Aging Fleets Call for Predictive Maintenance

The average age of heavy-duty trucks continues to climb upward. What does the trend — which predates the supply chain disruptions that have slowed new vehicle production — mean for transportation and logistics?

In this blog, we’ll cover why fleets are running aging equipment, how they’re dealing with downtime, combatting warranty expirations, and two key ways that predictive maintenance is helping aging fleets run reliably.

First, some good news. Longer asset lifecycles can be a silver lining for transportation and logistics. Durable equipment tends to be more sustainable and less capital-intensive.

The shortage of semiconductors has slowed down the fabrication of new computer chips, which are used to power the most basic features of new vehicles today. Equipment longevity is a significant reason why fleets have been able to move record volumes of cargo without new vehicles.

Now, some not-so-good news. A shortage of spare parts, also due to supply chain disruptions, has fleets dealing with longer-than-usual time in the shop.

In some shops, downtime has dragged on to more than two months for vehicles waiting on spare parts. Two weeks would have been the upper limit pre-pandemic, but the longer times offline are now a reality that carriers must address.

Without a clear ramp-up to new vehicle production, trucking companies have pushed back procurement cycles and dealt more heavily in a hot used vehicle market.

Inventory and availability challenges are stretching vehicle reliability. Class 8 truck utilization is north of 80% for the average fleet, and vehicles are depreciating quicker than normally.

Trucking companies are seeing an increase in issues related to heavier duty cycles. Shops are experiencing more exhaust system repairs now, for example — a tell-tale sign of aging equipment as warranty coverage expires.

Many fleets are running their vehicles even longer than the typical 4-5 year trade-in cycles. Along with rising labor and parts costs, longer lifecycles have contributed to a 10% increase in maintenance costs year-over-year, according to a survey of 5,000 service shops published by the American Trucking Association (ATA).

The same survey reported that 82% of repair shops faced service disruptions, and 14% of shops overall reported severe disruptions to their operations.

Inventory challenges have forced fleet managers to consider tradeoffs in lifecycle management: between deliveries today and vehicle reliability tomorrow, operational and capital expenses.

These maintenance management decisions weigh on overall fleet performance — from the driver experience with vehicle reliability to customer satisfaction and service levels.

The extended time in the shop underscores a significant area where predictive maintenance is making an impact. A predictive maintenance program enables fleets to know precisely when vehicles and components need attention — before a road call, tow, or derate.

Rather than fault codes, which are reactive and imprecise, and work order data, which gives an idea about what has already happened, predictive analytics give fleets a future-looking profile of vehicle performance.

That capability is especially important for fleets running older assets that — because of their age — are more prone to fail, place drivers and other motorists at risk, and jeopardize deliveries.

Instead of having your vehicle sidelined in the shop, maintenance teams gain a precise warning on which vehicles are likely to fail and why. They also have the power to keep tabs on underperformance, which can go undetected and put on-highway performance at risk.

They can pull vehicles from the road to make the proactive repair only when it is imperative to do so. It might come down to the severity of one failure, the series of impending issues that a vehicle has, or the criticality of a vehicle on a given route. Advanced visibility — enabled by predictive analytics — gives maintenance teams the ability to make the next best decision.

Predictive maintenance also informs fleet planning. Proactive orders on spare parts can cut into the long wait times in the aftermarket right now.

If failures of one kind persist, like a coolant issue, fleets with predictive analytics have the data-backed support to evaluate how different shops are performing and can uncover opportunities for technician training. Or even new vehicles when the next procurement cycle rolls around — fleets can dig into the survivability of individual components prone to fail.

Even as the market makes it challenging to buy new, fleets have support to bring reliability to aging heavy-duty trucks. Predictive maintenance offers the assurance of delivery and gives maintenance teams a heads-up on impending issues, with the most trip-ready assets at their disposal.

Ready to put your data to work?