Abstract
Incorporating resilience in design is important for the long-term viability of complex engineered systems. Complex aerospace systems, for example, must ensure safety in the event of hazards resulting from part failures and external circumstances while maintaining efficient operations. Traditionally, mitigating hazards in early design has involved experts manually creating hazard analyses in a time-consuming process that hinders one’s ability to compare designs. Furthermore, as opposed to reliability-based design, resilience-based design requires using models to determine the dynamic effects of faults to compare recovery schemes. Models also provide design opportunities, since models can be parameterized and optimized and because the resulting hazard analyses can be updated iteratively. While many theoretical frameworks have been presented for early hazard assessment, most currently-available modelling tools are meant for the later stages of design. Given the wide adoption of Python in the broader research community, there is an opportunity to create an environment for researchers to study the resilience of different PHM technologies in the early phases of design. This paper describes fmdtools, an attempt to realize this opportunity with a set of modules which may be used to construct different design models, simulate system behaviors over a set of fault scenarios and analyze the resilience of the resulting simulation results. This approach is demonstrated in the hazard analysis and architecture design of a multi-rotor drone, showing how the toolkit enables a large number of analyses to be performed on a relatively simple model as it progresses through the early design process.
Highlights
Resilience, the ability to prevent and mitigate hazards, is a key consideration in the design of complex engineered systems (Cottam et al, 2019; Yodo & Wang, 2016a)
One creates a functional decomposition of the tasks the system is to perform, finds solution principles to achieve those tasks, and synthesizes those principles into a realized design concept. These design processes are supported by static failure-logic functional hazard assessment and network models, dynamic behavioral models, and hierarchical fault models, respectively
A number of modelling formalisms have been developed to assess the risk of hazards in engineered systems, including fault trees, bayesian networks, and stochastic petri nets (Chemweno, Pintelon, Muchiri, & Van Horenbeek, 2018)
Summary
Resilience, the ability to prevent and mitigate hazards, is a key consideration in the design of complex engineered systems (Cottam et al, 2019; Yodo & Wang, 2016a). The main contribution of this work is the development and study of a computational environment for performing resilience-based hazard assessment early in the design process This paper presents this contribution by first describing the fmdtools project, an open-source python-based toolkit for the high-level modelling, simulation, and analysis of resilience. It seeks to enable the practical application of early model-based functional hazard assessment frameworks while explicitly enabling the consideration of resilience An approach like this has a number of potential applications to considering PHM in aerospace systems by supporting cost-benefit analysis (e.g., (Holzel, Schilling, & Gollnick, 2014)), which can used to allocate resources for PHM (Youn et al, 2011) and assess design alternatives (e.g. prevention or recovery schemes) (Hulse, Hoyle, Goebel, & Tumer, 2019b).
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