How AI-Driven Predictive Maintenance Helps Fleet Customers

According to the American Transportation Research Institute's most recent data, maintenance and repair accounted for the third-largest cost for operating a fleet in 2023, at 11% of the total, behind fuel and lease or purchase payments. In addition, this cost is rising year over year, now at $0.202 of the average marginal cost per mile, up 3.4% from 2022 to 2023. 

Historically, fleets have used preventive maintenance to keep their trucks in top operating condition but recently have begun moving toward a predictive maintenance model. 

Artificial Intelligence Can Analyze Fleet Data to Help Managers Make Maintenance Decisions

Effective predictive maintenance depends on securing data: the more data, the better. Data can come from maintenance records, sensors and driver vehicle inspection reports (DVIRs), and it needs to be gathered from all makes and models of trucks across a range of vehicle ages. 

However, data by itself isn’t valuable; fleets need to make decisions based on what the data tells them. That’s where analytics come in, when the data is scrutinized to look for patterns, trends and anomalies. 

One key point to remember is that the quality of the data matters. Bad data, like incomplete vehicle histories or readings from damaged sensors, will negatively impact the analysis. 

Until recently, data analysis had to be done by a person who studied the maintenance and repair records of past service events to get a sense of where the fleet had problems. The analysis was then leveraged to make future spec’ing decisions and tweak maintenance schedules.

The term "AI" is used a lot these days and can consist of several components: 

• Machine Learning: Algorithms that analyze data patterns
• Deep Learning: Neural networks that can detect complex patterns in large amounts of data
• Big Data Analytics: A large amount of data from various sources is processed for anomalies that indicate an upcoming failure

Fixing Maintenance Issues Before an On-Road Failure Can Introduce Cost Savings for Fleets

Today, in real time, AI can monitor things like engine performance, tire pressure, temperature and fluid levels — and analyze these metrics — along with the existing service history data to get a more complete picture of what’s happening in the fleet. 

AI can predict when vehicles need service so Fleet Managers can schedule a service appointment before the truck experiences an on-road breakdown, which is more costly. In fact, a roadside repair can cost four times as much as one done on a scheduled basis in the shop.

In addition, according to Transport Topics, “With AI, the fleet manager can automatically monitor the performance of each vehicle against benchmark standards on the expected life of a part on that vehicle — and automatically schedule routine maintenance when the life of that part is expected to expire.”

How much fleets can save in costs by using AI to analyze fleet data is unclear since each fleet operates differently, but there are a few examples of how predictive maintenance saved fleets money. Jim Rice, Uptake vice president, noted in a Fleet Owner article, “By getting advanced warnings of cylinder head failures, a food and beverage fleet of 50,000 turned $50,000 engine replacement catastrophes into manageable $3,000 repairs. This failure mode happened on 80 trucks, so in four months, the fleet saved $1 million.”

Fleet Complete and Pitstop have collaborated on a predictive maintenance platform that uses AI for its analytics, and noted “The collaboration has demonstrated predictive analytics of parts and components, like brakes, tires and engines, alerting to potential breakdowns before they happen. This capability is expected to increase vehicle uptime by up to 25%, with savings potential of up to $2,000 per vehicle per year,” according to Food Logistics. 

Research from Deloitte Analytics Institute, although not specifically focused on trucking, found that “On average, predictive maintenance increases productivity by 25%, reduces breakdowns by 70% and lowers maintenance costs by 25%.”

AI Can Give Dealers a Competitive Advantage

Predictive maintenance powered by AI can reduce downtime, improve safety, extend vehicle life, and improve compliance with CSA inspection rules, giving dealers a competitive advantage for their fleet customers. 

Today, AI is transforming truck maintenance practices and allowing fleets to optimize their maintenance schedules, lower repair costs, increase uptime and improve overall fleet operation. It’s possible that AI could also be used to monitor trailer health in the future. 

Learn more about how CDK AI integrations can deliver a competitive edge.