Mixed-Mode Order Picking for Low-Volume Articles
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Solution Overview
Problem
Existing storage and order-picking systems are inefficient in handling articles with low piece numbers for e-commerce and direct delivery to end customers, particularly in the order-picking zone, which has become a critical performance bottleneck.
Innovation Solution
A method and system that classifies articles into two groups: one for automatic handling and another for manual handling based on error rates, using automatic and manual order-picking stations to efficiently process orders with mixed article types.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If articles are handled manually in the order-picking zone, then flexibility and adaptability are improved, but productivity and automation extent deteriorate
Solution Approach 1:
The order-picking system is segmented into multiple workstations, each specialized for specific article types (e.g., perishable goods, non-perishable goods, cold chain articles). This segmentation allows automatic handling for standardized articles while reserving manual handling capability for specialized cases, thereby improving both productivity through automation and adaptability through specialized manual stations.
Solution Approach 2:
Different workstations are equipped with different handling capabilities and equipment suited to local requirements. For example, cold chain workstations have temperature-controlled environments, while general workstations use standard automated pickers. This local quality approach ensures that each article type is handled by the most appropriate method, balancing automation efficiency with handling flexibility.
2Productivity
If articles are handled automatically in the order-picking zone, then productivity is improved, but adaptability and ease of operation deteriorate
Solution Approach 1:
The system dynamically routes orders to appropriate workstations based on real-time order composition. When an order contains articles suitable for automatic handling, they are routed to automated stations; when manual handling is required, the system dynamically assigns those specific articles to manual workstations. This dynamic adaptation maintains high productivity while preserving flexibility for complex orders.
Solution Approach 2:
The order-picking system is designed as a universal platform that can handle both automatic and manual picking within the same facility. Multiple workstations with different capabilities work in parallel, allowing the system to adapt to various order types without sacrificing overall productivity. The universal design enables seamless switching between automatic and manual handling modes.
3Extent of automation
If the order-picking zone is fully automated, then extent of automation is improved, but device complexity and difficulty of detecting and measuring deteriorate
Solution Approach 1:
The automated system is divided into modular workstation units, each with dedicated functionality for specific article types. This segmentation reduces the complexity of individual automated stations while maintaining high overall automation. Each module can be independently controlled and maintained, simplifying the management of system complexity.
4Ease of operation
If the order-picking zone is fully manual, then ease of operation is improved, but productivity and extent of automation deteriorate
Solution Approach 1:
The system segments manual workstations into specialized units (cold chain, perishable, non-perishable) that handle specific article types. This segmentation simplifies operational complexity at each station while maintaining high productivity through optimized workflows. Workers at each station deal only with their specialized article type, improving ease of operation.
Solution Approach 2:
The system introduces an intelligent routing intermediary that automatically directs articles to appropriate workstations based on their handling requirements. This intermediary reduces the operational burden on workers by eliminating the need for them to make routing decisions, thereby improving ease of operation while maintaining high productivity through optimized article flow.
Data Source
AI summary
In a method for order-picking articles from source loading aids into or onto target loading aids in a storage and order-picking system, the articles belong to a first group of types of article, whose types of article can be handled automatically, or a second group of types of article, whose types of article can be handled manually. A first order part with articles of the first group of types of article is transported to a first automatic order-picking station and order-picked there, and a second order part with articles of the second group of types of article is transported to a first manual order-picking station and order-picked there. Further, a storage and order-picking system executes the method.