How does the optimization of multi-attribute design in mechanical engineering consider trade-offs among conflicting performance metrics and integrate interdisciplinary knowledge?

Optimization of multi-attribute design in mechanical engineering involves balancing conflicting performance metrics through techniques like multi-objective optimization, Pareto analysis, and weighted sum methods. Interdisciplinary knowledge from materials science, control systems, economics, and human factors is integrated to achieve an optimal design that meets diverse criteria.