Automated Warehouse Dynamic Shelf Positioning
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Solution Overview
Problem
Conventional automated warehouse systems face inefficiencies in storage and retrieval cycles due to the need for pre-acquired storage-retrieval frequency information, leading to suboptimal conveying performance and cycle efficiency.
Innovation Solution
An automated warehouse system with a controller that tracks storage times and moves articles from closer shelves to farther shelves based on predetermined time thresholds, optimizing shelf positions without requiring external information, thereby improving cycle efficiency and reducing long-term storage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If articles are stored on shelves closer to the retrieval station to improve retrieval efficiency, then the cycle efficiency of storage and retrieval is improved, but articles stored for long periods remain in the first area, reducing the effectiveness of shelf position optimization
Solution Approach 1:
The patent implements dynamic shelf position adjustment by dividing shelves into multiple areas (first area closer to retrieval station, second area farther away) and automatically moving articles between areas based on their storage duration. Articles are periodically checked and relocated from the first area to the second area after a predetermined time threshold, enabling the system to adapt shelf positions dynamically rather than statically.
Solution Approach 2:
The patent changes the parameter of shelf position assignment based on the time parameter of article storage. By monitoring storage duration and using this time information to determine article relocation, the system optimizes shelf positions according to actual storage patterns, transforming a static shelf assignment system into one that responds to temporal changes in article usage.
2Productivity
If conventional shelf determining methods are used that require pre-acquired storage-retrieval frequency information, then shelf positioning can be optimized, but the system complexity increases and cycle efficiency cannot be sufficiently increased
Solution Approach 1:
The patent enables the automated warehouse system to self-optimize shelf positions by using its own internal storage time records to determine article relocation decisions. The controller monitors storage duration internally and automatically executes relocation operations without requiring external information acquisition or complex pre-configured frequency data, allowing the system to serve itself in optimizing its own performance.
Solution Approach 2:
The patent implements a feedback mechanism where the system uses actual storage time data (feedback from the controller's monitoring) to adjust shelf positions. This closed-loop approach allows the system to learn from its own operational data and automatically optimize article placement, eliminating the need for external information acquisition while maintaining high conveying performance.
Data Source
AI summary
An automated warehouse system having an improved cycle efficiency of storing and retrieving articles to and from the automated warehouse system includes a storage station, a retrieval station, a plurality of article storage shelves, a stacker crane, and a system controller. An article is brought to the storage station to be stored and retrieved from the retrieval station. The article storage shelves store articles. The stacker crane can move an article between the storage station, the retrieval station, and the article storage shelves. The system controller keeps track of the amount of storage time articles have been stored and, when it determines that an article has been stored on an article storage shelf in a buffer area for a first predetermined amount of time or longer, the system controller controls the stacker crane such that the stacker crane carries the article from an article storage shelf in the buffer area to an article storage shelf in the first storage area.