Reliability-based bottom-up manufacturing cost optimisation for composite aircraft structures

Abstract

A novel methodology is presented for the reliability-based manufacturing cost optimisation of composite aircraft structures. A comprehensive bottom-up costing approach is employed, enabling precise manufacturing cost estimation in terms of material, machine, labour, tooling, and indirect costs. This approach splits the manufacturing process into many individual activities, which can be combined in many different ways, allowing the proposed optimisation methodology to be applied to a wide range of composite aircraft structures. A genetic algorithm (GA) is coupled with a deep neural network (DNN) to efficiently determine the optimal composite ply stacking sequence for every part of an assembled structure. A numerical example featuring a composite-stiffened aircraft fuselage panel is investigated. The reliability of the panel is measured in terms of its buckling resistance, and its manufacturing cost is estimated based on the individual costs of over 20 activities. The labour times for each activity were estimated based on data collected from an aerospace company specialising in the manufacture of advanced composite aircraft structures. Results indicate that material, machine, labour, and tool costs can vary significantly depending on the level of structural reliability required, demonstrating the importance of accounting for non-material costs when designing composite aircraft structures.