Predictive analytics for delivery vehicles

For commercial fleets, vehicle efficiency and uptime are always critical, but this has been especially true over the past two years.

During the pandemic, demands on the supply chain have increased aggressively with the growing need for transportation and delivery of goods. At the same time, due to other supply chain issues, there has been a shortage of new vehicles.

Together, these trends have forced fleets to keep their existing vehicles on the road longer. As vehicles age and rack up more miles, it becomes more critical for fleet managers to keep track of what’s going on.

“If you sit in the seat of a fleet manager, he comes in every day and he has, say, 100 drivers who get on trucks and they have all these goods that are packed in the back of the trucks that they need to get to different points throughout the day,” Pitstop Founder and CEO Shiva Bhardwaj told PYMNTS “If all of a sudden two of the trucks break down, it disrupts everyone. plan your daily workflow and it becomes a very sore point.”

Embrace digital solutions

Managing the maintenance of these vehicles to prevent breakdowns and analyzing their total cost of ownership to see when they need to be replaced has largely been done manually.

“There’s a large percentage – probably 70% – that’s pen and paper in this industry,” Bhardwaj said. “Right now people are doing this stuff very manually and rarely. So it’s more of a rule of thumb based on experience.

Increasingly, however, fleets are adopting platforms that provide digital tools and information. Pitstop offers a cloud-based analytics platform that uses connected vehicle data along with artificial intelligence (AI) to help fleet managers predict and prevent vehicle breakdowns.

With the predictive analytics provided by the platform, fleet managers can plan vehicle downtime for necessary maintenance and avoid unexpected breakdowns.

Send notifications to fleet managers

Vehicles today have an average of about 100 modules that receive input from sensors and control things like motors and switches, Bhardwaj said.

When this data is delivered to a platform like Pitstop, it can be used for predictive analysis. The data points can be fed into prediction models that tell the user the status of vehicle subsystems and the risk of failure of those subsystems.

This information is transmitted to the fleet manager via alerts classified as critical, major or minor depending on the vehicles requiring maintenance or at risk of downtime.

The platform is powered by the data stream from thousands of vehicles. So, for example, it can see the number of times a vehicle brakes while carrying the weight of a load, and then estimate the amount of energy dissipated by the brakes. He can then compare this to other similar vehicles and their rate of brake wear.

“It dictates the alert you want to send to the user,” Bhardwaj said. “He might say, ‘Hey, the brake wear on this vehicle is very high. We estimate it will need to be replaced in a month or two. You should have an inspector double-check it.

Although original equipment manufacturers (OEMs) of vehicles provide maintenance schedules based on time and mileage, vehicle needs may vary depending on how they are used. For example, a vehicle that is only used on city streets will brake much more than a vehicle that is driven on a highway most of the time. And a vehicle that carries heavy equipment will be used more than another.

“Everyone uses these assets in such different ways. As a result, they are going to wear differently,” Bhardwaj said.

Determining the total cost of ownership

This data can also be used to analyze a vehicle’s fuel costs and maintenance costs to see if they are performing as they should. Thanks to the information provided by the AI, the fleet manager can consult the total cost of ownership of the vehicles.

Because the platform knows the status of every system in a vehicle, it can provide information that helps the fleet manager determine which vehicles to take off the road for maintenance and which vehicles to take out of their fleet in because of their escalating costs.

“So every week you say, ‘Here are three vehicles we need to take care of,'” Bhardwaj said. “The other vehicles are constantly monitoring and analyzing, and then when there’s a problem, they highlight it so you can take action. This allows you to focus on the few assets that are actually at risk rather than not knowing what is going to happen. »



About: Results from PYMNTS’ new study, “The Super App Shift: How Consumers Want To Save, Shop And Spend In The Connected Economy,” a collaboration with PayPal, analyzed responses from 9,904 consumers in Australia, Germany, UK and USA. and showed strong demand for one super multi-functional app rather than using dozens of individual apps.

Lance B. Holton