Absorbance Spectrum Prediction for Mixed Dye Mixing
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Solution Overview
Problem
The conventional dyeing process relies heavily on skilled workers to accurately mix single-color dyes for color reproduction, leading to time-consuming and costly trial-and-error methods, especially when inexperienced workers are involved, as it is difficult to identify the optimal dye combination without extensive know-how.
Innovation Solution
An apparatus and method that predict the absorbance spectrum of a mixed dye based on CCM reflectance data, using a processor to convert reflectance data into absorbance data, generate mathematical models for single-color dyes, and correct the dye mixing ratio to match the customer's color order, thereby reducing reliance on skilled workers and minimizing color differences.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If skilled workers use trial-and-error methods to determine dye mixing ratios, then color reproduction accuracy can be achieved, but the process becomes time-consuming and costly
Solution Approach 1:
The system performs preliminary actions by pre-measuring reflectance data for all available single-color dyes and pre-calculating their absorbance spectra before the actual dyeing process. This advance preparation enables the computer to quickly determine optimal mixing ratios without requiring time-consuming trial-and-error experiments during production, thereby resolving the contradiction between color accuracy and process time.
Solution Approach 2:
The system creates a digital copy of the physical dyeing process by measuring reflectance data and converting it to absorbance spectra. This digital representation allows the computer to simulate and calculate optimal dye mixing ratios virtually, replacing the need for repeated physical beaker tests and reducing both time and material consumption while maintaining color reproduction accuracy.
2Manufacturing precision
If skilled workers with extensive know-how are used to select dye combinations, then optimal color matching can be achieved, but the process becomes complex and difficult to replicate
Solution Approach 1:
The system replaces the mechanical system of human expert judgment with an automated computer-based calculation system. The computer uses mathematical algorithms to convert reflectance data to absorbance spectra and automatically determines optimal dye mixing ratios, eliminating the need for workers with decades of experience while maintaining or improving color matching accuracy and making the process replicable.
Solution Approach 2:
The system transforms the complex qualitative knowledge of skilled workers into quantitative parameters by measuring reflectance data and converting it to absorbance spectra. This parameter transformation allows the computer to process dye selection and mixing ratio determination through mathematical calculations, simplifying the decision-making process while maintaining precision.
3Manufacturing precision
If multiple beaker tests are conducted to correct dye mixing ratios, then color difference reduction can be achieved, but the number of required measurements and adjustments increases
Solution Approach 1:
The system implements feedback by measuring the reflectance data of the final dyed fabric and comparing it with the target color specifications. The computer uses this feedback information to calculate the absorbance spectrum and determine whether the dye mixing ratio achieves the desired color match, eliminating the need for multiple iterative beaker tests while maintaining color difference control.
Solution Approach 2:
The system introduces an intermediary computational layer between the physical dyeing process and quality control. The computer acts as an intermediary by calculating optimal mixing ratios based on reflectance measurements and predicting the resulting absorbance spectrum, thereby reducing the need for repeated physical measurements and adjustments while maintaining productivity and color accuracy.
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
This approach simplifies the selection of single-color dye mixing ratios, reduces trial-and-error cycles, and decreases the time and labor required for color reproduction, making it feasible for less experienced workers to achieve accurate color matching in dyeing processes.
Implementation Method 1
a processor reproducing an absorbance spectrum through conversion of reflectance data in a QTX file of the customer order
Data Source
AI summary
An apparatus for predicting an absorbance spectrum of a mixed dye based on CCM reflectance data. The apparatus includes: an input module receiving input of a customer order for dyeing; and a processor reproducing an absorbance spectrum through conversion of reflectance data in a QTX file of the customer order, wherein the processor generates absorbance spectra and predicted colors through conversion of reflectance data of single-color dyes in a dyeing factory; implements a predicted absorbance spectrum of a mixed dye produced according to a recommended single-color dye mixing ratio corresponding to CCM values of the customer order; compares the predicted absorbance spectrum of the mixed dye with the absorbance spectrum according to the customer order; and complements or corrects the recommended single-color dye mixing ratio to match the predicted absorbance spectrum of the mixed dye to the absorbance spectrum according to the customer order.