomalies like temperature spikes.
Get the Full Picture
The benefits of using predictive insights to move beyond remote diagnostics are clear. On average, fleets that are using insights to make better decisions and prioritize have seen a:
12% reduction in maintenance costs
20% reduction in breakdowns
15% increase in vehicle availability
The Uptake Fleet platform applies the latest advancements in data science with industry expertise and cloud computing to generate best-in-class predictive maintenance insights. Granular vehicle data collected through Geotab telematics is analyzed by the trained models of Uptake Fleet to enhance lead times for addressing vehicle, engine and component failures.
With Uptake Fleet, maintenance operations can proactively schedule repairs, reduce over-the-road risks, and improve vehicle performance. More uptime equals a better bottom line.
Learn more about how to put predictive insights to work by downloading “The Ultimate Guide for Maximizing Vehicle Uptime.”
