Conceptual Aircraft Design for Producibility

In modern aircraft design, though the conceptual stage still relies heavily on historical data and expert consultation, techniques in multidisciplinary design optimization (MDO) have been increasingly employed to explore the design space and inform vehicle-level design decisions. In the MDO approach, the major system-level design parameters are varied in order to analyze and uncover optimal vehicle configurations to maximize performance or other metrics. This process typically includes analyses from a range of disciplines, such as aerodynamics, structures, and mission analysis; however, producibility is rarely incorporated in a rigorous way, owing in large part to challenges related to model fidelity and the many non-engineering factors which influence producibility. In the present work, methods to assess producibility in the context of early design optimization processes are investigated, with the source of producibility information broken down into five broad categories: engineering intuition, manufacturing data, vehicle-level historical data, physics-based indicators, and manufacturing rules/methods. From these data sources, a series of methods is derived – including directed intuition, historical parameter similarity, and finite element analysis (FEA)-based indicators – that can be employed to create individual risk flags targeting specific producibility concerns, which are then combined to represent the overall producibility risk for a conceptual aircraft design. With this approach to computing manufacturing-related risk metrics, an integrated method for MDO with producibility is proposed here, and an example design space exploration is then presented. By incorporating such assessments in a rigorous way in early concept development, the producibility of structural designs may be improved to ultimately yield reduced development costs, fewer schedule delays due to late engineering changes, and enhanced aircraft performance.