Model-based and simulation-driven methods for the reliability and safety analysis of systems
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Tundis, Andrea
Greco, Sergio
Garro, Alfredo
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Dottorato di Ricerca in Ingegneria dei Sistemi e Informatica, Ciclo XXVI, a.a.2013; In several industrial domains such as automotive, railway, avionics, satellite,
health care and energy, a great variety of systems are currently designed and
developed by organizing and integrating existing components (which in turn
can be regarded as systems),that pool their resources and capabilities together
to create a new system which is able to o er more functionalities and performances
than those o ered by the simple sum of its components. Typically,
the design and management of such systems, whose properties cannot be immediately
de ned, derived and easily analyzed starting from the properties of
their parts when they are considered in stand-alone, require to identify and
face with some important research issues.
In particular, the integration of system components is a challenging task
whose criticality rises as the heterogeneity and complexity of the components
increase. Thus, suitable engineering methods, tools and techniques need to be
exploited to prevent and manage the risks arising from the integration of system
components and, mainly, to avoid their occurrence in the advanced phases
of the system development process which may result in a signi cant increase
in the entire project costs. To overcome these issues the adoption of the Systems
Engineering approach represents a viable solution as it provides a wide
set of methods and practices which allow the de nition of the system architecture
and behavior at di erent abstraction level in terms of its components
and their interactions. Moreover, systems requirements are constantly traced
during the di erent system development phases so to clearly specify how a
system component concurs to the ful llment of the requirements. However,
in the Systems Engineering eld, even though great attention has been devoted
to functional requirements analysis and traceability, there is still a lack
of methods which speci cally address these issues for non-functional requirements.
As a consequence, the analysis concerning if and how non-functional
requirements are met by the system under development is not typically executed
contextually to the design of the system but still postponed to the last
stages of the development process with a high risk of having to revise even
basic design choices and with a consequent increase in both completion tim and development costs. Among all system requirements, Reliability and Safety
are important non-functional requirements. Especially for mission-critical systems,
there is a strong demand for new and more powerful analysis tools and
techniques able not only to verify the reliability indices and safety of a system
but also to
exibly evaluate the system performances and compare di erent
design choices.
In this context, the research aimed to promote the use of
exible methods
for the analysis of non-functional requirements by focusing on the de nition
of: (i) model-based method for system reliability analysis centered on popular
SysML/UML-based languages for systems modeling and on de-facto standard
platforms for the simulation of multi-domain dynamic and embedded
systems (Mathworks Simulink); (ii) a methodological process for supporting
the safety analysis, along with an approach for performing the Fault Tree
Analysis of cyber-physical systems, mainly based on the Modelica language
and OpenModelica simulation environment. Furthermore, in order to support
the representation of system requirements and thus enable their veri cation
and validation during the design stages, a meta-model for modeling requirements
of physical systems as well as di erent approaches for extending the
Modelica language have been proposed. Moreover, an algorithm, which allows
trace and evaluate requirements violation through simulation, has been
de ned.
Finally, the e ectiveness of the proposed methods and approaches, especially
in the modeling and analysis of both the expected and dysfunctional
system behavior, is the result of an intensive experimentation in several industrial
domains such automotive, avionics and satellite; Università della CalabriaSoggetto
Ingegneria dei sistemi; Sistemi; Modelli; Simulazione
Relazione
ING-INF/05;