Structurally Encoded Component via 3D Printing
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Solution Overview
Problem
Current identification methods for sensitive objects and components are prone to wear, removal, or alteration, and have limited data storage capacity, making them ineffective for secure tracking and communication, especially in applications like medical devices, vehicles, and pharmaceuticals.
Innovation Solution
A method involving 3D printing to embed encoded data into components by converting structural parameters into indicia, which are then integrated into the component using a 3D printer, allowing for high data density storage and secure identification through imaging methods like x-ray or CT scans.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional identification tags, plates, or labels are used for component identification, then the identification method is simple to implement, but the identification becomes ineffective due to wear, intentional or unintentional removal, or alteration, and the data storage capacity is limited
Solution Approach 1:
The patent merges the identification data with the component itself by embedding encoded structural features directly into the component's geometry. The component's physical structure serves dual purposes: functional operation and identification/data storage. This eliminates separate identification tags or labels that are prone to wear and removal, while integrating the identification system into the manufacturing process itself.
Solution Approach 2:
The patent embeds encoded identification data within the component's internal or external structure. The identification features are nested within the component's geometric design, allowing the component to contain its own identification information without adding external elements. This nesting approach protects the identification data from external damage and removal.
2Loss of information
If existing identification devices are used, then the implementation is straightforward, but the size of the identification device limits the amount of information that can be stored
Solution Approach 1:
The patent transitions from traditional two-dimensional surface labels to three-dimensional structural encoding. By utilizing the component's volumetric space and geometric complexity across multiple dimensions, the system can encode significantly more information within the same physical footprint. The identification data is distributed throughout the component's structure rather than confined to a surface label.
Solution Approach 2:
The patent encodes information by varying multiple structural parameters of the component simultaneously, including but not limited to dimensions, shapes, positions, orientations, and material properties. By modulating numerous geometric parameters, the system achieves high data density without increasing the component's overall size, as each parameter variation contributes to the encoded information.
3Reliability
If structural parameters are converted into indicia and embedded via 3D printing, then robust and secure identification is achieved with high data density storage, but the manufacturing process becomes more complex
Solution Approach 1:
The patent incorporates identification encoding into the preliminary design and manufacturing stages. The structural parameters that define the component's function are simultaneously used to encode identification data. This preliminary integration means that the identification features are created during the base manufacturing process itself, rather than requiring separate post-processing steps for tagging or labeling.
Solution Approach 2:
The component's manufacturing process serves dual purposes: creating the functional component and embedding its identification system. The 3D printing or additive manufacturing process that forms the component also directly creates the encoded structural features. This self-service approach eliminates the need for separate identification device installation and reduces overall manufacturing complexity despite the advanced encoding capabilities.
Data Source
AI summary
A method of inserting a data structure into a component using a 3D printer is provided. The method includes providing the data structure having at least one structural parameter associated with the component, converting the data structure into indicia representative of the data structure, and manufacturing the component containing the indicia.