Iterative Design Synthesis Using Real-World Sensor Feedback
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Solution Overview
Problem
Conventional design synthesis methods provide limited feedback on the actual performance of fabricated products, relying on qualitative feedback from designers' experience and intuition, which is of limited value for directing further design iterations.
Innovation Solution
A computer-implemented method that incorporates quantitative usage feedback from sensors installed on products during real-world usage conditions to generate design solutions, translating sensor data into design problem statements and using topology and beam-based optimization algorithms to produce improved design iterations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional design synthesis methods are used, then design solutions can be generated efficiently, but limited feedback is provided on actual product performance
Solution Approach 1:
The patent implements a feedback mechanism where sensors on physical products collect usage data (forces, accelerations, temperatures) and feed this information back to the design synthesis system. This closed-loop feedback enables the system to learn from actual product performance and refine subsequent design iterations, directly addressing the information loss problem while maintaining design efficiency through automated processing
2Ease of operation
If qualitative feedback from designer experience is used, then design iterations can proceed, but the feedback value is limited
Solution Approach 1:
The patent replaces subjective qualitative feedback from designer experience with objective quantitative sensor data. Sensors measure actual physical parameters (forces, accelerations, temperatures) during product usage, providing precise measurement data that substitutes for imprecise human intuition while maintaining ease of operation through automated data collection and analysis
3Manufacturing precision
If real-world usage data is collected, then design accuracy improves, but data processing complexity increases
Solution Approach 1:
The patent introduces an intermediary computational layer that processes raw sensor data into meaningful design parameters. This intermediary system translates complex multi-sensor data (forces, accelerations, temperatures) into actionable design feedback, improving design accuracy while managing processing complexity through structured data pipelines and automated analysis algorithms
Data Source
AI summary
An iterative design environment performs an iterative design process of a product by implementing usage feedback of the product when utilized under real-world conditions. Sensors are installed on the physical product and collect data about the behavior of the product under real-world conditions. The sensor data comprise usage feedback implemented to inform and produce a design problem statement and one or more design solutions. The sensor data is received by a problem statement engine to produce a problem statement based, at least in part, on the sensor data. A design engine then produces one or more design solutions for the problem statement and one of the design solutions is fabricated to produce a new physical product. Sensors are then installed onto the new physical product and the iterative design process may be performed again. The iterative design process may be performed multiple times until a satisfactory physical product is achieved.