Drones in Distribution: Counting Inventory

Drones in Distribution: Counting Inventory | LoadProof

We can all imagine drones moving boxes in the distribution center. However, there are a couple of reasons that make it difficult to move boxes today. That being said, another scenario offers even a more compelling advantage: inventory control. Of course, a few technological hurdles need to be overcome for this idea to be really feasible. Today, the payload for a drone is limited. To increase the payload, the drones need more motors and propellers, which increases the size of the drone significantly.

This size increase also its battery efficiency. After installing this many propellers and battery, the flight time on the drone might only be 15 to 20 minutes with a payload of maximum 10 to 15 pounds. In order to keep the drones operating, there have to be recharging stations where the drones have to be sent every 15 minutes. Again fast charging technology will help here, but that technology is not fully ready yet.

So this significantly reduces the feasibility of drone deployment, except in distribution centers that move small items. Electronic components might be one example. Also small electronics products, including smart watches or fitness trackers. Of course, all these in E-commerce customer order fulfillment scenarios.

The second area where drones offer a lot more opportunity and better bang for the buck is for inventory counting. There are two approaches to leveraging drones for inventory count.

The first approach is using radio-frequency identification (RFID tags). In this scenario, each unit of every SKU would need an RFID tags in it and then also the locations that hold them (any type of location, such as pallet reserve, case reserve, case pick, active, etc.). The drone would take a flight path that covers all the locations, which would mean that the drone would have to fly at different altitudes to cover all levels of racking and then read the tags that are in that vicinity including the parent RFID tags associated with the locations.

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