Dye Mixing Ratio Correction Using Fabric and Dye Characteristic Data
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Solution Overview
Problem
Current dye mixing ratio correction methods in computer color matching (CCM) systems fail to effectively consider fabric and dye characteristic data, leading to significant trial and error in beaker tests, experimental dyeing, and on-site dyeing, resulting in inefficiencies and increased costs due to the lack of utilization of fabric and dye characteristics in correcting colorimetric deviations.
Innovation Solution
An apparatus and method that utilize fabric characteristic data and dye characteristic data to generate a learning dataset through data augmentation, allowing for the calculation of correction values to minimize deviations between requested and measured CCM colorimetric values, thereby optimizing the dye mixing ratio and reducing trial and error in dyeing processes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If CCM colorimetric system is used to determine dye mixing ratio, then color matching can be performed computationally, but significant trial and error is still required in beaker tests and experimental dyeing due to lack of fabric and dye characteristic data
Solution Approach 1:
The system performs preliminary actions by collecting fabric characteristic data (fiber composition, weight, structure) and dye characteristic data (chemical structure, molecular weight, absorption wavelength, color strength, solubility, dispersion point, reaction point, exhaustion rate, fixing rate) before the actual dyeing process. This preliminary data collection and analysis enables the computational color matching system to make more accurate initial predictions, reducing the number of trial and error cycles needed in subsequent beaker tests and experimental dyeing operations.
Solution Approach 2:
The system implements feedback mechanisms by continuously comparing the computed color results with actual measured CCM values from fabric samples. The fabric characteristic data and dye characteristic data are used to refine the computational model based on actual dyeing outcomes. This feedback loop allows the system to learn from previous dyeing results and improve the accuracy of dye mixing ratio predictions, thereby reducing time loss in repeated trial and error processes.
2Ease of manufacture
If conventional CCM colorimetric measurement is used without fabric and dye characteristic data, then the process is simpler, but manufacturing precision of color matching deteriorates due to deviations between requested and actual colors
Solution Approach 1:
The system changes the parameters used in CCM colorimetric measurement by incorporating fabric characteristic data (fiber composition, weight, structure) and dye characteristic data (chemical structure, molecular weight, absorption wavelength, color strength, solubility, dispersion point, reaction point, exhaustion rate, fixing rate). These additional parameters are integrated into the computational color matching process, transforming the simple CCM measurement into a multi-parameter analysis system that significantly improves color matching precision while maintaining operational simplicity through automated data processing.
3Measurement precision
If fabric and dye characteristic data are collected and analyzed, then dye mixing ratio accuracy is improved, but device complexity and data processing requirements increase
Solution Approach 1:
The system introduces an intermediary computational color matching system that acts as a mediator between the raw fabric and dye characteristic data and the final dye mixing ratio determination. This intermediary system automatically processes the complex multi-dimensional data (fabric characteristics, dye characteristics, CCM values) using algorithms and mathematical models to compute optimal dye mixing ratios. By placing this intelligent intermediary in the process, the system manages data complexity through automated processing while delivering high measurement precision for dye mixing ratios, reducing the burden on operators to manually handle complex data.
Data Source
AI summary
The present invention relates to an apparatus for correcting a dye mixing ratio, the apparatus including a memory, and a processor connected to the memory, wherein, upon receiving a dyeing order including a first computer color matching (CCM) colorimetric value requested by a client, the processor uses at least one of the first CCM colorimetric value, a currently selected dye mixing ratio, a second CCM colorimetric value measured in a dyeing process, fabric characteristic data, and dye characteristic data and corrects the dye mixing ratio so that deviation between the first CCM colorimetric value and the second CCM colorimetric value is minimized.