Intralogistics (the movement of goods and materials within warehouses) is increasingly being undertaken by a fleet of next generation robots. How are they changing the landscape of the warehouse and what’s required to keep them moving?
What is intralogistics?
Intralogistics refers to the internal flow of materials, goods, and related information within a manufacturing or distribution facility. This includes the transportation, storage, and handling of materials and goods, as well as the management of associated information and data.
Intralogistics covers all processes from the moment raw materials enter a facility until the finished product is shipped out.
Why is intralogistics important?
The frictionless movement of goods and materials within a businesses has massive consequences for profit and loss. Delays and disruption caused by intralogistics failure can disrupt production lines, frustrate customers and lose companies money.
Over the years these processes have been subject to robotic automation in order to:
- Reduce the health and safety risk to humans within warehouses
- Increase the speed and accuracy of materials handling
- Ensure faster delivery of products to end users
- Support just-in-time supply chain management
The first era of robotic automation included conveyor belts, automated storage and retrieval systems (AS/RS), and other basic mechanized solutions. While these advancements improved efficiency, they still required substantial human oversight and intervention.
Intralogistics robotics is entering a new smart era
But advancements in sensor-led mechatronics, made smarter by IoT and AI have created a new era of cyber-physical logistics that are optimising warehouse performance in ways we’ve never seen before.
As Gartner points out:
“Ninety-five percent of supply chain organizations say they have invested, or plan to invest, in cyber-physical automation (CPA), and a significant percentage of these plan to use intralogistics smart robots (ISRs).” Gartner
Here are just a few of the smart robots and their manufacturers that are automating process, and gathering data to continually optimise intralogistics movements through machine learning.
Automated Guided Vehicles (AGVs):
Amazon Robotics uses AGVs to transport shelves of products to human pickers in their fulfilment centres. These robots follow predefined paths marked by barcodes on the floor to navigate the warehouse efficiently.
Autonomous Mobile Robots (AMRs):
ABB provides AMRs that autonomously navigate warehouses to transport goods, handle material movement, and assist in order fulfilment. Their robots use advanced sensors and machine learning algorithms to avoid obstacles and optimise their routes.
Robotic picking systems:
RightHand Robotics offers robotic picking systems that use machine vision and AI to identify and pick items from bins or shelves. These robots are used in warehouses for e-commerce giants to handle diverse and complex picking tasks.
Sorting robots:
GreyOrange's robots are used in sorting centres to automate the sorting of packages based on size, destination, and other criteria. These robots streamline the sorting process in large-scale logistics operations.
Palletizing Robots:
FANUC’s robotic palletizers are used by companies like Coca-Cola to automate the stacking of beverage cases onto pallets. These robots handle repetitive and heavy lifting tasks, improving efficiency and reducing manual labour.
Unloading robots:
Boston Dynamics’s Stretch robot is designed for moving boxes in warehouses. Stretch combines mobility, reach, and vision to unload goods from trucks and place them on conveyors or storage racks.
Inventory robots:
Bossa Nova Robotics’ inventory robots are used by Walmart to scan shelves and monitor inventory levels. These robots help ensure shelves are stocked and items are correctly placed, improving inventory accuracy and availability.
Shuttle systems:
Swisslog’s CycloneCarrier shuttle system is used by IKEA for automated storage and retrieval. This system optimizes space utilisation and ensures fast and accurate handling of items within the warehouse.
Drone-based systems:
Warehouse Automation Expert RAWview uses camera systems for inventory management in large warehouses and yards. These drones can conduct inventory counts, empty bin audits, put-away audits, and space utilisation analysis to minimise H&S concerns in the warehouse while optimising intralogistics performance.
Warehouses reimagined
Meanwhile, Ocado’s intralogistics robotic solution re-imagines traditional warehouses altogether. The inefficiency of human movement is here replaced by the continual, orchestrated movement of bots across giant chess-board like grids that span warehouses the size of football fields.
Picking orders ready for distribution, the bots are controlled by a central ‘hive mind’ continually processing order information from the central e-commerce hub.
The picking and packing bots collaborate and share sensor-captured data to jointly plot their movements across the grid in the most efficient way possible.
Humanoid Robots
But what about robots that look and operate like humans yet possess the strength of machines to carry out heavy-duty tasks?
In the future, warehouses could be automated by the ultimate, intelligent, indefatigable, dextrous humanoids. Gartner are optimistic walking and ‘thinking’ robots are the next big thing.
“We project humanoid robots will evolve during the next several years to address the limitations of previous generations of automation”
Source: SCMR
But what level of sensing and data capture will be required to automate those actions?
A final thought?
The world of intralogistics robotics and automation is developing fast. Companies are working with all kinds of data and integration specialists to ensure they are moving the right goods to the right places in the most efficient ways.
As these solutions are being imagined, the need for ever more sophisticated sensors and actuators to extract data from robots on the ground to drive decision making becomes ever more acute. The MOEMS (Microoptoelectromechanical systems) of the future that can help control the full range of robots in the warehouse must be highly sensitive, multi-functional and robust.
Building the next generation of connected, automated warehouses will require collaboration at the macro and the micro level.
