CAD Model Customization via Constraint Satisfaction Optimization
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Solution Overview
Problem
Existing CAD systems face challenges in efficiently and optimally customizing mechanical designs due to complex dependencies between design changes and parameter values, making it difficult to ensure compliance with dependencies and achieve globally optimal solutions.
Innovation Solution
A system that converts the configuration model into a constraint satisfaction problem (CSP), using a configuration engine to calculate an optimal solution and a CAD interface to update the CAD model, allowing for flexible parameter entry and explicit definition of dependencies, ensuring compliance with design choices and providing immediate feedback on parameter changes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If manual customization of CAD model is performed by changing dimensions and replacing parts, then the CAD model can be adapted to specific user requirements, but the process becomes very time consuming due to large number of changes and complex dependencies between changes
Solution Approach 1:
The system transforms the customization process from manual dimension changing to automated parameter value assignment. The configuration engine automatically assigns values to parameters (dimensions, part selections) based on customer requirements, eliminating the need for manual modification of each dimension and reducing customization time while maintaining adaptability.
Solution Approach 2:
The patent replaces the mechanical manual customization process with an automated computational system. Instead of manually changing dimensions and parts, the system uses a configuration engine that processes customer requirements and automatically generates the customized CAD model, substituting human manual operations with automated computational logic.
2Extent of automation
If built-in programming tools are used to automate customization, then the customization process is automated, but it becomes difficult to define procedures that always comply with dependencies between changes
Solution Approach 1:
The system incorporates a constraint satisfaction mechanism that continuously checks for compliance with dependencies between parameter changes. The configuration engine receives customer requirements, processes them through constraint rules that define dependencies, and only assigns values that satisfy all constraints, providing feedback to ensure reliability and compliance.
Solution Approach 2:
The patent introduces a constraint satisfaction layer as an intermediary between customer requirements and CAD model changes. This intermediary layer processes requirements through a set of constraints that define valid combinations, acting as a mediator that ensures dependency compliance before applying changes to the CAD model.
3Adaptability or versatility
If a large number of changes are made to customize the CAD model, then the model can be fully adapted to requirements, but the risk increases that the resulting model cannot be assembled or will not work properly
Solution Approach 1:
The system performs preliminary validation by processing customer requirements through constraint satisfaction before actually applying changes to the CAD model. The configuration engine pre-checks for validity and only proceeds with changes that are guaranteed to result in a valid, assembleable model, preventing invalid combinations from being applied.
Solution Approach 2:
The patent uses a virtual configuration space as a disposable intermediate layer. Instead of directly modifying the CAD model with risky changes, the system creates a virtual representation of the configuration, validates it against constraints, and only then translates to actual model changes, isolating the risk in a disposable virtual layer.
Data Source
AI summary
A CAD model customized, which represents a mechanical design of an artifact comprising a set of parts with respective dimensions. A configuration model defines an exhaustive range of ways to customize the CAD model by changing a subset the dimensions. A model translation module is arranged to convert the configuration model into: (i) a CSP representing all possible customizations defined by the configuration model, the CSP is defined by: (a) set of integer variables, wherein each variable may attain a finite number of different values, and (b) a set of constraints restricting which variable values that are simultaneously possible for the variables, (ii) a set of CSP variable-dimension pairs, and (iii) a set of CSP variable-parameter pairs. A configuration engine is arranged to: calculate a solution to the CSP, which solution is optimal with respect to a value assigned to each variable in the CSP relative to a predefined optimizing criterion, and assign a parameter value for each CSP variable-parameter pair, the allocated parameter value corresponding to the value assigned to the CSP variable in the optimal solution. A CAD interface is arranged to assign a dimension in the CAD model for each CSP variable-dimension pair, where the assigned dimension corresponds to a value assigned to the CSP variable in the optimal solution.