Evolution is a key distinguishing trait of Systems-of-Systems (SoS) that introduces a layer of complexity in analysis that is not present when considering static systems. Some SoS analysis tools exist to determine and evaluate the evolution of an SoS, while other tools are better suited for studying individual instances of an SoS. System Operational Dependency Analysis (SODA) is one such method that has been used previously to study static SoS networks. SODA that has been proven effective in investigating the impacts of partial system disruptions and would benefit from a framework to apply SODA to evolving SoS. This thesis provides an approach to modeling evolving SoS in SODA and presents new data visualization methods to highlight the effects of changing network configurations across evolutionary phases. These visualization enhancements include Failure Impact Range sequence plots to show effects of deterministic system disruptions on capabilities of interest across evolutionary phases, as well as Stochastic Impact plots to quantify the impact of disruptions in particular systems in the context of the probabilistic operating statuses assigned to each system. Integration of SODA and the related method of System Developmental Dependency Analysis (SDDA) is explored to model how operational disruptions and developmental delays might interact and compound during the evolution of an SoS. The SODA enhancements provide decision makers with new information that can be used to explore design and implementation tradeoffs in an evolving SoS under budget and scheduling constraints. These ideas are demonstrated through a case study based on NASA's Artemis program to return humans to the Moon in commercially-built Human Landing Systems (HLS). The HLS concepts proposed to NASA consist of multiple elements that provide distinct capabilities in different phases of the lunar mission, and therefore can be considered an evolving SoS architecture. The operational dependencies of two HLS concepts are modeled across a four-phase lunar landing mission and results are generated using the new visualization methods to highlight the impacts of changing SoS configuration on the performance of key mission capabilities. The development timeline of the first three planned Artemis lunar landing missions is analyzed with SDDA and integrated with SODA results from one HLS concept to explore how developmental delays impact the likelihood of HLS mission completion and how operational failures requiring system redesign impact the program schedule. Connections between SDDA and Integrated Master Schedules (IMS) are discussed to show how SDDA results can be useful in a context more familiar to program managers.
| Identifer | oai:union.ndltd.org:purdue.edu/oai:figshare.com:article/12743591 |
| Date | 31 July 2020 |
| Creators | Christopher T Brand (9189131) |
| Source Sets | Purdue University |
| Detected Language | English |
| Type | Text, Thesis |
| Rights | CC BY 4.0 |
| Relation | https://figshare.com/articles/thesis/System_Dependency_Analysis_for_Evolving_Space_Exploration_System_of_Systems/12743591 |
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