Theoretical Framework for Risk Factors and Safety Factors in Systems Modeling Language
Johnson, DeAndre, Systems Engineering - School of Engineering and Applied Science, University of Virginia
Lambert, James, EN-SIE, University of Virginia
This dissertation proposes a framework integrating risk management into the model-based systems engineering (MBSE) process using Systems Modeling Language (SysML). The framework describes the identification and assessment of risks while capturing comprehensive system descriptions, thus improving communication and decision-making among stakeholders. The proposed method involves designing a risk management approach that tracks risk and safety factors through SysML diagrams. These diagrams identify risk and safety factors for given systems, prioritizing system initiatives using a multi-criteria impact analysis to explore disruptions caused by emergent and future conditions. The innovative aspect of this study lies in the theoretical development of a risk management framework for SysML, which includes risk sources and safety factors, and its practical application across two examples: the supply chain for sustainable aviation fuels (SAF) and the system development of a smart parking lot systems. Applying the risk-induced framework to the SAF supply chain addresses the intricacies of blending operations attached to airport infrastructure. The methodology is subsequently extended to a smart parking lot architecture, demonstrating its adaptability and effectiveness in varied engineering scenarios. These case studies highlight the framework's ability to provide a comprehensive approach to risk management in large-scale systems and underscore its versatility in adapting to different engineering contexts. The study's findings emphasize the benefits of improved communication among stakeholders and the traceability of risk sources and controls within the SysML framework. Improved communication and semantic traceability are foundational pillars for informed decision-making, proactive risk mitigation, and the success of complex engineering projects. This research provides stakeholders with an understanding of the interplay between technical risks and administrative considerations, contributing to more effective risk management strategies and sustainable engineering solutions in diverse contexts.
PHD (Doctor of Philosophy)
Risk Management, Model-Based Systems Engineering, Multi-Criteria Decision Analysis
English
2024/07/26