Non-Uniform Shelving Layout for Robotic Crate Storage
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Solution Overview
Problem
Modern logistic centers face inefficiencies in storage space utilization due to uniform vertical spacing between shelves, which restricts the handling of crates of varying sizes and limits accessibility, leading to suboptimal storage capacity and accessibility efficiency.
Innovation Solution
Implementing a shelving system with non-uniform vertical spacing between horizontal storage surfaces and a computerized control system that routes lift robots to optimize storage and retrieval based on crate size, allowing for the use of crates of different heights and widths, and relocating items to smaller storage locations when available.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If uniform vertical spacing between shelves is used, then structural simplicity and ease of manufacture are improved, but storage capacity and accessibility for varied crate sizes deteriorate
Solution Approach 1:
The shelving structure is segmented into multiple zones with different vertical spacing configurations. Each zone can be independently designed to accommodate specific crate size ranges, allowing the system to handle varied crate dimensions while maintaining manufacturing simplicity within each segment.
Solution Approach 2:
Different regions of the shelving structure have different vertical spacing characteristics. Specifically, certain shelving units have reduced vertical spacing in specific zones to optimize storage for particular crate height ranges, while other regions maintain standard spacing for different crate types.
2Adaptability or versatility
If non-uniform vertical spacing between shelves is implemented, then storage capacity and adaptability for varied crate sizes are improved, but device complexity and manufacturing difficulty increase
Solution Approach 1:
The shelving system incorporates universal components and standardized connection mechanisms that can accommodate both uniform and non-uniform spacing configurations. This allows the same basic structural elements to be reused across different spacing zones, reducing overall manufacturing complexity despite the varied spacing requirements.
Solution Approach 2:
The system allows for adjustable and reconfigurable spacing parameters through modular design elements. Vertical spacing can be modified by reconfiguring modular components rather than requiring custom-made parts for each spacing variation, thereby managing device complexity while maintaining adaptability.
3Productivity
If robots are routed through tracks for crate delivery and retrieval, then automation and productivity are improved, but energy consumption and maintenance costs increase
Solution Approach 1:
The system performs preliminary routing calculations and optimization to determine the most energy-efficient paths for robots. By pre-planning routes that minimize travel distance and avoid unnecessary movements, the system reduces energy consumption while maintaining high productivity levels.
Solution Approach 2:
The routing system incorporates feedback mechanisms that monitor robot position, energy consumption, and task completion status in real-time. This feedback enables dynamic route optimization, where paths are adjusted based on current system state to minimize energy usage while ensuring timely crate delivery and retrieval.
4Use of energy by moving object
If average traveling distance for robots is reduced, then energy efficiency and maintenance costs are improved, but storage accessibility and retrieval time may deteriorate
Solution Approach 1:
The system optimizes robot routing by utilizing three-dimensional space more effectively. Robots can travel through vertical and horizontal track intersections to reach storage locations more directly, reducing the average traveling distance without compromising accessibility. This multi-dimensional routing approach allows shortcuts that would not be possible in a two-dimensional plane.
Solution Approach 2:
The system replaces traditional mechanical routing with computerized control and intelligent path planning algorithms. The computerized control system calculates optimal routes that minimize travel distance while ensuring timely access to all storage locations, substituting mechanical route fixedness with flexible, computationally-determined paths.
Data Source
AI summary
A storage setup and method for robotic delivery and retrieval of crates from shelving blocks are disclosed. At least one shelving block in the setup comprises non-uniformly spaced apart storage surfaces. The storage surfaces are accessible to lift-robots through a network of tracks comprising intersecting vertically and horizontally oriented tracks. A computerized control system is configured to differentiate between storage locations based on which crate sizes from at least two different ranges of crate sizes a storage location can store. The storage may be automatically optimized by routing robots to store crates in storage locations sized in correlation with the size of the crate to be stored.