Component Material Selection Under Multi-Constraint Compatibility
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Solution Overview
Problem
Current computer-aided design and manufacturing systems lack effective methods for selecting optimal materials for multi-component products, considering both component-level and product-level constraints, which can lead to suboptimal material mixes and manufacturing inefficiencies.
Innovation Solution
A computer-implemented method that provides a set of materials and constraints for each component and the product, using Multiple Criteria Decision Aiding sorting models to determine optimal materials based on compatibility, incorporating Non-Compensatory Sorting and SAT/MaxSAT encodings to find compatible material combinations that satisfy both component and product requirements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If traditional material selection methods are used in CAD/CAM systems, then the design and manufacturing process is simpler, but the material selection quality and manufacturing efficiency deteriorate due to inability to consider multiple constraints simultaneously
Solution Approach 1:
The patent introduces a dedicated material selection module as an intermediary component between the CAD design system and CAM manufacturing system. This module serves as a mediator that receives design requirements from CAD, processes material constraints through Multiple Criteria Decision Aiding algorithms, and outputs optimized material selections to CAM, thereby resolving the contradiction by adding a specialized intermediate layer rather than complicating the entire system
Solution Approach 2:
The material selection process is segmented into distinct functional components: constraint definition, criteria weighting, compatibility checking, and optimization algorithms. By dividing the complex material selection task into manageable segments that can be processed independently and systematically, the system achieves high-quality material selection without overwhelming system complexity
2Reliability
If material constraints are not properly considered, then the manufacturing process is faster, but the manufacturing reliability deteriorates due to incompatible material combinations
Solution Approach 1:
The system performs preliminary material compatibility assessment and constraint verification during the design phase before manufacturing begins. By pre-evaluating material combinations against defined constraints and compatibility criteria, the system ensures reliable material selections are made upfront, preventing manufacturing delays and rework while maintaining high productivity
Solution Approach 2:
The material selection module implements feedback mechanisms where compatibility results and constraint satisfaction levels are continuously evaluated and fed back into the optimization process. This allows the system to adjust material selections in real-time based on compatibility assessments, ensuring reliable outcomes without sacrificing manufacturing efficiency through iterative refinement
3Reliability
If multiple criteria are considered for material selection, then the material compatibility improves, but the computational complexity increases due to Multiple Criteria Decision Aiding requirements
Solution Approach 1:
The system transforms the complex Multiple Criteria Decision Aiding problem into a more manageable form by changing parameters: converting qualitative compatibility requirements into quantitative constraint equations, and transforming multi-objective optimization into a structured algorithmic process with defined weighting factors. This parameter transformation reduces computational complexity while maintaining comprehensive criteria evaluation
Solution Approach 2:
The patent applies different levels of analytical depth to different aspects of material selection: simple compatibility checks for basic constraints, moderate complexity for common material properties, and full MCDA algorithms only for critical decision points. By applying local quality of analysis matched to the importance and complexity of each evaluation aspect, the system achieves high material compatibility without uniformly high computational complexity throughout the entire process
Data Source
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AI summary
The disclosure notably relates to a computer-implemented method for selecting materials of components of a product to be manufactured. The method comprises providing a set of materials for the components of the product. The method also comprises providing, for each component, a set of use and/or manufacturing and/or material constraints for the component. The method also comprises providing, for the product, a set of use and/or manufacturing constraints for the product. The method also comprises providing, for the product, one or more material compatibility constraints. The method also comprises providing specifications. The specifications indicate an extent of compatibility of one or more reference materials within the set of materials with the constraints. The method also comprises determining, for each component of the product, at least one optimal material, with respect to compatibility with the constraints and based on the provided specifications, for manufacturing the component.