Automated Packing System Optimizes Container Stability
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Solution Overview
Problem
Current methods for packing goods into shipping containers, such as pallets, often result in unstable containers with air gaps, leading to damage and inefficiencies, as they do not optimally utilize space or account for item attributes like strength and density.
Innovation Solution
An automated process determines the best configuration of item containers within shipping containers by considering size, position, orientation, strength, density, and categories, generating assignment data to minimize void spaces and ensure stability, which is transmitted for display to packing personnel.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual packing methods are used, then packing speed is fast and process is simple, but packing efficiency is low and void spaces are created
Solution Approach 1:
The system automatically generates packing assignments by self-evaluating item attributes (size, weight, strength) and determining optimal container configurations without human intervention, thereby improving packing efficiency while maintaining operational simplicity through automated decision-making algorithms
Solution Approach 2:
The system changes the packing parameters by considering multiple item attributes simultaneously (size, weight, strength, density) rather than simple volume fitting, enabling optimization of packing efficiency through multi-parameter evaluation and automated assignment generation
2Stability of the object's composition
If items are packed without considering stability, then packing process is simple and fast, but container stability deteriorates and items may fall or crush
Solution Approach 1:
The system performs preliminary stability analysis and generates optimized packing assignments before actual packing occurs, evaluating item attributes and container configurations in advance to ensure stability requirements are met, thereby preventing item damage without adding time to the physical packing process
Solution Approach 2:
The system rapidly evaluates multiple packing configurations and immediately generates optimized assignments without manual verification steps, skipping time-consuming manual stability checks while ensuring stability through automated algorithmic evaluation of item attributes and container configurations
3Object-affected harmful factors
If more containers are used, then item damage is reduced through better protection, but shipping costs increase
Solution Approach 1:
The system optimizes nested arrangements of items within containers by evaluating size and shape compatibility, fitting smaller items into available spaces around larger items, thereby maximizing container utilization and reducing the total number of containers needed while maintaining item protection through proper nesting configurations
Solution Approach 2:
The system transitions from two-dimensional surface packing to three-dimensional volumetric optimization by considering item depth, height, and width simultaneously, enabling more efficient space utilization within containers and reducing container quantity while maintaining item safety through optimized spatial arrangements
4Productivity
If traditional packing methods are used, then packing process is simple, but void spaces are created reducing efficiency
Solution Approach 1:
The system applies local quality optimization by analyzing specific void spaces within containers and determining whether additional items can be fitted into those localized areas based on their dimensions and characteristics, thereby eliminating wasted space through targeted local optimizations rather than uniform packing approaches
Data Source
AI summary
This application relates to automated processes for assigning item containers, such as boxes, to a location on a shipping container, such as a pallet. For example, a computing device may receive an item assignment request identifying a plurality of item containers, and determines a subset of the plurality of item containers for assigning to a layer of a shipping container. Further, the computing device determines a plurality of positions and a plurality of orientations for each of the subset of the plurality of item containers. The computing device also assigns the subset of the plurality of item containers to the layer of the shipping container based on the plurality of positions and the plurality of orientations. The computing device further generates an item assignment response identifying the assignments of the plurality of item containers, and transits the item assignment response for display.