How AI Improves Fleet Longevity

Artificial intelligence – or AI – is a hot topic across most industries today, with extensive debates taking place about the benefits and risks of how “machine-based intelligence” may be influencing our society. While experts propose that self-driving autonomous commercial rigs are still decades away (at least), smaller AI-powered implementations are already working their way into the day-to-day tasks of the trucking industry, promising improvements in fraud detection, route optimization, and more.

One of the most practical and beneficial implementations of AI in the trucking industry comes in the form of fleet health maintenance, helping fleet managers move from reactive maintenance to preventive maintenance, and, ideally, on to a predictive maintenance mindset. This capability is particularly attractive in today’s current environment when parts are hard to obtain, new trucks are backlogged, and EV regulations are being rolled out industry-wide. 

Good, Better, Best: The Three Tiers of Fleet Maintenance

Vehicle maintenance is a key consideration and cost for commercial fleet managers, and the more ahead of the game they can stay, the more they drive down the cost of their equipment over the full life of ownership. There are three ways to approach fleet maintenance: first, bring in your vehicle when something breaks or you receive a warning lamp on your instrument panel. Everything grinds to a halt as you remove the truck from operations, impacting your timelines, shifts, and bottom line.

The second approach is more proactive; you utilize OEM recommendations and regular check-ups for your vehicles before they even “need” them. This allows you to schedule your service team and routes more efficiently, and reduces disruption to your operations. This approach is an excellent step in the right direction, although you’re still heavily dependent on manufacturers’ recommendations that don’t take into account your specific routes, loads, and conditions.

The third and most ideal approach is predictive maintenance that pushes your problem detection capabilities even further up the timeline. In this scenario, you’re utilizing real world data from your own vehicles to catch any small sign that a part might be deteriorating, that a system needs maintenance, or that trouble is on the horizon. Combining this data with regularly scheduled maintenance plans greatly reduces the risk of part failure and damage to your vehicles, driving down the cost of each vehicle over the lifetime of ownership. 

How AI Promotes Preventative Maintenance

Preventative maintenance sounds like a very smart and attractive approach to extending the longevity of your fleet, but one problem quickly becomes apparent: how to manage the large amount of data flowing in from each vehicle. Even with a relatively small set of data points per vehicle, the amount of number crunching and monitoring for a full fleet could soon threaten to overwhelm. This is where machine intelligence – or AI – comes into play.

Emerging AI software tools can now collect and process large amounts of vehicle data from an entire fleet – and even add additional “virtual sensors” based on other factors and thresholds – to ascertain the most accurate view of health for each vehicle in your fleet. These models can leverage vehicle and fleet data to generate new and unique data points such as vehicle stress, effective mileage, and overall vehicle health. The tools can then automatically create prescriptive maintenance plans based on your specific goals and resources. 

By integrating these AI tools into fleet management software, managers super-charge their vehicle maintenance, reducing downtime while improving sustainability and safety. Trucks operating in top condition not only last longer, but reduce the risk of dangerous malfunctions during routes that could injure drivers or bystanders.

Nemodata and Platform Science

To bring the benefits of AI health monitoring to more fleets across the nation, Platform Science recently partnered with Nemodata, a leading innovator in AI and data analytics, to offer an innovative add-on app to its fleet management software tools. The Nemodata app acts as an AI-based decision-making layer that leverages telematics data and additional fleet data sources to provide specific maintenance recommendations for each asset in the fleet.

Using proprietary core technology built by a team of experts in physics, mechanical engineering, and AI, the Nemodata app makes recommendations based on the health score and usage of each specific vehicle. By following Nemodata’s smart schedule, fleets can increase vehicle uptime, drive more miles between breakdowns, extend the vehicle lifecycle, and enable smooth integration of electric vehicles into the fleet.

This next generation of sustainable fleet operations – driven by data and artificial intelligence – promises great efficiencies and future-proofing for fleets. By embracing AI in its most useful form, fleets are making smart decisions to ensure safety and success of their operations for years to come.

Learn more about the Nemodata app for the Platform Science ecosystem.