Security Printing Compensation for Authentication Accuracy
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Counterfeit goods and misrepresentation of products undermine producers' reputations and consumers' trust due to substandard quality, resulting in revenue loss for both parties.
Innovation Solution
Implementing security printing methods that utilize variable data printing with closed-loop qualification and open-loop authentication, incorporating structural, spectral, and thermo-chromic/fading compensations to create unique, difficult-to-reproduce features in security features like 2D Data Matrix barcodes, ensuring they can be authenticated accurately across various devices and processes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional printing methods are used, then manufacturing simplicity is maintained, but security features can be easily reproduced by counterfeiters
Solution Approach 1:
The system performs preliminary characterization of the printing process to determine compensation values before actual printing. A test pattern is printed first, measured to detect deviations, and compensation values are calculated and stored. These pre-computed compensation values are then applied during production printing, enabling accurate security features without adding complexity to the main printing workflow.
Solution Approach 2:
The system implements a feedback loop where the printed test pattern is measured and analyzed to detect deviations from the intended design. These measurements feed back into the compensation calculation process, which adjusts the compensation values to account for printing process variations. This closed-loop feedback ensures that the security features are printed with the correct dimensions and characteristics for reliable authentication.
2Reliability
If security features are made more complex to prevent counterfeiting, then authentication reliability improves, but manufacturing precision requirements increase
Solution Approach 1:
The system pre-characterizes the printing process by printing test patterns and measuring them to determine the relationship between intended and actual feature dimensions. Compensation values are calculated in advance based on these measurements, allowing the system to compensate for printing variations without requiring ultra-precise printing control during production.
Solution Approach 2:
The system changes the parameters of the security features by applying compensation values that adjust the intended feature dimensions. Instead of requiring the printing process to achieve exact dimensions, the system modifies the design parameters of the security features to account for expected printing variations, ensuring that the printed features fall within acceptable tolerances for authentication.
3Measurement precision
If compensation values are pre-computed for each printing process, then authentication accuracy improves, but data storage requirements increase
Solution Approach 1:
The system stores compensation values locally associated with specific printing processes, authentication features, and capture devices rather than maintaining a single large database. Each printing process has its own set of compensation values tailored to its specific characteristics, allowing for precise compensation without requiring storage of all possible compensation scenarios.
Solution Approach 2:
The system uses characterization data that describes the general behavior of printing processes, authentication features, and capture devices. This characterization data allows the system to compute specific compensation values as needed based on the actual printing conditions, rather than pre-computing and storing all possible compensation values for every conceivable scenario.
Data Source
AI summary
Method for security printing. A digital model of a feature for printing is received, wherein the feature is for authentication by an external device. Deviation from the digital model is compensated for, to a printed instance of the feature.