Guideline 1:
Robotic Picking 101
Why use robots for picking orders?
E-commerce is rapidly expanding, increasing the pressure on businesses to meet customer expectations for fast delivery, accurate order fulfillment, and competitive pricing. This means businesses will eventually need to increase efficiency and maybe extend their order fulfillment outside normal working hours at the lowest operational costs to fulfill these end-customer expectations
The biggest challenge to maintaining consistently high-performing order fulfillment while keeping operational costs reasonable is the reliance on manual labor. Businesses eventually need to embrace automation.
There’s no doubt that humans are more adaptable and flexible than automation, but when controlling operational costs is crucial, relying on manual labor only isn’t sustainable. Additionally, the warehouse industry is facing a growing labor shortage, making it increasingly difficult to achieve order fulfillment through manual labor alone
And this is where the robots come in. They do not have the same adaptability and flexibility as humans, but they can pick orders outside normal working hours at high performance and low picking cost.
How do they work?
Piece picking robots are doing more or less the same thing as a human picker. The robot receives a task to fulfill, conducts the task and informs the task giver about the result. It could be “Done, next task please” or the likes of “I could not find the item I was supposed to pick”, “The bin I was delivering to was full” or “Sorry, I dropped the item. Shall I pick another one?”.
In technical terms, the piece picking robot does the following after receiving a task:
- Moves over to the location of where the item(s) to be picked is(are) (source container).
- Takes an image and uses computer vision to find the item to be picked.
- The item is picked up using a gripper, with suction cup grippers being the most preferred since they provide a fast and secure hold on suction-cup-friendly items.
- Finally, the robot moves the item to the delivery location and delivers the item in the designated bin (destination container). Typically picking robots can deliver using three methods;
- dropping the item (can be a 20 cm drop),
- placing the item (lowering the item before releasing them, or
- packing the item (like 3D Tetris)
Piece-picking robots can operate continuously without the need for breaks, serving as super-efficient and tireless helpers in your production facilities
Any risks involved in using robots?
No automation systems are without risks. It can be performance risks or technical risks.
Within the performance risk category, you find things like:
- Having a cap on throughput
- Items not being pickable
- The item the robot is picking is damaged/not as expected
And within the technical risks, you find things like:
- Mechanical failure
- Suction cup can be damaged or worn-out resulting in dropped items
- The software/control system can stop working
Unexpected stops do happen. The effect ofunexpected stops depends on the severity of the failure and how well the system is prepared for these stops.
We at Pickr.AI have addressed this with some neat features in our solutions which should reduce the effect of unexpected stops to the minimum. Market trends and needs.
Robots have been in use for decades, primarily in manufacturing, with automotive companies leading the way. This made sense until the advent of ´proper AI´ around a decade ago as manufacturing tasks are highly uniform and repetitive, making them well-suited for traditional robots.
With the advent of ´proper AI´, robots can now handle more unstructured tasks, such as piece picking, which were previously too slow and costly to implement in warehouses.
Recent advancements in AI and similar technologies are driving a trend in the warehouse industry towards adopting robotics and AI. Companies are seeking solutions to achieve more intelligent and responsive order fulfillment systems.
