Modeling of function failure propagation across uncoupled systems

Arlitt

2019

Systems Engineering

Self Cite

System of interest (SoI) failures can sometimes be traced to an unexpected behavior occurring within another system that is a member of the system of systems (SoS) with the SoI. This article presents a method for use when designing an SoI that helps to analyze an SoS for unexpected behaviors from existing SoS members during the SoI's conceptual functional modeling phase of system architecture. The concept of irrationality initiators—unanticipated or unexpected failure flows emitted from one system that adversely impact an SoI, which appear to be impossible or irrational to engineers developing the new system—is introduced and implemented in a quantitative risk analysis method. The method is implemented in the failure flow identification and propagation framework to yield a probability distribution of failure paths through an SoI in the SoS. An example of a network of autonomous vehicles operating in a partially denied environment is presented to demonstrate the method. The method presented in this paper allows practitioners to more easily identify potential failure paths and prioritize fixing vulnerabilities in an SoI during functional modeling when significant changes can still be made with minimal impact to cost and schedule.

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Background and Related Workmentioning

confidence: 99%

See 3 more Smart Citations

A method of identifying and analyzing irrational system behavior in a system of systems

Bossuyt

Arlitt

2019

Systems Engineering

Self Cite

A Graph Theory Approach to Functional Failure Propagation in Early Complex Cyber‐Physical Systems (CCPSs)

INCOSE International Symp

Papakonstantinou

Giammarco³

et al. 2017

This paper presents a framework to quantify failure propagation potential for complex, cyber‐physical systems (CCPSs) during the conceptual stages of design. This method is referred to as the Function Failure Propagation Potential Methodology (FFPPM). This research is motivated by recent trends in engineering design. As systems become increasingly connected, an open area of research for CCPSs is to move reliability and failure assessments earlier in the engineering design process. This allows practitioners to make decisions at a point in the design process where the decision has a high impact and a low cost. Standard methods are limited by the availability of data and often rely on detailed representations of the system. As such, they have not addressed failure propagation in the functional design prior to selecting candidate architectures. To develop the metrics, graph theory is used to model and quantify the connectedness of the functional block diagram (FBD). These metrics quantify (1) the summation of the reachability matrix and (2) the summation of the number of paths between nodes (functions within system models) i and j for all i and j. From a practical standpoint, these metrics quantify the reachability between functions in the graph and the number of paths between functions defines the failure propagation potential of that failure. The unique contribution of this research is to quantify failure propagation potential during conceptual design prior to selecting candidate architectures. The goal of these metrics is to produce derived system requirements, based on an analysis, that focus on minimizing the impact of failures.

A graph theory approach to predicting functional failure propagation during conceptual systems design

Papakonstantinou

Giammarco

et al. 2021

Systems Engineering

Self Cite

An open area of research for complex, cyber‐physical systems is how to adequately support decision making using reliability and failure data early in the systems engineering process. Having meaningful reliability and failure data available early offers information to decision makers at a point in the design process where decisions have a high impact to cost ratio. When applied to conceptual system design, widely used methods such as probabilistic risk analysis (PRA) and failure modes effects and criticality analysis (FMECA) are limited by the availability of data and often rely on detailed representations of the system. Further, existing methods for system reliability and failure methods have not addressed failure propagation in conceptual system design prior to selecting candidate architectures. Consideration given to failure propagation primarily focuses on the basic representation where failures propagate forward. In order to address the shortcomings of existing reliability and failure methods, this paper presents the function failure propagation potential methodology (FFPPM) to formalize the types of failure propagation and quantify failure propagation potential for complex, cyber‐physical systems during the conceptual stage of system design. Graph theory is leveraged to model and quantify the connectedness of the functional block diagram (FBD) to develop the metrics used in FFPPM. The FFPPM metrics include (i) the summation of the reachability matrix, (ii) the summation of the number of paths between nodes (i.e., functions) i and j for all i and j, and (iii) the degree and degree distribution. In plain English, these metrics quantify the reachability between functions in the graph, the number of paths between functions, and the connectedness of each node. The FFPPM metrics can then be used to make candidate architecture selection decisions and be used as early indicators for risk. The unique contribution of this research is to quantify failure propagation potential during conceptual system design of complex, cyber‐physical systems prior to selecting candidate architectures. FFPPM has been demonstrated using the example of an emergency core cooling system (ECCS) system in a pressurized water reactor (PWR).