Substrate Fastening Point Layout for Vibration-Resistant PCB Mounting
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Solution Overview
Problem
Existing methods for designing fastening points on substrates, such as circuit boards in power control units, face inefficiencies in determining optimal combinations due to exponential combination growth with increasing candidates, leading to prolonged computation times and inability to ensure vibration resistance without symmetric substrate structures.
Innovation Solution
A design device utilizing an Ising machine to convert a regression model into an Ising model, selecting fastening points from candidates to minimize an evaluation value, ensuring vibration resistance by maintaining a natural frequency above a threshold and reducing the number of fastening points.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the number of fastening point candidates increases to improve design flexibility, then the design adaptability improves, but the computation time increases exponentially
Solution Approach 1:
The patent replaces traditional computational optimization methods with an Ising machine that uses physical quantum effects to solve the optimization problem. The Ising machine maps the fastening point optimization problem to an Ising model where binary variables represent candidate selections, and the system naturally finds the optimal configuration through quantum tunneling and thermal annealing processes, avoiding exponential computation time growth.
Solution Approach 2:
The patent transforms the design problem by changing parameters from continuous coordinates to discrete binary variables representing candidate fastening points. This discretization allows the problem to be mapped to an Ising model framework, where the optimization landscape can be efficiently explored using quantum annealing, thus managing computation time even with many candidates.
2Measurement precision
If traditional optimization methods are used to evaluate all combinations, then the solution accuracy improves, but the productivity decreases
Solution Approach 1:
The patent substitutes exhaustive computational evaluation with an Ising machine that physically evolves to find optimal solutions. The machine uses quantum annealing to naturally converge to low-energy states corresponding to optimal fastening point combinations, providing accurate solutions without evaluating all possible combinations, thus maintaining precision while dramatically improving productivity.
3Reliability
If the distance between fasteners is reduced to improve vibration resistance, then the reliability improves, but the device complexity increases
Solution Approach 1:
The patent applies local quality by optimizing fastening point positions individually based on substrate characteristics, vibration modes, and local structural properties rather than applying uniform spacing rules. The Ising model evaluation function incorporates local stiffness, mass distribution, and vibration mode shapes to determine optimal positions, achieving vibration resistance without requiring uniformly reduced distances that would increase complexity.
Data Source
AI summary
A combination of fastening points is obtained by repeating following steps as an optimum value when an evaluation method of a physical quantity acting on a substrate is specified. The steps include: obtaining the physical quantity according to the combination of fastening points; generating a regression model expressing one fastening point candidate by a binary variable; converting the regression model into an Ising model based on the evaluation method; and determining the combination of fastening points by selecting one of fastening points from the fastening point candidate positions using an Ising machine so as to minimize an evaluation value of the Ising model.