Automated Layer Picker Scheduling for Shorter Pallet Travel
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Solution Overview
Problem
Existing automated layer pickers, such as gantry and robotic arm layer pickers, are limited by their pick area and travel distance, leading to reduced throughput and inefficient use of resources due to the need to move pallets multiple times before depletion or assembly, causing delays and inefficiencies in warehouse operations.
Innovation Solution
A computer system determines and iteratively adjusts batches, locations, and schedules of pallets to optimize throughput by minimizing travel distance and maximizing the efficiency of automated layer pickers, using a heuristic approach to dynamically adapt to real-time changes in orders and availability of source pallets.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If source pallets are positioned further from the destination pallet in the layer picking area, then the picking area can accommodate more pallets, but the automated layer picker has to travel a further distance, reducing throughput
Solution Approach 1:
The system performs preliminary planning and optimization of pallet positions before the picking operation begins. The computer system determines optimal positions for source and destination pallets in advance, calculating arrangements that minimize travel distance while maximizing area utilization. This preliminary optimization ensures that when picking operations start, all pallets are in their most efficient positions.
Solution Approach 2:
The system dynamically adjusts pallet positions and picking sequences based on real-time conditions. The computer system continuously monitors the picking area and reoptimizes pallet arrangements during operation, allowing the system to adapt to changing conditions and maintain optimal throughput while maximizing area capacity.
2Productivity
If pallets are moved in and out of the layer picking area multiple times before being fully depleted or assembled, then more pallets can be processed, but more automated pallet moving resources are used, causing delays
Solution Approach 1:
The system performs preliminary batching and grouping of pallets that will be processed together. By identifying which source pallets will supply which destination pallets in advance, the system can set up all necessary pallets in the picking area before operations begin, eliminating the need for multiple trips in and out of the area.
Solution Approach 2:
The system merges multiple picking operations into single continuous operations by grouping destination pallets that require items from the same source pallets. This consolidation allows the automated layer picker to process multiple destination pallets in sequence without requiring source pallets to be moved in and out repeatedly.
3Device complexity
If the automated layer picker is limited to a specified picking area, then the system structure can be simplified, but the travel distance increases and throughput decreases
Solution Approach 1:
The system optimizes the spatial arrangement of pallets within the constrained picking area by utilizing two-dimensional positioning strategies. The computer system calculates optimal x-y coordinates for each pallet, effectively using the horizontal plane to minimize travel distance without requiring additional vertical space or complex three-dimensional structures.
Solution Approach 2:
The system changes the operational parameters of the automated layer picker, including picking sequences, travel speeds, and pallet positions, to optimize throughput within the fixed picking area. By dynamically adjusting these parameters based on real-time conditions, the system maximizes productivity without expanding the physical picking area or increasing structural complexity.
Data Source
AI summary
Disclosed are techniques for determining and controlling automated layer pick operations. A computer system can receive, from a warehouse management system, a layer pick planning request for at least one order and determine an initial feasible solution for completing the request. The computer system can determine: initial batches of pallets based on grouping destination pallets that require layers of items from same source pallets, corresponding batch scores, initial locations of the pallets based on assigning locations in a pick area to the source and destination pallets, corresponding location scores, initial schedules for the initial batches based on determining an order of tasks to complete each batch, and corresponding schedule scores. For each batch, the computer system can iteratively adjust the initial schedule, initial locations based on the adjusted schedule, and initial batches based on the adjusted schedule and adjusted locations. The computer system can then identify a heuristic solution.