Performance-Based System Configuration for Faster Simulation Setup
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Solution Overview
Problem
The current systems engineering process is time-consuming and inefficient due to the manual and iterative nature of designing systems and subsystems, requiring numerous simulation setups and operations to achieve performance objectives, with complex simulations taking days to complete and often resulting in extensive redesign cycles.
Innovation Solution
A performance-based system design configuration generation system that includes an explainable recommendation module to automatically determine optimal system component selections for simulation setups, predicting performance scores for each component and ranking system configurations to reduce the number of simulation iterations by identifying performance-constraining components.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual simulation setups and simulation operations are performed repeatedly to achieve performance objectives, then system performance can be optimized, but time consumption increases significantly
Solution Approach 1:
The patent applies preliminary action by performing performance estimation of system elements before conducting full simulation cycles. The system calculates performance metrics for each system element in advance, allowing designers to identify the most influential elements prior to simulation. This preliminary assessment guides the selection of candidate system designs, reducing the number of iterative simulation cycles needed to achieve performance objectives.
2Measurement precision
If complex systems are modeled for simulation to predict performance of candidate designs, then performance prediction accuracy is improved, but simulation completion time extends to days
Solution Approach 1:
The patent applies segmentation by dividing the complex system into individual system elements and evaluating their performance contributions separately. The system models each system element independently and calculates performance metrics for each component. This segmentation allows for efficient performance estimation without requiring complete simulation of the entire complex system, thereby reducing simulation time while maintaining prediction accuracy for the overall system performance.
3Reliability
If multiple iterations of simulation setup, simulation, and redesign are performed, then optimal system design is achieved, but productivity decreases due to extensive redesign cycles
Solution Approach 1:
The patent applies feedback by implementing a performance estimation mechanism that provides immediate feedback on system element performance before full simulation. The system evaluates performance metrics for each system element and uses this feedback to guide design decisions. This feedback loop allows designers to identify performance-constraining elements early and make informed redesign decisions, reducing the number of iterative cycles required to achieve optimal system design.
4Loss of information
If manual determination of system performance for each system element is performed prior to simulation, then performance understanding is improved, but time consumption increases
Solution Approach 1:
The patent applies self-service by implementing an automated performance estimation system that calculates performance metrics for system elements without requiring manual determination. The system automatically models system elements, evaluates their performance contributions, and generates performance reports. This automated self-service mechanism provides comprehensive performance understanding while eliminating the time-consuming manual analysis process.
Data Source
AI summary
System for performance-based design space composition in engineering systems includes design configuration module, explainable recommendation module and user interface module. A list of one or more system configurations is generated, each system configuration having a unique set of components that satisfy system goals and system requirements. For each system configuration, system performance values are determined based on performance enabled by each system component. A design dashboard presents the system configurations in rank order and the system performance value for each of the system configuration components.