Automated Coating Pigmentation Matching With Tinting Base Selection
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
The existing color matching processes are inefficient and often result in suboptimal solutions due to the lack of expertise in interpreting spectral remission curves and incorrect combinations of tinting bases, leading to longer processing times, residual color differences, and metamerism issues.
Innovation Solution
A computer-implemented method and system that uses digital color measurements and a radiative transfer model to adjust pigmentation by calculating optimal concentrations of tinting bases, recommending additional pigments to improve color matching accuracy and efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual color matching with spectral remission curve interpretation is used, then color matching expertise can be applied, but the process takes longer and requires experienced colorists
Solution Approach 1:
The patent replaces manual spectral remission curve interpretation with an automated computer-based system that uses digital color measurements and algorithms to determine pigment concentrations. This substitution eliminates the need for experienced colorists to manually analyze complex spectral data, thereby reducing matching time while maintaining or improving accuracy through consistent automated processing.
Solution Approach 2:
The system enables self-service color matching by providing automated recommendations for pigment combinations and concentrations without requiring expert intervention. The computer-implemented method autonomously analyzes target coating measurements, searches formulation databases, and generates matching formulas, allowing the process to serve itself without external expertise.
2Productivity
If incorrect combinations of tinting bases are used, then the matching process can proceed quickly, but the solution quality is limited with residual color differences and metamerism
Solution Approach 1:
The patent implements feedback mechanisms where the system evaluates candidate pigment combinations by calculating predicted color values and comparing them against target measurements. The algorithm iteratively refines pigment selections based on color difference metrics and metamerism assessment, providing feedback that guides the optimization process toward high-quality matches while maintaining efficient processing.
Solution Approach 2:
The system performs preliminary evaluation of multiple pigment combinations before finalizing the matching formula. By pre-assessing candidate formulations using digital color measurements and predicting their performance, the system identifies optimal pigment combinations early in the process, ensuring high solution quality is achieved efficiently without trial-and-error adjustments.
3Adaptability or versatility
If multiple pigments are combined in a formulation, then color matching capability is enhanced, but the interpretation of remission curves becomes more difficult and requires more expertise
Solution Approach 1:
The patent extracts and isolates the complex task of spectral curve interpretation from the overall matching process by implementing automated algorithms that specifically handle multi-pigment analysis. The computer-based system separates the complexity of interpreting overlapping pigment characteristics from the user, extracting only the essential matching results while the system manages the computational complexity of multiple pigment interactions.
4Ease of operation
If a starting formula with non-conforming pigmentation is used, then the color matching process can begin immediately, but the matching takes longer and results in lower quality solutions
Solution Approach 1:
The system performs preliminary optimization of the starting formula by evaluating its pigmentation against the target coating characteristics before the main matching process begins. The automated method pre-adjusts pigment concentrations and identifies appropriate tinting bases, ensuring the starting formula is well-prepared for efficient matching. This preliminary action maintains ease of process initiation while significantly improving subsequent matching efficiency and solution quality.
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
The method enables faster and more reliable color matching by identifying required tinting bases and reducing the need for manual expertise, resulting in improved color similarity and texture alignment with the target coating.
Implementation Method 1
Each included pigment in a formulation changes the color of reflected light as a result of wavelength-dependent absorption and scattering
Implementation Method 2
Each included pigment in a formulation changes the color of reflected light as a result of wavelength-dependent absorption and scattering
Data Source
AI summary
Described herein is a computer-implemented method for matching and adjusting pigmentation of a target coating, the method including at least the steps of: retrieving from a formulation database which includes formulas for coating compositions with different pigmentations, one preliminary matching formula; providing a match metric; and by using one or more processors: calculating a match metric value for the preliminary matching formula; and deciding, based on a magnitude of the match metric value, whether the pigmentation is significantly improvable; in the case that the pigmentation is significantly improvable: defining a selection of at least one additional tinting base which might be eligible for further adjusting the preliminary matching formula to the target coating; calculating, for each of the at least one additional tinting base, a match metric value; and issuing, via an output device, a list of eligible additional tinting bases of the at least one additional tinting base.