Concurrent Value-Driven Optimization Problems Addressing Aircraft Design, Manufacturing, and Supply Chain

In the last decades, several studies show how the concurrent evaluation of manufacturing and supply chain in the early design phase brings significant advantages to industries. In this frame, a value-driven methodology has been developed and applied in the aeronautical context to identify the best solution when considering design, manufacturing, and supply chain criteria at the same time. This study aims at including optimization algorithms in the methodology to face a new challenge: the identification of solutions simultaneously optimizing manufacturing, design, and supply chain variables. To achieve this objective, collaborative optimization problems are presented in this research activity in three multidisciplinary design and optimization (MDO) cases, which integrate domains first in pairs and then together. Shortly, MDO case I identifies a Pareto front of optimal supply chain combinations producing aircraft components among millions of possibilities after several hours of execution; MDO case II shows the optimal aircraft configuration made by considering hundreds of combinations of materials and processes in less than one hour; MDO case III reaches the Pareto front in a half-day considering millions of choices of materials, processes, and enterprises.