Document Type
Article
Publication Date
2025
DOI
10.3390/designs9010019
Publication Title
Designs
Volume
9
Issue
1
Pages
19 (1-23)
Abstract
The objective of this research is to incorporate system failure into a robust design formation and solution process. The system failure referred to here will be built using fault tree analysis (FTA), which will take all lower-level failure events into consideration. Two examples are investigated here. One will directly treat the probabilities of the basis events as design variables, The other will be formulated in five different models: deterministic design optimization, the reliability index-based, the “and” gate-based, the “or” gate-based and the “inhibit” gate-based robust design. Their corresponding optimization solutions will be compared with each other. The post-optimality analysis of each of the design optimization models is also investigated to evaluate the effect of the change in the problem parameters to the optimal solution. These problem parameters are deterministic and not treated as design variables in the optimization formulation. This research paves the way for much more broad applications of robust design optimization in the future by incorporating more advanced FTA models into the optimization solution process, such as fuzzy sets and dynamic FTA.
Rights
© 2025 by the authors.
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution 4.0 International (CC BY 4.0) License.
Data Availability
Data availability statement: "The original contributions presented in this study are included in the article. Further inquiries can be directed to the corresponding author(s)."
Original Publication Citation
DeGroff, J., & Hou, G. J. (2025). Fault tree analysis for robust design. Designs, 9(1), 1-23, Article 19. https://doi.org/10.3390/designs9010019
ORCID
0000-0002-7352-1099 (Hou)
Repository Citation
DeGroff, Jonathan and Hou, Gene Jean-Win, "Fault Tree Analysis for Robust Design" (2025). Mechanical & Aerospace Engineering Faculty Publications. 171.
https://digitalcommons.odu.edu/mae_fac_pubs/171
Included in
Mechanical Engineering Commons, Probability Commons, Risk Analysis Commons, Systems Engineering Commons