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How Can AI Truck-Loading Robots Seamlessly Integrate With Existing Processes?

Many logistics businesses use robots to pick items or move goods throughout the warehouse. Beyond that, though, robotics hasn’t seen much adoption in this sector — at least, until now. Artificial intelligence (AI)-powered truck-loading robots are starting to appear.

FedEx and Dexterity AI

Logistics robots took another leap forward with the news that FedEx is collaborating with robotics company Dexterity AI. In a September 26 press release, the businesses unveiled DextR — a two-arm robot that uses AI to determine the best way to load boxes onto a truck.

Historically, robots perform best in highly predictable environments. Truck loading doesn’t fall into that category because every shipment includes boxes and packages of varying shapes and sizes. DextR works around that obstacle by analyzing each shipment and truck space in real time to adapt to different jobs.

According to Dexterity AI, DextR can assess billions of possibilities in 500 milliseconds. That way, it can determine how to pack boxes to use the space as efficiently as possible while ensuring the shipment is secure. Cameras and LiDAR sensors help it make these decisions, as touch sensors let it grab and move boxes without damaging or letting them slip.

Benefits of Truck-Loading Robots

It will take time for DextR’s real-world impact to become apparent. Even before this announcement, though, truck-loading robots as a concept have presented several promising benefits.

Optimized Truck Loads

Making the most of a truck’s available space while protecting packages is tricky, even for seasoned employees. However, detail-oriented, complex decision-making is precisely the type of work AI excels at. It can simulate and analyze more possibilities in less time than the human brain, making it an ideal tool to find the best way to load a truck.

That better decision-making could let truck-loading robots save logistics companies considerable cash. Studies show using more of trucks’ available capacity can reduce costs by 20 cents per mile, adding up to roughly $200 per day on average. Fleets making fewer trips would also generate fewer greenhouse gas emissions, helping meet rising environmental regulations.

Higher Efficiency

Robots like the Dexterity AI solution could also help pack trucks faster. Determining the best packing method in half a second saves time on the planning end, but robots also move faster than humans. Warehouses could then pack trucks as quickly as possible to minimize idle times and improve shipping speeds despite moving away from the less-than-truckload model.

It’s important to note that automation doesn’t have to replace humans to achieve these benefits. You can also boost efficiency by using robots to complement human workers. Humans and robots can pack a truck together faster than they can independently. Alternatively, robots could manage packing to let employees accomplish other tasks at the same time.

Overcoming Labor Challenges

Similarly, automated truck loading would help logistics companies address the industry’s persistent labor challenges. More than half of 3PLs and 78% of shippers say they’ve experienced negative impacts from labor shortages. Automation could fill the gaps these organizations struggle to fill with new hires.

Robots could also address issues with the existing workforce. When automation handles the most repetitive physical tasks, human employees are less prone to injuries from musculoskeletal disorders. Having more time to focus on other tasks can also boost engagement and reduce stress to prevent turnover.

How to Implement Truck-Loading Robots

These benefits are impressive, but many companies recognize tech adoption is inherently disruptive. If they want to capitalize on truck-loading robots fully, they must approach them carefully.

Review Workflows for Ideal Use Cases

Implementing robots effectively starts with recognizing where they’re most valuable. Picking has become a popular target for automation because human pickers spend 50% of their time traveling, which isn’t very productive. Truck loading is similar in that it involves a lot of excess motion, so it’s an ideal application for automation.

That said, if you have a workflow with lower efficiency that is just as or more easily automatable, you should automate that first. Even within truck loading, start by finding which trucks, routes, or regular shipments are the most prone to long or inaccurate loading. The slowest or most error-prone are the best workflows to automate.

Start Small and Set Goals

It’s also important to remember automation is expensive. Because truck-loading robots require AI to operate effectively, they’ll likely incur even higher costs. The way to manage these expenses is to automate a single function in a single workflow first, then carefully monitor the results.

Measure your performance before automating and keep monitoring the same KPIs afterward. If anything exceeds or falls below expectations, ask why. This analysis will inform more cost-efficient, less disruptive automation expansion in the future.

Keep Robots in Optimal Condition

Getting a full return on investment also requires robots to stay in optimal condition for as long as possible. Like any other machine, robots need regular maintenance. Review manufacturer guidelines to learn what to fix, when to do it and how you can do so to prevent breakdowns.

Additional equipment can help optimize these maintenance practices. Internet of Things sensors can monitor equipment health to alert you when a robot needs repair. Vibration isolation systems can minimize vibrations in the robot arms, which interfere with precision measurements, enabling better results.

Communicate With Workers Throughout

Seamless integration is only possible if you prepare your workers for the shift. Before implementing the truck-loading robot, discuss the change with workers so they know what to expect. Encourage them to ask questions, and listen to their feedback to ensure human-robot collaboration doesn’t lead to feelings of job insecurity or devaluation.

Similarly, it’s important to stress that the machines are supposed to help existing employees, not replace them. Studies show people feel more positive about robots as equipment than they do about robots as coworkers, so present them as a tool, not an employee. The more comfortable your workers feel around the robots, the smoother the transition will be.

AI Truck-Loading Robots Could Be the Future of Logistics

If the FedEx/Dexterity AI collaboration works out, it could be a significant step forward for the logistics industry. As truck-loading robots become more common, they could unlock new efficiency, cost-effectiveness and labor-management standards.

You must know how to implement robots for them to be of use. When you understand the steps and where these projects could falter, you can avoid complications to ensure a smoother tech rollout.

Emily Newton
Emily Newton
Emily Newton is the Editor-in-Chief of Revolutionized, an online magazine celebrating advances in science and technology.

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