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Requirements are often fluid in the early stages of engineering design. To address this challenge, we adopt a set-based approach for considering and exploring several alternatives so that commitment to a single design can be delayed until requirements are settled. We present a method to obtain scalable optimal design solutions that can satisfy changing requirements through remanufacturing. We first use design optimization to obtain a set of parametric optimal designs, which is then reduced to scalable optimal designs by observing a set of transition rules for the manufacturing process used.
However, requirements may also change over the lifetime of engineering systems and their components. In the aerospace industry, for example, systems can be in operation for more than 30 years. To mitigate the impact of such changes in requirements, so-called design margins are introduced, which usually lead to overdesign. We present a design optimization method for minimizing overdesign subject to reliability constraints by exploiting additive remanufacturing. The proposed method is used to obtain a set of design decisions for different changing requirement scenarios.
We demonstrate both methods using the example of an aeroengine turbine rear structure, where changes in the temperature loads are met by depositing different types of stiffeners on the outer casing. Results are visualized in a tradespace that enables the comparison among sets of optimal, flexible, and robust designs, which offers valuable quantitative decision-making support to design engineers.
The work presented in this seminar is based on the research of the speaker’s former PhD student Khalil Al-Handawi. Part of it has been published in K. Al-Handawi, P. Andersson, M. Panarotto, O. Isaksson and M. Kokkolaras, 2020. "Scalable Set-based Design Optimization and Remanufacturing for Meeting Changing Requirements." ASME Journal of Mechanical Design, 143(2):021702, DOI: 10.1115/1.4047908.