Promotion of the Model-Based System Engineering approach for dependability analyses of critical complex systems integrating COTS

Nowadays, industrial systems are getting more and more complicated, integrating various technologies. Their designs involve many different engineering fields to maximize rentability and to offer the most up to date functionalities and services. The Model-Based System Engineering (MBSE) approach address specifically these issues by allowing a more global way of designing a complex system from many points of view. However, MBSE does not ensure dependability. That is the reason why, in this thesis, our work aims to connect the MBSE approach with dependability analysis. The SysML modeling language is used to reify the results of system engineering activities, to obtain a model of the system. This model is then computed to extract data that will help dependability analysis. These automatic processes of extraction and redaction are part of the MéDISIS methodology which is defined in this thesis. Two aspect of the MéDISIS methodology are discussed: the generation of functional FMEA and the use of the FIDES methodology in association with SysML to evaluate the failure rate of COTS. This work and the whole MéDISIS methodology are applied in the industrial context of the LEA project. This project, financed by MBDA, consists in designing an hypersonic vehicle.

Data and Resources

Additional Info

Field Value
Source https://theses.hal.science/tel-00812898
Author Cressent, Robin
Maintainer CCSD
Last Updated May 11, 2026, 12:28 (UTC)
Created May 11, 2026, 12:28 (UTC)
Identifier NNT: 2012ORLE2047
Language fr
Rights https://about.hal.science/hal-authorisation-v1/
contributor Laboratoire Pluridisciplinaire de Recherche en Ingénierie des Systèmes, Mécanique et Energétique [2008-2013] (PRISME) ; Université d'Orléans (UO)-Ecole Nationale Supérieure d'Ingénieurs de Bourges (ENSI Bourges)
creator Cressent, Robin
date 2012-12-12T00:00:00
harvest_object_id 716fe13c-c8b2-4110-9dd6-b376b62316b3
harvest_source_id 3374d638-d20b-4672-ba96-a23232d55657
harvest_source_title test moissonnage SELUNE
metadata_modified 2026-03-31T00:00:00
set_spec type:THESE