Doctoral Dissertations
Keywords and Phrases
Clustering; Interface Analysis; Risk Assessment
Abstract
“Interface analysis and integration risk assessment for a large-scale, complex system is a difficult systems engineering task, but critical to the success of engineering systems with extraordinary capabilities. When dealing with large-scale systems there is little time for data gathering and often the analysis can be overwhelmed by unknowns and sometimes important factors are not measurable because of the complexities of the interconnections within the system. This research examines the significance of interface analysis and management, identifies weaknesses in literature on risk assessment for a complex system, and exploits the benefits of soft computing approaches in the interface analysis in a complex system and in the risk assessment of system integration readiness. The research aims to address some of the interface analysis challenges in a large-scale system development lifecycle such as the ones often experienced in aircraft development. The resulting product from this research is contributed to systems engineering by providing an easy-to-use interface assessment and methodology for a trained systems engineer to break the system into communities of dense interfaces and determine the integration readiness and risks based on those communities. As a proof of concept this methodology is applied on a power seat system in a commercial aircraft with data from the Critical Design Review”--Abstract, page iv.
Advisor(s)
Corns, Steven
Committee Member(s)
Dagli, Cihan H., 1949-
Kwasa, Benjamin J.
Long, Suzanna, 1961-
Low, Lesley
Pernicka, Henry J.
Department(s)
Engineering Management and Systems Engineering
Degree Name
Ph. D. in Systems Engineering
Publisher
Missouri University of Science and Technology
Publication Date
Summer 2021
Journal article titles appearing in thesis/dissertation
- SOS explorer application with fuzzy-genetic algorithms to assess an enterprise architecture -- A healthcare case study
- A cluster-based framework for interface analysis in large-scale aerospace systems
- Fuzzy-risk assessment methodology for large-scale systems
Pagination
xii, 89 pages
Note about bibliography
Includes bibliographic references.
Rights
© 2021 Josh Henry Goldschmid, All rights reserved.
Document Type
Dissertation - Open Access
File Type
text
Language
English
Thesis Number
T 11895
Electronic OCLC #
1286686958
Recommended Citation
Goldschmid, Josh Henry, "A fuzzy clustering methodology to analyze interfaces and assess integration risks in large-scale systems" (2021). Doctoral Dissertations. 3000.
https://scholarsmine.mst.edu/doctoral_dissertations/3000