Fetch Robotics announces collaboration with Zebra Technologies for the Optimal Optimization Solution

Together, we can transform and fully optimize collaborative picking across multiple orders, among workers and robots, and for piece, case and pallet workflows.

Today, we announced an integrated fulfillment solution with Zebra Technologies that combines the breadth of Fetch AMRs and picking optimization of Zebra FulfillmentEdgeTM. This new joint solution not only optimizes collaborative picking across multiple orders while dynamically orchestrating workers and robots, but does so for piece picking, case picking, and pallet building.  

In addition to the solution being unique in that it optimizes picking operations of merchandise ranging in size from tiny transistors to 3000 pound pallets and everything in between, customers can also interleave others tasks such as replenishment into the flow to better leverage workers’ time in the aisles. In addition, FulfillmentEdge, through Zebra handhelds, can direct Fetch AMRs to other non-picking operations such as removal of recycling, reverse logistics and restocking of packing stations in order to maximize robot utilization. 

While we are most excited that Fetch AMRs and FulfillmentEdge together enable faster, more accurate fulfillment and improved workflows that allow workers to spend more time in the aisle instead of manually moving material throughout a facility, we are also happy that Fetch made a different decision than other AMR providers about building an optimization layer. 

Bob Trebilcock wrote an excellent article in Modern Materials Handling on Warehouse Execution Systems (WES) 2.0.  Regardless of what you call this functionality, a WES, an Optimization Layer, or some other name, it will bring a new level of optimization and productivity to the conventional warehouse.  Bob highlights FulfillmentEdge in this article, but also mentions other companies that are providing similar functionality. Bob does not mention the WMS vendors or integrators that also offer or soon will offer this functionality.  

At Fetch, we decided to focus our efforts on areas outside optimization so that we can focus on:

  • The broadest portfolio of AMRs and AMR accessories in the market
  • A solution that works across distribution, fulfillment, and manufacturing
  • An on-demand automation platform where you can deploy AMRs in hours, iterate workflows until perfect, and then integrate into a WMS or optimization layer when desired
  • Implementing a cloud-based architecture that can leverage cloud-native machine learning tools on massive amounts of sensor data collected from AMRs to identify areas of the facility where efficiencies can be dramatically improved or safety concerns can be autonomously identified before employees are injured.  
Image result for fulfillmentedge zebra

While we realize that this is a dramatically different strategy than other fulfillment-focused AMR vendors, we believe that customers will want more than just optimized piece picking from their AMR provider and will also want to leverage a trusted and highly stable partner like Zebra Technologies for their optimization layer.  

And it doesn’t stop there.  Just imagine what’s possible when you combine the broad portfolio of Fetch AMRs, Fetch’s cloud-based robotics platform, and “insights” about a facility derived from AMR sensor data along with Zebra’s warehouse domain expertise, inventory data within FulfillmentEdge, and “insights” about the same facility derived from infrastructure-based sensor data.  

E-commerce is causing a profound change in supply chain operations as companies increasingly ship to consumers and stores from the same facility. Increasing order volume, labor shortages, high turnover, long ramp up times, and physically taxing material movement related to picking are forcing companies to accomplish more with fewer resources. This integration of Fetch AMRs and Zebra FulfillmentEdge will allow companies to transform their picking operations to fulfill more orders and the widest variety of orders with fewer and less experienced workers.

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