Computer-Implemented Detergent Performance Evaluation Method
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Solution Overview
Problem
The detergent development process is time-consuming and costly, often resulting in suboptimal detergent compositions due to inefficiencies in evaluating and optimizing wash conditions and ingredient data.
Innovation Solution
A computer-implemented method and electronic device that obtain wash conditions and ingredient data to determine and optimize detergent compositions, providing performance evaluations for stain removal, cost, sustainability, and ecolabel performance, thereby simplifying and accelerating the development cycle.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional detergent development processes are used, then comprehensive performance evaluation can be achieved, but the process becomes time-consuming and costly
Solution Approach 1:
The patent creates virtual copies of physical testing through computer simulations. Performance models simulate stain removal, cost, sustainability, and ecolabel performances without requiring actual physical trials. This allows comprehensive evaluation of multiple detergent compositions simultaneously in silico, dramatically reducing the time and resources needed while maintaining evaluation thoroughness.
Solution Approach 2:
The system performs preliminary computational analysis and performance prediction before physical formulation and testing. By using performance models to evaluate detergent compositions in advance, the invention identifies promising formulations computationally, allowing researchers to focus physical resources only on the most promising candidates, thereby reducing overall development time and cost.
2Adaptability or versatility
If multiple performance parameters are evaluated, then optimization capability improves, but resource consumption increases
Solution Approach 1:
The patent implements a universal performance evaluation system that handles multiple performance types (stain removal, cost, sustainability, ecolabel) through a single integrated platform. The system can evaluate different detergent compositions across all these performance dimensions simultaneously using computational models, eliminating the need for separate physical testing programs for each performance metric and significantly reducing resource consumption.
Solution Approach 2:
The invention replaces mechanical/physical testing systems with computational models and algorithms. Instead of conducting physical experiments to evaluate multiple performance parameters, the system uses computer-based performance models that calculate stain removal, cost, sustainability, and ecolabel performances mathematically, thereby evaluating multiple parameters with minimal resource consumption.
3Measurement precision
If physical trials and tests are conducted, then performance data accuracy is ensured, but cost and time requirements increase
Solution Approach 1:
The system creates virtual replicas of physical testing scenarios through computational models. These digital twins simulate the chemical and physical interactions of detergent ingredients with stains and fabric under various wash conditions, providing accurate performance predictions without the need for expensive and time-consuming physical trials for every formulation variant.
Solution Approach 2:
The patent applies partial physical testing combined with extensive computational evaluation. Rather than conducting full physical trials on all possible formulations, the system uses performance models to screen and prioritize candidates, then conducts limited physical validation only on the most promising formulations identified computationally, thereby achieving accurate data with reduced cost and effort.
Data Source
AI summary
A computer-implemented method for performance evaluation of a detergent composition is disclosed, the method comprising obtaining one or more wash conditions including a first wash condition; obtaining ingredient data comprising first ingredient data and second ingredient data, the first ingredient data associated with one or more first ingredients including a first primary ingredient and the second ingredient data associated with one or more second ingredients including a second primary ingredient; determining a first detergent composition based on the ingredient data; determining a first performance of the first detergent composition; and outputting a first performance representation of the first performance.


