Cdot Matrix Code for Traceability on Reflective Surfaces
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Solution Overview
Problem
Existing methods for digitizing raw materials, components, and products exposed to harsh operational conditions, such as QR and Data Matrix codes, are insufficient due to issues like axial non-uniformity, angle distortion, and grid non-uniformity, especially on inclined and reflective surfaces, and in environments with high temperature, humidity, and vibration.
Innovation Solution
A pattern coding and decoding method that uses a unique Cdot Matrix, which is resistant to harsh operational conditions and can be applied to various surfaces and materials, including inclined, reflective, transparent, and textured surfaces, using techniques like laser carving, UV printing, and silkscreen processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If QR or Data Matrix codes are applied to surfaces exposed to harsh operational conditions, then digitization and traceability are achieved, but the codes become unreadable due to axial non-uniformity, angle distortion, and grid non-uniformity
Solution Approach 1:
The patent applies asymmetry by designing a code structure that intentionally incorporates asymmetric error correction patterns and distortion compensation algorithms. The code geometry is designed to accommodate expected distortions through asymmetric placement of reference markers and adaptive decoding regions that can handle non-uniform axial and angular variations.
Solution Approach 2:
The patent implements beforehand cushioning by embedding redundant error correction data and distortion compensation information within the code structure before the harsh conditions occur. The code is pre-designed with buffers against axial non-uniformity, angle distortion, and grid non-uniformity that will protect readability even when exposed to high temperature, humidity, and vibration.
2Ease of manufacture
If conventional coding methods are used on inclined and reflective surfaces, then application is simplified, but the codes cannot be properly read due to surface geometry and reflectivity
Solution Approach 1:
The patent applies local quality by adapting the code properties to local surface characteristics. Different regions of the code are designed with varying error correction strengths and geometric tolerances based on the expected local distortion patterns. The decoding algorithm adjusts local parameters such as reference marker weighting and grid tolerance thresholds to match the specific surface geometry being read.
3Reliability
If codes are applied before heavy metallized coating, plasma diffusion, or HIPIMS processes, then traceability is maintained, but the codes are covered and become unreadable
Solution Approach 1:
The patent implements nested doll by creating a hierarchical code structure where multiple layers of information are embedded within each other. The code contains embedded reference patterns at different scales and densities, allowing the decoding algorithm to extract traceability information even when portions of the code are covered or distorted by subsequent coating processes.
4Adaptability or versatility
If existing digitization solutions are used for complex shapes and curved surfaces, then application coverage is improved, but axial non-uniformity and angle distortion prevent successful reading
Solution Approach 1:
The patent applies dynamics by implementing a dynamic decoding algorithm that adapts to the actual geometric distortions present in each code instance. The system dynamically adjusts decoding parameters such as grid tolerance, angle compensation factors, and reference marker positioning based on real-time analysis of the code's actual geometry, allowing successful reading even when codes are applied to complex curved surfaces.
Data Source
AI summary
A method for traceability of raw materials or objects exposed to operational conditions in industry, including coding phasea and decoding phase. The coding phase includes steps of uploading a design matrix file to a Cdot API, the Cdot matrix is a digital decomposition part of the coding phase, coding parameter inputs of the design matrix; generating a Cdot matrix by embedding a codeword using a Cdot matrix calculation algorithm. The decoding phase includes providing the Cdot matrix to a reader device; creating a Cdot matrix image from a raw image of a material or object or product having a Cdot matrix on a surface captured by a camera; decoding coded values in a code area of the Cdot matrix image to extract an assertive code; interpreting the assertive code to determine a unique object or material identification definition; providing the the object or material identification definition to a display.