Article Position Tracking with Rack-Container Identification
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Solution Overview
Problem
Existing article management systems struggle to efficiently track and manage the positions of articles in spaces like plants and warehouses, lacking the ability to easily update and retrieve location information.
Innovation Solution
A system comprising a camera, containers, racks, and a controller that uses identification codes and databases to associate and track articles, containers, and racks, enabling precise location detection based on imaging data and stored associations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional identification methods are used, then the system structure is simple, but the position tracking accuracy and ease of location is poor
Solution Approach 1:
The system segments the storage space into multiple racks, and each rack into multiple containers, with each container holding multiple articles. Each level (rack, container, article) has its own identification code, allowing precise position tracking by recording the hierarchy of locations rather than requiring a single complex positioning system.
Solution Approach 2:
The controller acts as an intermediary that manages the association between identification codes at different levels. It stores and processes the hierarchical relationships between racks, containers, and articles, enabling accurate position determination without requiring direct complex interaction between all components.
2Productivity
If manual location recording is used, then the system complexity is low, but the time required to locate and update article positions is long
Solution Approach 1:
The system automatically tracks article positions by associating identification codes at different levels. When articles are moved between containers or racks, the controller automatically updates the hierarchical associations, eliminating the need for manual location recording while maintaining low operational complexity.
Solution Approach 2:
The system maintains continuous feedback loops where the controller monitors and updates the associations between identification codes. This ensures that position information is always current without requiring manual intervention, improving productivity while keeping the system manageable.
3Loss of information
If detailed hierarchical tracking is implemented, then the position management accuracy is high, but the information storage and processing complexity increases
Solution Approach 1:
The hierarchical structure divides position information into discrete levels (rack level, container level, article level), each with its own identification code. This segmentation allows the system to manage complex position data through simple associative relationships at each level rather than requiring complex integrated tracking.
Solution Approach 2:
The system pre-establishes the hierarchical relationships between racks, containers, and articles in advance. By storing these associations in the controller before actual movement occurs, the system can quickly determine positions without complex real-time calculations, reducing processing complexity while maintaining accuracy.
Data Source
AI summary
An article management system includes a camera, a container, a rack, a storage part, and a controller. The camera images a prescribed space. The container stores an article as a management object. The rack is located inside the space. The rack stores the container. The storage part stores article identification information, container identification information, and rack identification information. The rack includes an identification code being identifiable by the camera. The storage part stores a first association and a second association. The first association is of rack identification information or container identification information, and container identification information. The second association is of the rack identification information or the container identification information, and article identification information. The controller detects a position of the article inside the space based on imaging data and the first and second associations.