MN
M. Nikitin
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With growing demand for air transportation, it is crucial to improve the efficiency of aircraft systems design. A key area of focus is the implementation of manufacturability considerations into the design process at early stages. This could be done by integrating manufacturability analysis modules into an MDAO workflow, however, each production method places unique requirements on the system. This study investigates the impact of considering manufacturing in the initial design phase, using a novel dynamic MDAO workflow that is capable of changing its analysis disciplines, design variables and constraints based on the current design point within an optimisation. This methodology was tested on a wing rib design case, with two production methods available: machining for metal ribs and stamp-forming for composite ribs. Integrating DFM analyses into the design study improved the trustworthiness of optimum results, removing non-manufacturable rib designs. Dynamic MDAO workflows yielded faster multi-objective optimizations and efficient handling of correlated objectives compared to conventional static workflows while providing similar results.
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With growing demand for air transportation, it is crucial to improve the efficiency of aircraft systems design. A key area of focus is the implementation of manufacturability considerations into the design process at early stages. This could be done by integrating manufacturability analysis modules into an MDAO workflow, however, each production method places unique requirements on the system. This study investigates the impact of considering manufacturing in the initial design phase, using a novel dynamic MDAO workflow that is capable of changing its analysis disciplines, design variables and constraints based on the current design point within an optimisation. This methodology was tested on a wing rib design case, with two production methods available: machining for metal ribs and stamp-forming for composite ribs. Integrating DFM analyses into the design study improved the trustworthiness of optimum results, removing non-manufacturable rib designs. Dynamic MDAO workflows yielded faster multi-objective optimizations and efficient handling of correlated objectives compared to conventional static workflows while providing similar results.