7 research outputs found
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Resiliency analysis for complex engineered system design
Resilience is a key driver in the design of systems that must operate in an uncertain operating environment, and is a key metric to assess the capacity for systems to perform within the specified performance envelop despite disturbances to their operating environment. This paper describes a graph spectral approach to calculate the resilience of complex engineered systems. The resilience of the design architecture of complex engineered systems is deduced from graph spectra. This is calculated from adjacency matrix representations of the physical connections between components in complex engineered systems. Furthermore, we propose a new method to identify the most vulnerable components in the design and design architectures that are robust to transmission of failures. Non-linear dynamical system (NLDS) and epidemic spreading models are used to compare the failure propagation mean time transformation. Using these metrics, we present a case study based on the Advanced Diagnostics and Prognostics Testbed (ADAPT), which is an Electrical Power System (EPS) developed at NASA Ames as a subsystem for the Ramp System of an Infantry Fighting Vehicle (IFV).Keywords: Complex System Design, Failure Density, Failure Propagation, Robust Desig
Network-based metrics for assessment of naval distributed system architectures
The architecture of a system is generally established at the end of the conceptual design phase where sixty to eighty percent of the lifetime system costs are committed. The architecture influences the system’s complexity, integrality, modularity and robustness. However, such properties of system architecture are not typically analytically evaluated early on during the conceptual process. System architectures are defined using qualitative experience, and the early stage decisions are subject to the judgement of stakeholders. This article suggests a set of network-based metrics that can potentially function as early evaluation indicators to assess complexity, integrality, modularity and robustness of distributed system architectures during conceptual design. A new robustness metric is proposed that assesses the ability of architecture to support a level functional requirement of the system after a disruption. The new robustness metric is evaluated by an electrical simulation software (MATPOWER). A ship vulnerability assessment software (SURVIVE) was used to find potential disruptive events. Two technical case studies examining existing naval distributed system architectures are elaborated. Conclusions on the network modelling and metrics as early aids to assess system architectures and to choose among alternatives during the conceptual decision phase are presented
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The Effects of Modularity on Cascading Failures in Complex Engineering Systems
To design engineering systems that have improved reliability, it is important to understand what kind of system faults they will be susceptible to. Mitigation strategies are important to ensuring the performance of these engineering systems. Understanding how the modularity of complex engineering systems affects the risk of devastating failures such as cascading failures can help enable engineers to implement strategies in the design phase to increase reliability. The extent to which decreased system modularity propagates the spread of a cascading failure is unknown. This study analyzes how modularity in complex engineering systems affects resistance to the spread of cascading failures. In this research, synthetic networks are used to represent component models at differing degrees of modularity. These synthetic networks are then infected through epidemic spreading models that model cascading failures. The loss of functionality is determined by the percent of diseased nodes in the system, and the influence of the initial node is measured by eigenvector centrality. Increased modularity is associated with the improved ability of a system to inhibit the propagation of cascading failures over time through failure isolation within a module, measured by percent infected in the system, in comparison to less modular systems (p < 0.001). This finding indicates that the structural design of complex engineering systems could be crucial to increasing reliability in design with reference to cascading failures.
Key Words: Complex engineering systems, modularity, cascading failure
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A framework for assessing and improving the resilience of complex engineered systems during the early design process
As modern systems continue to increase in size and complexity, they pose significant safety and risk management challenges. System engineers and much of the government research efforts are focused on understanding the attributes and characteristics that emerge from the interactions of components and subsystems. As a result, the objective of this research is to develop techniques and supporting tools for the verification of the resilience of complex engineered systems during the early design stages. Specifically, this work focuses on automating the verification of safety requirements to ensure designs are safe, automating the analysis of design topology to increase design robustness against internal failures or external attacks, and allocating appropriate level of redundancy into the design to ensure designs are resilient. In distributed complex systems, a single initiating fault can propagate throughout engineering systems uncontrollably, resulting in severely degraded performance or complete failure.
This research is motivated by the fact that there is no formal means to verify the safety and resilience properties, and no provision to incorporate related analysis into the design process
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Designing Resilient Manufacturing Systems In the Presence of Change
Economic and technical changes force manufacturers to redesign and enhance their operational systems. The implications of such changes within a complex system such as manufacturing and the supply chain can be very challenging. In particular, where the number of system elements and their connections result in a high level of complexity, the potential effects of a change can be expensive concerning the delivery time and cost targets, as a change to one part or element of a design requires additional changes throughout the system.
Companies need to understand the characteristics of their manufacturing systems that make them resilient to change. Considered from a system perspective, the structures of the system, and its elements and connections, contribute greatly to the characteristics and behavior of the system and hence potential resilience. A change prediction method can help to analyse the change properties and improve complex systems by focusing on the underlying structural elements and dependencies.
This thesis proposes a novel system change method that can enable the review of the current manufacturing system and understand how to design a more robust or adaptable system that addresses resilience. This method is a combination of matrix-based approaches and methods to assess the interaction between elements of the product and its manufacturing process in order to understand the risk of changes propagating through the system. Risk assessment across layers of a system can give valuable insight into how an element change interacts within the system. The goal of this thesis is to contribute to gaining a fundamental understanding of manufacturing systems resilience by developing a method to evaluate capabilities of changes, performance robustness or adaptability, and achieving high resilience.Universal Oil Products (a Honeywell Company);
Laing O’Rourk