Custom Package Cushioning Using 3D Scanning and Neural Networks
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Solution Overview
Problem
Current packaging methods often result in damage to goods during transport due to insufficient or inappropriate padding, particularly when combining fragile and heavy items, as standardized padding does not adapt to individual transport requirements.
Innovation Solution
A method utilizing 3D scanning and neural networks to create customized padding by obtaining 3D data of goods, sorting and grouping them, virtually arranging them in packaging, selecting a padding template, and producing the padding using an upholstery machine, ensuring individual adaptation to transport needs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If standardized padding is used to fill unused volume in outer packaging, then packaging speed and simplicity are improved, but goods protection and transport reliability deteriorate
Solution Approach 1:
The system performs preliminary scanning and analysis of the goods to be packaged, determining the optimal padding configuration before actual packaging. The 3D scanner captures goods geometry, and the control unit pre-calculates the required padding shape and volume, enabling rapid execution without compromising protection
Solution Approach 2:
The padding system transitions from static standardized forms to dynamic customized shapes. The padding material is dispensed in variable quantities and configurations based on real-time analysis of goods geometry and transport requirements, allowing the packaging to adapt to each specific case while maintaining high speed through automated control
2Reliability
If individual customized padding is produced for each piece of cargo, then goods protection and transport reliability are improved, but device complexity and manufacturing complexity increase
Solution Approach 1:
The system replaces complex manual manufacturing of customized padding with an automated dispensing mechanism controlled by a control unit. The control unit receives 3D scan data and automatically controls the padding dispenser to create the required custom shapes, eliminating the need for complex manual fabrication processes
Solution Approach 2:
The system performs self-measurement and self-configuration through the 3D scanner and control unit, which automatically determine the required padding specifications based on the scanned goods. This self-service capability eliminates the need for manual measurement and calculation, reducing operational complexity while enabling customized padding production
3Manufacturing precision
If 3D scanning and neural network processing are implemented to create customized padding, then padding precision and goods protection are improved, but measurement complexity and processing time increase
Solution Approach 1:
The system extracts only the essential geometric features and dimensions required for padding configuration from the complete 3D scan data. The control unit processes the scan results to identify critical measurement parameters for padding design, eliminating the need to process and analyze every detail of the scanned data, thus reducing measurement complexity while maintaining precision
4Productivity
If loose filling material is used to evenly fill unused volume, then packaging simplicity and speed are improved, but material consumption and environmental impact worsen
Solution Approach 1:
The system applies padding with locally optimized quality and quantity to each specific region of the packaging space. Instead of uniformly distributing loose filling material throughout the entire unused volume, the controlled dispensing mechanism delivers padding only where needed, in the exact amounts required for protection, thereby reducing overall material consumption while maintaining packaging efficiency
Solution Approach 2:
The system enables more efficient use of padding material by precisely delivering it only where needed, reducing waste. The unused or excess padding material can be recovered and reused for subsequent packaging operations, implementing a circular approach that reduces material consumption and environmental impact while maintaining packaging productivity
Data Source
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AI summary
The invention relates to a method for producing upholstery (1) for transporting a piece of goods (2) in an outer packaging (3), with which a computer (4), a 3D scanner (6) and/or an upholstery machine (7) carried out steps: b) Obtaining 3D data of a 3D CAD model and material data for each item (2) by transmission from a database (5) and/or by three-dimensional scanning of the item by means of the 3D scanner (6), c ) Sorting the general cargo (2) by means of a first neural network into a transport category, if one already exists, or else into a transport category to be created, with the first neural network categorizing using the 3D CAD data and the material data, d) grouping the General cargo in a general cargo group based on the transport category and/or a general cargo ID, e) virtual arrangement of the general cargo group in the outer packaging (3), f) selection of a 3D CAD model of a padding front position for the general cargo group using a second neural network based on the virtual arrangement, g) calculating a difference, an intersection and/or a union between the virtual arrangement of the general cargo group in the selected 3D CAD model of the upholstery template and the 3D CAD model the selected upholstery template, the 3D CAD model of the piece goods and the coordinates and orientation of the 3D CAD model of the piece goods as a 3D CAD model of a virtual upholstery, n) producing the upholstery (1) from the 3D CAD model the virtual upholstery using the upholstery machine (7).