Ant trails on the terrace or bees’ nests in the garden—these are familiar sights to many of us who share our surroundings with our insect neighbors. What’s less apparent, however, is how much we could learn from insects in terms of optimizing work processes. They carry out some complex logistics operations. At KION there are several examples of how naturally occurring phenomena can be adapted to improve the way we work.
2023-01-25
“Ants have always fascinated me as they are extremely efficient creatures,” says Frank Heptner, Vice President Sales & Realisation Automation and Intralogistics at KION. When a trail of ants is interrupted, the insects immediately reorganize themselves and find a new route, and the process continues. “This is the exact approach that we have when working for our customers,” says Heptner: “Finding the shortest route, responding to the unexpected and being ready for action at all times.”
How does that work in an ant colony? According to sociobiologist Bert Hölldobler, one worker ant looks for food or building materials, depending on the priority at the time. It uses its natural scent, or pheromone, to mark out the route to the destination, which its “colleagues” then follow. If an ant finds a faster route, a new path will be set and marked out with a stronger pheromone. The ants following use the intensity of the scent to differentiate which route is currently the most efficient. If the new path is blocked, the ants will find their way back to the old route, which they can identify thanks to the weaker scent.
The remarkable thing is that all of this works without a higher authority. The ants organize themselves and each individual ant is aware of all the processes and changes. This principle is directly transferable to intralogistics. “In our world, we call this ‘goods to person’,” says Frank Heptner. This is where, for example, an employee goes to the shelf, finds the right product there, and then takes it to its destination. “That is still very common practice to this day,” says Heptner. To increase the efficiency of work processes, however, methods have been developed to provide an alternative to the employee retrieving the product, or to do away with this step altogether. After all, if the goods can be taken to the person rather than the person going to the goods, it saves time and makes the shipping process smoother.
The L-MATIC at ebm-Papst in Mulfingen, a company that manufactures ventilators and motors.
One example of this is the distributor for ebm-Papst in Mulfingen, who manufacture ventilators and motors. The distributor uses three L-MATICs—automated pallet stackers from KION subsidiary Linde Material Handling. The trucks independently retrieve the pallets from the conveyor belt and transport them to the respective drop-off point.
“This actually works in a very similar way to a trail of ants,” says Frank Heptner. The supervisor software controls the fleet of robots, calculates the route and issues orders to the L-MATIC trucks. The system also communicates with other automated systems, such as doors and conveyors. “This enables them to react to changes in real time,” continues Heptner: “It prevents collisions and means the optimum route is used at all times—just like in an ant colony!”
The omni-channel retailer Radial Europe is another company to have optimized the efficiency of its logistics center—this time with support from the automation specialists at KION subsidiary Dematic. The approach used here is another example of how intralogistics can learn from ant colonies: At 45 picking and loading areas around the warehouse, transport robots are assigned various tasks—“like individual ants within an ant colony,” says Heptner.
The company uses AMRs or autonomous mobile robots. These transport pallets from transfer points to the shelves and then on to the packing area. Other AMRs transport containers between the warehouses and order picking stations. Seamless cooperation between different systems is guaranteed thanks to the use of warehouse management software. This ensures smooth operation and makes sure the process runs efficiently. Frank Heptner calls this interaction the “ant algorithm” and says: “This principle is now used in many logistics warehouses worldwide.”
It’s All About Division of Labor.
Ants aren’t the only creatures whose social behaviors are reflected in intralogistics processes. Another example is bees. The sociobiologist Bert Hölldobler describes the way in which bees search for food: The insect flies off and checks flowers for their quality, but instead of digging right in, first they inform the other bees by performing a kind of dance. This lets the other bees know the coordinates of the flower, its quality and the route to fly there.
So, unlike with ants, it doesn’t involve a chain of workers all acting very quickly, but rather preparation that is closely related to division of labor. While there are hierarchies and different roles within an ant colony, with bees this behavior is much more pronounced. There are drones, workers, royal bees and the queen. The worker bees are divided further into several subgroups. For example, some collect nectar and some help with navigation, while others take care of ventilation, cleaning, keeping the others “fueled”, and much more.
“What intralogistics can learn from bees is that, in order for communication and management to run smoothly in any process, the utmost priority is a well considered division of labor,” says Frank Heptner. Just like with bees, division of labor is essential in intralogistics. To make the best possible use of communication channels and therefore to share information as efficiently as possible, we work with software systems in intralogistics. Like the gatherer bees, these systems share information about work tasks.
The order picking process with the OPX iGo neo resembles the work of gatherer bees, who fly back to the hive.
If an employee is then sent off to collect goods from the shelf, for example, we can think of the OPX iGo neo from STILL as being part of the worker bee. Bees use pockets on their legs to transport pollen—in a very similar way to our semi-automated order pickers. Just as the bees only let their pockets get so full that they can still return as quickly as possible to their nest, the operators of the OPX iGo neo also load up their equipment in a way that ensures the most effective flow of materials. The order picking process also resembles the work of gatherer bees, who fly back to the hive to deliver the pollen they have collected. Just as the bees follow one another, the OPX iGo neo automatically follows its operator wherever they go and adapts its route and speed until they arrive at their destination.
There are also work processes in the warehouse that resemble how bees work. Take ventilator bees, for example, who use their flight muscles to regulate the temperature of the beehive. In winter, they can use their wings to heat the hive to a temperature of up to 35 °C, while in summer they use them to cool the hive and stop the honeycomb from melting. In the warehouse, too, it’s important to put goods in the right place and keep them at the right temperature, to ensure optimal storage conditions.
The LoadRunner is a perfect example for swarm intelligence.
However, the most important principle that intralogistics can borrow from the animal kingdom is swarm intelligence and the super-organism. This describes the incredibly effective capacity that insects have to act and make decisions as a collective. The business consultant Ernst Kurzmann describes four mechanisms for how swarm intelligence observed in animals can be applied to the world of work. First, employees need to be independent in their decision-making. Second, a clear division of labor is needed—one that reflects the respective talents and competencies. The third requirement is decentralized knowledge and the fourth is aggregation, i.e. the amalgamation of all these individual skills which feed into the “wisdom of the crowd.”
Can this principle also be adapted for intralogistics processes? Absolutely, and we’re already working on that at KION, too. The “LoadRunner” is a prototype of a small transport truck that is designed not to work alone but as part of a swarm. It is currently being developed by KION in collaboration with the Fraunhofer Institute for Material Flow and Logistics (IML). The LoadRunner aims to take efficiency to a whole new level, with the little trucks reaching a speed of ten meters per second. Thanks to shared artificial intelligence, they are also capable of coordinating themselves independently.
Furthermore, the individual modules can be coupled together in order to transport heavier loads—a lot like ants, who can carry many times their own body weight. Were the engineers behind the LoadRunner directly inspired by nature? Frank Heptner grins: “I don’t know for sure and I don’t want to put words in their mouths,” he says: “But it’s a pretty logical assumption.” Regardless of where the inspiration ultimately came from, in terms of efficiency, the LoadRunner definitely gives ants a run for their money: When tested, the robot swarm was able to sort considerably more than 10,000 shipments per hour …
