I know I touched a sensitive topic, but truth be told mobile robots are transportation robots and not the picking robots. Pick is actually done by humans. Warehouse Picking Arms exists to help with this actual picking.
Warehouse picking arms, to some extent, remain a relatively under-explored area where user education is not easily accessible. So let’s dive into how do they really work, and what affects their performance and get your 101 class on it.
1. Understanding Picking Arm Tasks
Picking arms are robotic devices designed to automate the actual picking process (transferring a single unit or a carton from a storage location to a shippable medium like a box or pallet). The speed and efficiency of these arms can vary significantly based on the complexity of the tasks they perform.
Before we delve into the specifics of picking arms, let’s understand the system at a high level. In a typical warehouse setting, a tote is presented to the robotic arm. This tote is referred to as the inbound tote. On the other side of the picking arms, you have the outbound tote or the final box.
- Homogeneous Totes: These totes contain the same SKUs, so scanning the tote number will suffice for the robotic arm to understand what is being presented.
- Heterogeneous Totes: These totes contain multiple SKUs, so the robotic arm will need to identify each SKU it picks during the process.
Now that we understand the system at a high level, let’s delve into common tasks and how they impact picking arm performance:
- Pick & Drop: The simplest task where the arm picks an item and drops it in a designated area/tote/box. This task typically involves homogeneous totes.
- Pick & Place: Involves picking an item and placing it in a specific location, requiring more precision. This task also typically involves homogeneous totes.
- Pick, Scan & Drop: Adds a scanning step for identification before dropping the item. This task typically involves heterogeneous totes.
- Pick, Scan & Place: The most complex task, combining picking, scanning for verification, and precise placement. This task typically involves heterogeneous totes.
- Yaw Movement: Involves rotational movement to orient the item correctly during placement, adding complexity and time to the process.
2. Task Complexity and Speed
How does task complexity influence the speed of picking arms? Here’s a detailed look:
- Pick & Drop: This task is the fastest due to its simplicity, with picking arms capable of handling 600 to 750 units per hour (uph). In high-volume e-commerce fulfillment centers, such as those operated by Amazon, picking arms quickly pick items from totes and drop them into bins for packaging. The straightforward nature of this task allows for rapid item handling, significantly speeding up the order fulfillment process.
- Pick & Place: This task requires more precision, reducing the speed to around 500 to 600 uph. In distribution centers handling fragile goods, picking arms carefully place items into designated totes or boxes. While this adds a slight delay compared to Pick & Drop, it ensures safe and precise handling of delicate items.
- Pick, Scan & Drop: Adding a scanning step for identification or inventory tracking introduces a delay, resulting in a speed of approximately 400 to 500 uph. For instance, in pharmaceutical warehouses, picking arms scan each item to verify its identity and track inventory levels before dropping it into the correct bin. This task enhances accuracy and compliance but takes slightly longer than simpler tasks.
- Pick, Scan & Place: The most complex task, involving picking, scanning, and precise placement, reduces the speed further to around 300 to 400 uph. In electronics warehouses, picking arms handle high-value items that require verification and careful placement in anti-static packaging. The additional steps ensure accuracy and protection of sensitive items, although it results in the slowest performance among the tasks.
- Yaw Movement: Incorporating yaw movement to orient items correctly adds another layer of complexity. In grocery warehouses, for example, picking arms performing Pick, Scan, Yaw & Place tasks handle around 200 to 300 uph. These arms pick items from totes, scan them for verification, rotate them to the correct orientation, and place them into grocery bags. This ensures items are oriented correctly for packaging, reducing the risk of damage during transport but introducing further delays compared to simpler tasks.
Note: UPH numbers are based on typical understanding of operations. They are not actual numbers for your operations. Your vendor will be able to provide more accurate numbers for your specific operations.
3. Important Considerations
While understanding the speed and capabilities of picking arms is crucial, it’s essential to consider the overall system throughput rather than just the units per hour (uph) of individual picking arms. Real-world experience shows that buying picking arms based solely on their uph can lead to suboptimal results. Instead, evaluate the entire system’s performance, including factors such as:
- Integration with Warehouse Management Systems (WMS)
- Coordination with other automation systems (e.g., conveyors, sorters)
- Flexibility to handle various item types and sizes
- Ease of maintenance and support
- Scalability to accommodate future growth
Another critical aspect to consider is the cycle time of inbound and outbound totes, as well as their characteristics.
By focusing on the system throughput, cycle time, and the nature of inbound totes, warehouse operators can ensure a smoother and more efficient operation that maximizes the benefits of picking arms.
And now, go design that Robot Forward Warehouse!
Get in Touch
Do you have questions or experiences to share around Warehouse Picking Arms? I’d love to hear from you. Feel free to reach out to me at parth@whserobotics.com.
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