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A Study on Multi-objective Design Optimization Models and Algorithms for Reliability-aware PCB Design

printed circuit board,multi-objective optimization model,NSGA-Ⅱ genetic algorithm,Lagrange relaxation

Special Sessions > SSL 07 Belief reliability theory and its application in smart operation and maintenance

Modern electronic devices demand ever-smaller, higher-performance printed circuit boards (PCBs), yet miniaturization and complex service environments exacerbate failure risks. We first identify key failure modes under real-world conditions, build life-prediction models via multivariate nonlinear regression, and quantify reliability through uncertainty analysis. Next, we set optimization objectives and constraints based on failure-mode frequency, severity, and coupling, then formulate the coupled multi-objective model. An enhanced NSGA-II—using Lagrange relaxation to decouple constraints—expands the search space and improves solution diversity. Validation on a model-aircraft drive-control PCB demonstrates the method's effectiveness in balancing performance and reliability.