Towards Using Functional Decomposition and Ensembles of Surrogate Models for Technology Selection in System Level Design
DS 130: Proceedings of NordDesign 2024, Reykjavik, Iceland, 12th - 14th August 2024
Year: 2024
Editor: Malmqvist, J.; Candi, M.; Saemundsson, R. J.; Bystrom, F. and Isaksson, O.
Author: Arjomandi Rad, Mohammad; Panarotto, Massimo; Malmqvist, Johan; Martinsson Bonde, Julian; Warmefjord, Kristina; Isaksson, Ola
Series: NordDESIGN
Institution: Chalmers University of Technology, Sweden
Page(s): 421-430
DOI number: 10.35199/NORDDESIGN2024.45
ISBN: 978-1-912254-21-7
Abstract
Technology selection in complex system design is challenged by extended design evaluations and complicated design cycles. Utilizing function-mean modeling and the ensemble of surrogate model techniques, the paper reveals how low-level input parameters in the design can be instrumental in predicting higher-level performance outcomes. A case study from the space industry is used to show surrogates trained on system level and component levels in a flow management system are generalizable. Exploring the methods for aggregating surrogates demonstrates how such an ensemble can be built.
Keywords: Data Driven Design, Conceptual Design, Functional Modelling, Product Architecture, Innovation Management