How Robotics, Machine Learning, and UAVs are Transforming the Material Handling Industry

Robotics in Material Handling: Revolutionizing the Warehouse

Long gone are the days when manual labor was the only way to handle warehouse materials. General Motors kicked off the industrial robot revolution in 1961, using the first robot on a production line at its Ternstedt plant in Trenton, NJ. Since then, industrial robots in the material handling industry have continued to evolve and be adopted at a rapid rate.

Examples of Robotics Applications

Automated picking and packing machines: A lot has changed since the 1960s. Robots can now be equipped with advanced “vision systems.” This technology allows robots to pick items from storage and place them into packing for shipment. The result is faster and more accurate order fulfillment that avoids human error.
Collaborative robots (cobots): Humans aren’t entirely out of the picture, though. “Cobots” (including picking and packing robots) are designed to work safely alongside people. They can easily handle repetitive or physically demanding (and potentially dangerous) tasks like lifting and moving heavy packages to reduce strain on your human workforce and improve productivity.
Robotic forklifts and autonomous mobile robots (AMRs): These robots are able to navigate warehouses, ports, and shipping yards autonomously to transport goods, streamlining inventory movement and storage. Unlike people, AMRs can work around the clock, once again amping up productivity, minimizing supply chain disruptions, ideally reducing human error and safety hazards, and potentially reducing labor costs.
Palletizing and Depalletizing: With robotic arms, products can seamlessly be stacked onto pallets and unloaded. These robots are designed to handle heavy loads with precision, resulting in more efficient packing.

Robotics have significantly transformed material handling by automating tasks like moving, sorting, and organizing goods within warehouses and manufacturing facilities. As this technology evolves, business operations are positively impacted with increased efficiency, reduced costs, improved accuracy, and enhanced safety, minimizing human exposure to repetitive and potentially hazardous tasks.

Machine Learning: Smarter Operations for Predictive and Adaptive Handling

At this point, Artificial Intelligence (AI) and Machine Learning (ML) have affected nearly every industry, and material handling is no exception. ML enables smarter, more adaptive systems to be applied and has played an increasingly important role in optimizing warehouse operations. As with any good plan, effectively implementing AI and ML into your business operations starts with collecting quality data and identifying specific goals to address your biggest challenges.

Applications of Machine Learning in Material Handling

Inventory optimization: Using historical data, seasonal trends, and market conditions, ML can help predict demand, reducing stockouts/backorders or overstocking.
Maintenance prediction: By monitoring equipment data, you can make proactive repairs before failure occurs to minimize downtime for material handling equipment.
Route optimization: ML algorithms can analyze traffic, weather, and common delivery constraints to choose the most ideal travel routes via freight or truck and optimize travel flow at shipping ports.

Companies utilizing machine learning make more data-informed decisions and capitalize on cost savings by avoiding inefficiencies and equipment failures. This technology also allows small to medium-sized businesses to compete with larger enterprises.

UAVs (Drones): Taking Supply Chain Logistics to New Heights

Unmanned Aerial Vehicles (UAVs), or drones, were originally developed for military purposes. Since their first application, drone usage has evolved significantly, running the spectrum from a hobbyist toy to more productive uses outside of the defense industry — including supply chain management.

Examples of Emerging UAV Applications

Inventory management: UAVs equipped with barcode scanners and RFID technology can easily (and quickly) fly through warehouses to scan inventory data in real-time, replacing time-intensive manual stock-taking.
Last-mile delivery: Several companies — most notably Amazon — use drones for faster and more direct shipment of goods, delivering packages directly to doorsteps within a specific mile radius.
Port and shipping yard management: UAVs can quickly provide a bird’s eye view of ports, shipping yards, and rail terminals to track shipping container movements and identify potential bottlenecks that could slow down shipping times.

UAVs continue to reshape the material handling and logistics landscape, bringing more speed and precision to operations and reducing costs. Innovative uses (like providing direct delivery) speed up delivery times and provide companies with another way to increase customer satisfaction.

How Is the Landscape of Material Handling Changing?

When advanced technology enters the arena, change is inevitable. At Ongweoweh, we’re committed to tracking the trends and changes taking place within the material handling industry to keep our customers informed. Undoubtedly, robotics, machine learning, and the use of UAVs will continue to shape business operations and disrupt traditional systems. The pallet market’s growth — which is projected to grow by 22.43 billion USD from 2024 to 2028 — can doubtless be attributed, in part, to the adoption of such technologies, which is making it even easier to utilize pallets more efficiently.

Technological Impacts on Traditional Systems

Pallets as we know them continue evolving to accommodate robotic handling systems, with standardized sizing and high durability becoming even more critical. In addition, machine learning-powered inventory systems require designs that support advanced tracking methods, like built-in RFID integration. Lightweight yet durable pallets that are sustainably made continue to increase in popularity. Going beyond pallet changes, we’re also seeing increased automation in ports and freight rail transit systems, resulting in faster unloading, sorting, and distribution of goods.

Employment Implications

As these technologies evolve, shifts in workforce demand from manual labor to more technical and operational roles are taking place, creating opportunities for upskilling and reskilling employees. The demand for skilled workers who can program, maintain, and operate robotic systems and ML tools is only projected to increase. Rather than viewing this as a challenge, companies will benefit from investing in upskilling initiatives for their employees to help bridge the gap between existing and new roles that will undoubtedly be born out of the continued implementation of advanced technology.

Supporting Your Business in the Age of Innovation

Robotics, machine learning, and UAVs are here to stay — but so are we. During the 45 years we’ve been in business at Ongweoweh, we’ve seen plenty of changes. Still, one thing hasn’t changed: Remaining dedicated to bringing our customers the best pallet and supply chain solutions to support their business.

Our pallet management and optimization programs align with the efficiency and innovation offered by robotics, machine learning, and UAVs. We also offer in-depth reporting and analytics to provide your business with reliable, transparent data that can be utilized with machine learning tools. Our mission is to simplify your pallet needs so you can focus on your core business strategy and goals while staying ahead of technological trends.