When semiconductor manufacturers shifted production to consumer electronics during the pandemic, fleet management notched another supply chain disruption among its daily struggles: vehicle availability.

Procurement, like deliveries, used to come in semi-regular waves, as did the issues that threw fleet management off track. Among the challenges, fleets could count the recruitment of drivers and technicians, fluxating diesel prices, rising maintenance costs, and in some cases, expensive settlements for so-called “nuclear verdicts.”

This time around, the capital expenses for fleet management have remained high, but due to factors mostly outside the control of fleets.

The state of fleet maintenance today looks a lot different than a year ago. Fleets have had to run vehicles past conventional lifecycles due to the supply chain postponing shipments of spare parts, or the microchip shortage delaying orders for new vehicles. Trucks are on the road for the fifth and sixth calendar years, a year or two past their expected lifetime. In terms of repairs, what was once a day-long fix now drags on for a few days, while shops wait for parts or tend to an influx of other vehicles.

I visited a fleet a couple of weeks ago that’s now seeing its trucks left in repairs for two or three weeks in many instances. That’s bad for business. With few new vehicles coming off the line, trucking companies and private carriers can’t afford the expense of unplanned downtime.

In a survey of repair shops done by the American Trucking Associations, 82% reported facing service disruptions, and 14% counted the disruptions as severe. Without reliable service, fleets can't deliver.

It’s not all doom-and-gloom, though. For one, fleets are better equipped today than ever before to build resilience into their operations and maximize the lifetime value of their existing assets.

Carriers just need a more strategic way to prioritize repairing high-risk issues that can lead to downtime. Fleets might consider solutions that focus on fleet-wide reliability, such as predictive maintenance analytics, which gives fleet management a dynamic view into operations.

An approach to maintenance activity that focuses on the lifetime return on assets bolstered by predictive maintenance analytics shows maintenance managers how to:

• Catch catastrophic failures before they cause derates and roadside breakdowns;
• Perform proactive repairs that eliminate more expensive repairs later;
• Plan around scheduled trips, bringing in at-risk vehicles between assignments;
• Bundle repairs for vehicles with multiple critical issues, and
• Anticipate shortages of parts, in order to source and acquire replacements in advance.

Predictive Maintenance Analytics in Action

While fleets must run vehicles longer than originally anticipated, they can recoup their investment by avoiding untimely or costly repairs and replacements. Beyond preventive maintenance strategies, predictive maintenance reduces unplanned repairs and treats small things before they become big things –– and before a diagnostic fault code fires.

In most repair shops that get hundreds of fault codes per day, fleet managers and technicians lack the time or manpower to sift through the data. Instead, many fleets are reactive or follow through on preventive maintenance intervals –– focusing on the impending and most severe issues for the fleet.

By contrast, predictive maintenance analytics take the reliability of the fleet into account. Predictive analytics enables maintenance teams to be proactive in their service calls and address impending failures. Greater lead time allows maintenance teams to pull vehicles into the shop and cut maintenance costs.

Getting Started With Predictive Maintenance

Many fleets have already made significant investments in technology that enables them to quickly integrate predictive maintenance analytics in shop operations. Electronic logging devices (ELDs) and smart sensors provide substantial amounts of telematics data. Work orders in a computerized maintenance management system (CMMS) or enterprise asset management (EAM) software also provide data for predictive analytics, as do fluid samples and contextual information like weather or terrain.

What fleets need is a method to synthesize the information at a fleet manager’s fingertips, extract meaningful points, and surface valuable and digestible pieces of information. 

With predictive analytics, fleet management sees less data and gets more direction about which vehicles to pull from service and why. When those insights, or outputs from predictive analytics, are presented in a fleet’s maintenance management system, technicians can carry out the work while fleets can keep tabs on future issues.

With vehicle inventory disrupted by shocks to the supply chain, predictive analytics focus maintenance and operations teams on fleet-wide reliability.

Limited vehicle availability has caused carriers to rethink their approach to maintenance. Reliability is critical when new vehicles and spare parts are hard to come by. However, just an 8% average improvement in uptime from predictive maintenance would meet the same 12 billion tons of freight demand in the U.S. with 288,000 fewer trucks. 

Maintenance holds ample opportunity for fleets to generate value from their existing technology and vehicle investments.

Jim Rice is vice president of transportation with Uptake, a provider of predictive maintenance software.