Modular Product Design Explorer for Feasible Configuration Analysis
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing design systems struggle with the time-consuming and inefficient process of identifying valid combinations of modular components and subsystems for product development, lacking the ability to analyze these combinations and incorporate additional components during the design process.
Innovation Solution
A design explorer system that utilizes a graphical user interface to define application characteristics, identify feasible product configurations, perform simulations, and analyze these configurations to reduce the number of practical design permutations, incorporating scalable cloud-based infrastructure for enhanced scalability and reliability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual identification of component combinations is used, then design flexibility is maintained, but time consumption and inefficiency increase significantly
Solution Approach 1:
The patent replaces manual mechanical design processes with an automated computer-based system that uses algorithms to identify valid component combinations. The system automatically processes design requirements, queries component databases, and generates feasible configurations without manual intervention, dramatically reducing design time while maintaining flexibility through programmable constraints and rules.
Solution Approach 2:
The design system performs self-service by automatically identifying valid component combinations without requiring manual analysis. The computer-based system independently queries databases, applies design rules, evaluates compatibility, and generates multiple feasible configurations, enabling the system to serve its own design needs without external human intervention for each design task.
2Reliability
If comprehensive simulation and analysis are performed on all possible configurations, then design reliability improves, but computational resources and time requirements increase
Solution Approach 1:
The system performs preliminary filtering and pre-analysis of component combinations before conducting full simulations. By first identifying feasible configurations based on basic compatibility rules and constraints, the system narrows down the search space to only those configurations warranting detailed simulation and analysis, thereby reducing overall computational resource requirements while maintaining design reliability.
Solution Approach 2:
The system applies a tiered analysis approach where not all configurations receive full simulation treatment. Instead, it performs partial analysis on feasible configurations and reserves comprehensive simulation for selected candidates, optimizing the balance between validation thoroughness and computational resource consumption by applying analysis depth proportional to configuration promise.
Data Source
AI summary
Initial information associated with a product to be designed is obtained, where at least some initial information identifies an intended application. Multiple features associated with the product are identified. For each feature, one or more feature options acceptable for use in the application are identified, and one or more components or subsystems associated with the acceptable option(s) are identified. At least some identified components or subsystems are reusable in multiple products. Feasible configurations are generated based on the identified components or subsystems. Each feasible configuration represents a potential design for the product and is acceptable for use in the application. One or more simulations or analyses associated with each feasible configuration are performed, where at least one simulation or analysis estimates performance of each feasible configuration. A user interface is generated that identifies one or more feasible configurations and results associated with the simulations or analyses or information based thereon.