Order Batching and Robot Scheduling for High-Volume Picking
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Solution Overview
Problem
The traditional 'person-to-goods' picking system in logistics faces challenges of low efficiency, high error rates, high work intensity, and high labor costs, while the 'goods-to-person' picking system, although improved, still struggles with low picking efficiency, especially when dealing with large quantities of orders.
Innovation Solution
An order processing method and device that divides pending orders into batches, allocates tasks to target workstations, selects matching inventory containers and robots, and optimizes the picking process by determining overlapping order items and scheduling robots to reduce carrying and picking times, thereby improving efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the traditional 'person-to-goods' picking system is used, then labor cost and work intensity are high, but the picking efficiency is low and error rate is high
Solution Approach 1:
The system segments the picking process into distinct functional modules: order reception module, batch division module, task allocation module, robot selection module, and execution module. Each module handles a specific aspect of order processing, allowing for independent optimization and maintenance while improving overall picking efficiency through automated coordination.
Solution Approach 2:
The patent introduces an intermediary control system that acts as a mediator between the order pool and the robot fleet. This control system receives orders, divides them into batches, allocates tasks to workstations, and selects appropriate robots, thereby coordinating the entire picking process without requiring direct human intervention in each transaction.
2Productivity
If the 'goods-to-person' picking system is adopted, then picking efficiency is improved, but it still faces the problem of low picking efficiency when dealing with large quantities of orders
Solution Approach 1:
The system performs preliminary actions by pre-dividing orders into batches before actual picking execution. The batch division module analyzes order characteristics and groups compatible orders together in advance, so that when picking time arrives, robots can efficiently handle pre-organized batches rather than processing individual orders sequentially, significantly reducing total processing time.
Solution Approach 2:
The patent implements continuous useful action by maintaining an always-active order pool that continuously receives, processes, and dispatches orders. The system operates without idle periods, with the control system continuously monitoring the order pool, dividing new orders into batches, allocating tasks to available workstations, and dispatching robots, ensuring that picking operations flow continuously without interruptions.
3Productivity
If multiple robots are used to handle large quantities of orders, then order processing capacity increases, but the coordination complexity and task allocation difficulty increase
Solution Approach 1:
The control system implements self-service by autonomously performing task allocation and robot selection based on predefined criteria and real-time system state. The system automatically evaluates which robots are available, matches them with appropriate tasks based on workload and capability, and assigns tasks without requiring external intervention, thereby managing multiple robots efficiently while minimizing coordination complexity.
Data Source
AI summary
The present disclosure discloses an order processing method. The method includes: receiving at least one pending order and placing the at least one pending order in an order pool; dividing part or all of pending orders in the order pool into at least one batch of task; for any of the at least one batch of task, allocating the batch of task to a corresponding target workstation, selecting a target inventory container matching an order item for a pending order in the batch of task, and selecting a target robot for carrying the target inventory container for the batch of task; controlling the target robot to carry the target inventory container matching the order item to the target workstation corresponding to the batch of task. The present disclosure further discloses an order processing device, a server, and a storage medium.