Anodizing Parameter Analysis via Shapley Value Contribution

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Solution Overview

Problem

It is challenging for manufacturers to determine the essential processing parameters affecting the dyeing results of anodized aluminum alloys due to the complexity of the anodizing and dyeing process, which involves multiple variables such as temperature, sulfuric acid concentration, and residence time, making it difficult to find relationships between these parameters and the resulting dyeing outcomes.

Innovation Solution

A data analysis method is provided that acquires sample data groups containing dyeing result and processing parameter data, determines contribution values for each processing parameter, and identifies essential parameters affecting dyeing results through analysis, using techniques like the Shapley value method and data fusion to adjust processing parameters for improved outcomes.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If multiple processing parameters are used in the anodizing and dyeing process, then the quality and durability of the anodized products are improved, but it becomes difficult to determine the essential parameters affecting dyeing results

Engineering Contradiction:

Improvequality and durability of anodized productsVSAvoidcomplexity of parameter analysis

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The patent extracts and identifies essential processing parameters from a large set of multiple processing parameters through data analysis. By using contribution value calculation and parameter selection algorithms, the system separates the critical parameters that actually affect dyeing results from the non-essential ones, simplifying the parameter set while maintaining product quality and durability.

Inventive Principle:

Principle #2Taking out (Extraction)

Solution Approach 2:

The patent changes the state of parameter analysis by transforming raw processing parameter data into contribution values through mathematical modeling. This parameter transformation allows the system to quantify the influence of each parameter on dyeing results, enabling identification of essential parameters despite the complexity of having multiple parameters in the process.

Inventive Principle:

Principle #35Parameter changes

2Measurement precision

If comprehensive data analysis is performed on all processing parameters, then the accuracy of identifying essential parameters is improved, but the computational complexity and time consumption increase

Engineering Contradiction:

Improveaccuracy of parameter identificationVSAvoidtime consumption for data analysis

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The patent applies partial action by calculating contribution values for all parameters initially, then using threshold-based filtering to select only the essential parameters. This approach performs comprehensive analysis where needed (calculating all contribution values) but limits further processing to only the necessary subset of parameters, balancing accuracy with time efficiency.

Inventive Principle:

Principle #16Partial or excessive action

Solution Approach 2:

The patent replaces manual parameter analysis with automated computational algorithms. By using computer-based data processing, mathematical modeling, and automatic parameter selection algorithms, the system achieves high accuracy in identifying essential parameters while significantly reducing the time consumption compared to manual analysis methods.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

3Ease of manufacture

If traditional manual analysis methods are used to determine parameter relationships, then the process is simple to implement, but the ability to find relationships between parameters and dyeing results is insufficient

Engineering Contradiction:

Improveease of implementationVSAvoidability to find parameter relationships

Core Design Contradiction:

Ease of manufactureVSLoss of information

Solution Approach 1:

The patent introduces an intermediary computational system that bridges manual analysis and complex data relationships. The system uses automated algorithms as intermediaries to process processing parameter data, calculate contribution values, and identify essential parameters, thereby recovering the lost ability to find parameter relationships while maintaining ease of implementation through computer automation.

Inventive Principle:

Principle #24Intermediary (Mediator)

Solution Approach 2:

The patent implements feedback mechanisms where the data analysis system continuously processes processing parameter data, calculates contribution values, and provides feedback on which parameters are essential. This feedback loop enables the system to automatically adjust and refine parameter identification, maintaining high accuracy while being easy to implement through standardized computational procedures.

Inventive Principle:

Principle #23Feedback

Data Source

PatentUS20230160811A1Data analysis method, computing device, and storage medium

Publication Date: 2023.05.25 SHENZHENSHI YUZHAN PRECISION TECH CO LTD

AI summary

A data analysis method for optimization of aluminum anodizing and dyeing process acquires a plurality of sample data groups, each sample data groups comprising dyeing result data and parameter data of multiple processing parameters. Contribution value of each processing parameter data relative to the dyeing result data in each of the plurality of sample data groups is determined, and the contribution values are used to determine at least one essential processing parameter. The essential processing parameters are then adjusted according to a data analysis result for improving quality of products. A computing device and storage medium are also provided.