Additive Manufacturing Microstructure DOI for Tamper-Proof Identification
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Solution Overview
Problem
Existing methods for labeling and identifying components produced by additive manufacturing are either destructive, tamperable, or lack the necessary uniqueness and reliability for safe identification in critical sectors like aviation and automotive.
Innovation Solution
Generate a digital object identifier (DOI) based on the unique internal microstructure of additively manufactured components using 3D imaging techniques like CT, which captures structural and compositional microfeatures, and convert this data into a tamper-proof QR code or alphanumeric string attached to the component.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If embedded voids or QR codes are used for component identification, then component uniqueness is improved, but the method becomes destructive or tamperable
Solution Approach 1:
The component's natural microstructure serves as its own identification marker. The method extracts unique features from the component's inherent microstructure without requiring external markers or modifications, making the component self-identifying through its own natural characteristics
Solution Approach 2:
The invention changes the identification approach from using external markers (voids, QR codes) to using intrinsic microstructural parameters. By extracting and encoding microstructural features such as pore distributions, inclusion patterns, and grain structures, the system transforms the component's natural variability into a reliable identification signature
2Object-affected harmful factors
If natural microstructure variation is used for DOI generation, then non-destructive identification is achieved, but measurement and detection difficulty increases
Solution Approach 1:
The method extracts specific microstructural features from the complex 3D microstructure data. By identifying and isolating key characteristics such as pore positions, sizes, shapes, and distributions, the system converts complex microstructural information into a manageable set of defining parameters for DOI generation
Solution Approach 2:
The invention replaces complex manual microstructure analysis with automated image processing and computational algorithms. The system uses digital imaging techniques and software-based feature extraction to automatically identify, measure, and encode microstructural characteristics, eliminating the need for manual examination
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Provides a non-destructive, tamper-proof, and unique identification method that ensures one-to-one assignment between physical and digital data, reducing the risk of mix-ups and counterfeiting.
Implementation Method 1
obtaining digital image data of the component c either by using a digital 2D- or 3D-imaging technique... wherein the component is produced by an additive manufacturing process
Data Source
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AI summary
A method for of generating a digital object identifier (100) of a component (c) comprising: obtaining digital image data of the component (c), wherein the component (c) is produced by an additive manufacturing process; identifying a microfeature (f) within the component (c) in the digital image data of the component (c); determining a coordinate, comprising x, y and/or z; and generating the digital object identifier (100) of the component (c) by indicating the coordinate (x, y and or z) of the identified microfeature (f).