Warehouse Tote Induction Using Anchor-Based Robot Order Assignment
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Solution Overview
Problem
In warehouse order fulfillment operations, the selection of totes for robots is often inefficient, leading to errors and reduced productivity due to the potential for selecting totes with the wrong number of compartments or size, and idle robots waiting for service in less active areas of the warehouse.
Innovation Solution
A method and system that utilize a warehouse management system to assign orders to robots by selecting an anchor location based on robot, operator, and active location proximity, and recommending a tote type based on the order set characteristics, optimizing tote selection and reducing idle time by grouping orders and robots according to activity levels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a human operator manually selects totes for robots during induction, then the process is simple to operate, but errors occur in selecting totes with wrong compartment numbers or sizes
Solution Approach 1:
The system performs self-service by automatically selecting appropriate totes based on order set characteristics without requiring human operator intervention. The WMS compares order dimensions, weights, and compartment requirements against available tote specifications to autonomously make selections, eliminating manual errors while maintaining operational simplicity.
Solution Approach 2:
The manual mechanical selection process is replaced with an automated computational system. The WMS uses software algorithms to evaluate order characteristics and match them with suitable tote types, substituting human cognitive and physical actions with automated information processing and decision-making.
2Manufacturing precision
If totes are selected without optimization for order set characteristics, then the induction process is fast, but the selected totes may not fit the items properly
Solution Approach 1:
The system performs preliminary actions by pre-evaluating order set characteristics (dimensions, weights, item counts) and pre-matching them with appropriate tote specifications before the actual induction process. This advance preparation ensures proper fit precision while minimizing the time required during the actual induction, as the matching logic is already computed.
Solution Approach 2:
The system changes parameters by dynamically adjusting tote selection criteria based on specific order characteristics. Instead of using fixed selection rules, the WMS modifies selection parameters (compartment size, total capacity, weight limits) to match the actual order requirements, achieving precise fit while maintaining efficient induction throughput.
3Productivity
If robots are assigned orders without considering warehouse activity levels, then order assignment is simple, but robots may sit idle in less active areas
Solution Approach 1:
The system applies local quality by differentiating order assignment strategies based on specific warehouse locations and their activity levels. Instead of uniform assignment, the WMS identifies high-activity zones and prioritizes assigning orders to robots operating in those areas, tailoring the assignment approach to local conditions to maximize productivity while keeping the overall system manageable.
4Reliability
If the wrong tote type is selected for an order set, then induction is quick, but corrections are needed during picking
Solution Approach 1:
The system implements feedback by continuously monitoring order characteristics and comparing them against selected tote specifications. The WMS uses feedback loops to verify that chosen totes meet all requirements (compartment count, size, weight capacity) before finalizing the selection, ensuring high accuracy and smooth operations without requiring later corrections.
Data Source
AI summary
A method for assigning orders to a plurality of robots fulfilling orders in a warehouse with the assistance of a plurality of operators. The method includes providing a first robot of the plurality of robots to a be assigned an order set, including one or more orders to be fulfilled and assessing the locations of at least one of the plurality of robots or at least one of the plurality of operators in the warehouse. The method also includes selecting an anchor location in the warehouse and generating an order set for the first robot correlated to the anchor location in the warehouse. The method also includes assigning the order set to the first robot for fulfillment.