29 research outputs found

    Model-Based operational analysis for complex systems - A case study for electric vehicles

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    We present in this paper an operational analysis of a complex system following a Model Based Systems Engineering approach, illustrated by a case study on electric vehicles. We explain some strategic issues and reasons that make electric vehicles important and complex systems, and how these vehicles can significantly contribute to the European policies for sustainable development. We explain why it is necessary to apply a Systems Engineering approach to deal with the complexity of such systems, and we give an overview of the architectural design framework we follow. We present a model of the system of interest and of its environment built from the analysis of public documents and literature reviews. This allowed us to identify the key stakeholders, external interfaces, needs, use cases and operational scenarios. Based on this operational analysis, we present ways to pursue functional and trade-off analyses

    Scenario selection optimization in system engineering projects under uncertainty: a multi-objective ant colony method based on a learning mechanism

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    This paper presents a multi-objective Ant Colony Optimization (MOACO) algorithm based on a learning mechanism (named MOACO-L) for the optimization of project scenario selection under uncertainty in a system engineering (SE) process. The objectives to minimize are the total cost of the project, its total duration and the global risk. Risk is considered as an uncertainty about task costs and task durations in the project graph. The learning mechanism aims to improve the MOACO algorithm for the selection of optimal project scenarios in aSE project by considering the uncertainties on the project objectives. The MOACO-L algorithm is then developed by taking into account ants’ past experiences. The learning mechanism allows a better exploration of the search space and an improvement of the MOACO algorithm performance. To validate our approach, some experimental results are presented

    Application of machine learning techniques to the flexible assessment and improvement of requirements quality

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    It is already common to compute quantitative metrics of requirements to assess their quality. However, the risk is to build assessment methods and tools that are both arbitrary and rigid in the parameterization and combination of metrics. Specifically, we show that a linear combination of metrics is insufficient to adequately compute a global measure of quality. In this work, we propose to develop a flexible method to assess and improve the quality of requirements that can be adapted to different contexts, projects, organizations, and quality standards, with a high degree of automation. The domain experts contribute with an initial set of requirements that they have classified according to their quality, and we extract their quality metrics. We then use machine learning techniques to emulate the implicit expert’s quality function. We provide also a procedure to suggest improvements in bad requirements. We compare the obtained rule-based classifiers with different machine learning algorithms, obtaining measurements of effectiveness around 85%. We show as well the appearance of the generated rules and how to interpret them. The method is tailorable to different contexts, different styles to write requirements, and different demands in quality. The whole process of inferring and applying the quality rules adapted to each organization is highly automatedThis research has received funding from the CRYSTAL project–Critical System Engineering Acceleration (European Union’s Seventh Framework Program FP7/2007-2013, ARTEMIS Joint Undertaking grant agreement no 332830); and from the AMASS project–Architecture-driven, Multi-concern and Seamless Assurance and Certification of Cyber-Physical Systems (H2020-ECSEL grant agreement no 692474; Spain’s MINECO ref. PCIN-2015-262)

    Supporting multidisciplinary vehicle modeling : towards an ontology-based knowledge sharing in collaborative model based systems engineering environment

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    Simulation models are widely used by industries as an aid for decision making to explore and optimize a broad range of complex industrial systems’ architectures. The increased complexity of industrial systems (cars, airplanes, etc.), ecological and economic concerns implies a need for exploring and analysing innovative system architectures efficiently and effectively by using simulation models. However, simulations designers currently suffer from limitations which make simulation models difficult to design and develop in a collaborative, multidisciplinary design environment. The multidisciplinary nature of simulation models requires a specific understanding of each phenomenon to simulate and a thorough description of the system architecture, its components and connections between components. To accomplish these objectives, the Model-Based Systems Engineering (MBSE) and Information Systems’ (IS) methodologies were used to support the simulation designer’s analysing capabilities in terms of methods, processes and design tool solutions. The objective of this thesis is twofold. The first concerns the development of a methodology and tools to build accurate simulation models. The second focuses on the introduction of an innovative approach to design, product and integrate the simulation models in a “plug and play" manner by ensuring the expected model fidelity. However, today, one of the major challenges in full-vehicle simulation model creation is to get domain level simulation models from different domain experts while detecting any potential inconsistency problem before the IVVQ (Integration, Verification, Validation, and Qualification) phase. In the current simulation model development process, most of the defects such as interface mismatch and interoperability problems are discovered late, during the IVVQ phase. This may create multiple wastes, including rework and, may-be the most harmful, incorrect simulation models, which are subsequently used as basis for design decisions. In order to address this problem, this work aims to reduce late inconsistency detection by ensuring early stage collaborations between the different suppliers and OEM. Thus, this work integrates first a Detailed Model Design Phase to the current model development process and, second, the roles have been re-organized and delegated between design actors. Finally an alternative architecture design tool is supported by an ontology-based DSL (Domain Specific Language) called Model Identity Card (MIC). The design tools and mentioned activities perspectives (e.g. decisions, views and viewpoints) are structured by inspiration from Enterprise Architecture Frameworks. To demonstrate the applicability of our proposed solution, engine-after treatment, hybrid parallel propulsion and electric transmission models are tested across automotive and aeronautic industries.Les systĂšmes industriels (automobile, aĂ©rospatial, etc.) sont de plus en plus complexes Ă  cause des contraintes Ă©conomiques et Ă©cologiques. Cette complexitĂ© croissante impose des nouvelles contraintes au niveau du dĂ©veloppement. La question de la maitrise de la capacitĂ© d’analyse de leurs architectures est alors posĂ©e. Pour rĂ©soudre cette question, les outils de modĂ©lisation et de simulation sont devenus une pratique courante dans les milieux industriels aïŹn de comparer les multiples architectures candidates. Ces outils de simulations sont devenus incontournables pour conforter les dĂ©cisions. Pourtant, la mise en Ɠuvre des modĂšles physiques est de plus en plus complexe et nĂ©cessite une comprĂ©hension spĂ©ciïŹque de chaque phĂ©nomĂšne simulĂ© ainsi qu’une description approfondie de l’architecture du systĂšme, de ses composants et des liaisons entre composants. L’objectif de cette thĂšse est double. Le premier concerne le dĂ©veloppement d’une mĂ©thodologie et des outils nĂ©cessaires pour construire avec prĂ©cision les modĂšles de simulation des architectures de systĂšmes qu’on dĂ©sire Ă©tudier. Le deuxiĂšme s’intĂ©resse Ă  l’introduction d’une approche innovante pour la conception, la production et l’intĂ©gration des modĂšles de simulations en mode « plug and play » aïŹn de garantir la conformitĂ© des rĂ©sultats aux attentes, notamment aux niveaux de la qualitĂ© et de la maturitĂ©. Pour accomplir ces objectifs, des mĂ©thodologies et des processus d’ingĂ©nierie des systĂšmes basĂ©s sur les modĂšles (MBSE) ainsi que les systĂšmes d’information ont Ă©tĂ© utilisĂ©s. Ce travail de thĂšse propose pour la premiĂšre fois un processus dĂ©taillĂ© et un outil pour la conception des modĂšles de simulation. Un rĂ©fĂ©rentiel commun nommĂ© « ModĂšle de carte d'identitĂ© (MIC) » a Ă©tĂ© dĂ©veloppĂ© pour standardiser et renforcer les interfaces entre les mĂ©tiers et les fournisseurs sur les plans organisationnels et techniques. MIC garantit l’évolution et la gestion de la cohĂ©rence de l’ensemble des rĂšgles et les spĂ©ciïŹcations des connaissances des domaines mĂ©tiers dont la sĂ©mantique est multiple. MIC renforce Ă©galement la cohĂ©rence du modĂšle et rĂ©duit les anomalies qui peuvent interfĂ©rer pendant la phase dite IVVQ pour IntĂ©gration, VĂ©riïŹcation, Validation, QualiïŹcation. Finalement, aïŹn de structurer les processus de conception des modĂšles de simulation, le travail s’est inspirĂ© des cadres de l’Architecture d’Entreprise en reïŹ‚Ă©tant les exigences d’intĂ©gration et de standardisation du modĂšle opĂ©ratoire de l’entreprise. Pour valider les concepts introduits dans le cadre de cette thĂšse, des Ă©tudes de cas tirĂ©s des domaines automobile et aĂ©rospatiale ont Ă©tĂ© rĂ©alisĂ©es. L'objectif de cette validation est d'observer l'amĂ©lioration signiïŹcative du processus actuel en termes d'efficacitĂ©, de rĂ©duction de l'ambiguĂŻtĂ© et des malentendus dans la modĂ©lisation et la simulation du systĂšme Ă  concevoir

    Eco-design implementation for complex industrial system (From scenario-based LCA to the definition of an eco-innovative R&D projects portfolio)

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    Face Ă  l Ă©mergence des problĂ©matiques environnementales issues des activitĂ©s humaines, l Ă©coconception s attache Ă  offrir une rĂ©ponse satisfaisante dans le domaine de la conception de produits et services. Cependant, lorsque les produits considĂ©rĂ©s deviennent des systĂšmes industriels complexes, caractĂ©risĂ©s entre autres par un grand nombre de composants et sous-systĂšmes, un cycle de vie extrĂȘmement long et incertain, ou des interactions complexes avec leur environnement gĂ©ographique et industriel, un manque Ă©vident de mĂ©thodologies et d outils se fait ressentir. Ce changement d Ă©chelle apporte en effet des contraintes diffĂ©rentes aussi bien dans l Ă©valuation des impacts environnementaux gĂ©nĂ©rĂ©s au cours du cycle de vie du systĂšme (gestion et qualitĂ© des donnĂ©es, niveau de dĂ©tail de l Ă©tude par rapport aux ressources disponibles ) que dans l identification de rĂ©ponses adaptĂ©es (gestion de la multidisciplinaritĂ© et des ressources disponibles, formation des acteurs, inclusion dans un contexte de R&D trĂšs amont ). Cette thĂšse vise donc Ă  dĂ©velopper une mĂ©thodologie de mise en Ɠuvre d une dĂ©marche d Ă©co-conception de systĂšmes industriels complexes. Une mĂ©thodologie gĂ©nĂ©rale est tout d abord proposĂ©e, basĂ©e sur un processus DMAIC (Define, Measure, Analyse, Improve, Control). Cette mĂ©thodologie permet de dĂ©finir de maniĂšre formalisĂ©e le cadre de la dĂ©marche (objectifs, ressources, pĂ©rimĂštre, phasage ) et d accompagner rigoureusement l approche d Ă©coconception sur le systĂšme considĂ©rĂ©. Une premiĂšre Ă©tape d Ă©valuation environnementale basĂ©e sur l Analyse du Cycle de Vie (ACV) Ă  haut niveau systĂ©mique est ainsi rĂ©alisĂ©e. Etant donnĂ©e la complexitĂ© du cycle de vie considĂ©rĂ© et la variabilitĂ© d exploitation d un systĂšme industriel d un site Ă  l autre, une approche par scĂ©nario est proposĂ©e afin d apprĂ©hender rapidement l Ă©tendue possible des impacts environnementaux. Les scĂ©narios d exploitation sont dĂ©finis Ă  l aide de la matrice SRI (Stranford Research Institute) et intĂšgrent de nombreux Ă©lĂ©ments rarement abordĂ©s en ACV, comme la maintenance prĂ©ventive et corrective, la mise Ă  niveau des sous-systĂšmes ou encore la modulation de la durĂ©e de vie du systĂšme en fonction du contexte Ă©conomique. A l issue de cette ACV les principaux postes impactants du cycle de vie du systĂšme sont connus et permettent d entreprendre la seconde partie de la dĂ©marche d Ă©co-conception centrĂ©e sur l amĂ©lioration environnementale. Un groupe de travail multidisciplinaire est rĂ©uni lors d une sĂ©ance de crĂ©ativitĂ© centrĂ©e autour de la roue de la stratĂ©gie d Ă©co-conception (ou roue de Brezet), un outil d Ă©co-innovation peu consommateur de ressources et ne nĂ©cessitant qu une faible expertise environnementale. Les idĂ©es gĂ©nĂ©rĂ©es en crĂ©ativitĂ© sont alors traitĂ©es par trois filtres successifs, qui permettent : (1) de prĂ©sĂ©lectionner les meilleurs projets et de les approfondir ; (2) de constituer un portefeuille de projets de R&D par une approche multicritĂšre Ă©valuant leur performance environnementale, mais Ă©galement technique, Ă©conomique et de crĂ©ation de valeurs pour les clients ; (3) de contrĂŽler l Ă©quilibre du portefeuille constituĂ© en fonction de la stratĂ©gie de l entreprise et de la diversitĂ© des projets considĂ©rĂ©s (aspects court/moyen/long terme, niveau systĂ©mique considĂ©rĂ© ). L ensemble des travaux a Ă©tĂ© appliquĂ© et validĂ© chez Alstom Grid sur des sous-stations de conversion Ă©lectrique utilisĂ©es dans l industrie de l aluminium primaire. Le dĂ©ploiement de la mĂ©thodologie a permis d initier une dĂ©marche solide d Ă©coconception reconnue par l entreprise et de gĂ©nĂ©rer au final un portefeuille de 9 projets de R&D Ă©coinnovants qui seront mis en Ɠuvre dans les prochains mois.Face to the growing awareness of environmental concerns issued from human activities, eco-design aims at offering a satisfying answer in the products and services development field. However when the considered products become complex industrial systems, there is a lack of adapted methodologies and tools. These systems are among others characterised by a large number of components and subsystems, an extremely long and uncertain life cycle, or complex interactions with their geographical and industrial environment. This change of scale actually brings different constraints, as well in the evaluation of environmental impacts generated all along the system life cycle (data management and quality, detail level according to available resources ) as in the identification of adapted answers (management of multidisciplinary aspects and available resources, players training, inclusion in an upstream R&D context ). So this dissertation aims at developing a methodology to implement ecodesign of complex industrial systems. A general methodology is first proposed, based on a DMAIC process (Define, Measure, Analyse, Improve, Control). This methodology allows defining in a structured way the framework (objectives, resources, perimeter, phasing ) and rigorously supporting the ecodesign approach applied on the system. A first step of environmental evaluation based on Life-Cycle Assessment (LCA) is thus performed at a high systemic level. Given the complexity of the system life cycle as well as the exploitation variability that may exist from one site to another, a scenario-based approach is proposed to quickly consider the space of possible environmental impacts. Scenarios of exploitation are defined thanks to the SRI (Stanford Research Institute) matrix and they include numerous elements that are rarely considered in LCA, like preventive and corrective maintenance, subsystems upgrading or lifetime modulation according to the economic context. At the conclusion of this LCA the main impacting elements of the system life cycle are known and they permit to initiate the second step of the eco-design approach centred on environmental improvement. A multidisciplinary working group perform a creativity session centred on the eco-design strategy wheel (or Brezet wheel), a resource-efficient eco-innovation tool that requires only a basic environmental knowledge. Ideas generated during creativity are then analysed through three successive filters allowing: (1) to pre-select and to refine the best projects; (2) to build a R&D projects portfolio thanks to a multi-criteria approach assessing not only their environmental performance, but also their technical, economic and customers value creation performance; (3) to control the portfolio balance according to the company strategy and the projects diversity (short/middle/long term aspect, systemic level ). All this work was applied and validated at Alstom Grid on electrical conversion substations used in the primary aluminium industry. The methodology deployment has allowed initiating a robust eco-design approach recognized by the company and finally generating a portfolio composed of 9 eco-innovative R&D projects that will be started in the coming months.CHATENAY MALABRY-Ecole centrale (920192301) / SudocSudocFranceF

    Configuration interactive et contraintes : connaissances, filtrage et extensions

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    The value of our research work is rooted in the following observations :-1- the life cycle of products, systems, services and processes is tending to get shorter ; -2- new designs and updates of products on the market are becoming more and more frequent, leading to increasingly short design cycles ; -3 technologies are constantly changing, requiring permanent, ongoing acquisition of knowledge ; -4-the diversity of products offered on the market is growing all the time, ranging from customizable or configurable to made-to-measure or designed to order.These trends, and the mass of information and knowledge that requires treating as a result of them, are placing heavy demands on designers, requiring ever more attentiveness and increasingly intense cognitive effort. The result is an increased risk that the product does not fully meet the customer’s needs, that it is difficult to implement or manufacture, or that it will be prohibitively expensive. The aim of our work is thus to help the design process to reduce these risks and errors by delivering software tools and methodological environments that serve to capitalize and exploit general, contextual, academic, expert or business knowledge.Our work on various complex industrial cases has led us to take into consideration two kinds of knowledge, involving on the one hand the "product domain" and on the other the "product diversity element". Each kind of knowledge leads to differing industrial cases. The first kind of knowledge encompasses the scientific and technical aspects, but also the specific rules governing the business in question. This knowledge is required in order to define the product itself, and involves issues that can be resolved by aiding the product /system/service design. The second kind of knowledge relates to the diverse nature of the products, and involves issues of customization or configuration of the product/system/service.Our aim is to help in what might be called "routine" design, where different kinds and various types of knowledge exist, due to the recurrent nature of the activity. We consider that aid in design or configuration can be formalized, either completely or partially, in the form of a constraint satisfaction problem (CSP). In this context, we focus more specifically on interactive decision-support, by introducing the principles of filtering or constraint propagation. The diversity of knowledge formalized as a CSP and the interaction with the user allow us to assemble and adapt filtering algorithms in a generic constraint propagation engine, integrated in our CoFiADe software solution.In addition, this formalism based on CSP constraints is complemented by : - ontologies to structure knowledge and facilitate its reuse throughout the development cycle, - analogy-based approaches taking advantage of contextual knowledge encapsulated in the case under study, so as to make recommendations to the user on the choice of values, - evolutionary approaches to optimize the search for multi-criteria solutions.Les travaux de recherche présentés dans ce mémoire trouvent leurs fondements dans les constats suivants :-1- la durée de vie des produits et systèmes tend à se réduire,-2- les conceptions et les actualisations des produits mis sur le marché sont de plus en plus fréquentes alors que les cycles de conception sont toujours plus brefs,-3- les technologies employées en constante évolution nécessitent une acquisition de connaissance permanente,-4- la diversité des produits offerte sur les marchés ne cesse de croître allant des produits personnali- sables ou configurés jusqu’aux produits sur-mesure et conçus à la commande.Ces tendances et la masse d’informations et de connaissances à traiter en découlant exigent des concepteurs toujours plus d’attention et un travail cognitif toujours plus intense. Il en résulte une augmentation des risques, que le produit réponde imparfaitement aux besoins du demandeur, qu’il soit difficilement réalisable et fabricable, ou encore qu’il le soit à un coût prohibitif. L’objectif de nos travaux est donc de limiter ces risques et erreurs en proposant des outils logiciels et des environnements méthodologiques destinés à capitaliser et exploiter des connaissances générales, contextuelles, académiques, expertes ou métier pour aider la conception.Les travaux effectués sur différentes problématiques industrielles ont conduit à prendre en considération deux natures de connaissances relevant du « domaine produit » et de la « diversité produit » conduisant à des problématiques industrielles différentes : la première nature de connaissance recouvre aussi bien des aspects scientifiques et techniques que des règles métier, elle est nécessaire pour la définition du produit et débouche sur des problématiques d’aide à la conception de produit ; la seconde nature est une connaissance liée à la diversité des produits, qui débouche sur les problématiques d’aide à la personnalisation ou configuration de produit.Nous visons à aider un type de conception plutôt « routinier » où de la connaissance de différentes natures et de divers types existe du fait de la récurrence de l’activité. Nous considérons de plus dans nos travaux que l’aide à la conception ou configuration peut se formaliser, complètement ou partiellement, comme un problème de satisfaction de contraintes (CSP). Dans ce cadre, nous nous intéressons plus spécifiquement à l’aide à la décision interactive exploitant les principes de filtrage ou de propagation de contraintes. Notre objectif se décline alors en l’accompagnement des concepteurs dans la construction des solutions répondant au mieux à leurs problèmes, en retirant progressivement de l’espace des solutions, celles qui ne sont plus cohérentes avec les décisions prises, en estimant celles-ci au fil de leur construction et/ou en les optimisant.en complément, nous associons à ce formalisme à base de contraintes CSP :- des ontologies pour structurer les connaissances et faciliter leur réutilisateion sur l’ensemble du cycle de développement,- des approches par analogie exploitant de la connaissance contextuelle encapsulée dans des cas afin de proposer à l’utilisateur des recommandations quant aux choix de valeurs,- des approches évolutionnaires pour optimiser la recherche des solutions de manière multicritère

    Formalisation et exploitation de connaissances et d’expĂ©riences pour l’aide Ă  la dĂ©cision dans les processus d’ingĂ©nierie systĂšme

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    Ce manuscrit d’habilitation Ă  diriger des recherche synthĂ©tise mon activitĂ© professionnelle en enseignement et en recherche depuis l’obtention de mon poste de maĂźtre de confĂ©rences en 2001. AprĂšs l’obtention de mon diplĂŽme de doctorat, prĂ©parĂ© au Laboratoire GĂ©nie de Production (LGP) entre 1997 et 2000 sous la direction de Bernard Grabot, j’ai obtenu mon poste de maĂźtre de confĂ©rences Ă  l’UniversitĂ© de Bretagne Sud Ă  Lorient (UBS). Durant une pĂ©riode de trois annĂ©es dans cette universitĂ© et au Laboratoire d’Electronique des SystĂšmes Temps RĂ©els (LESTER devenu LAB-STICC par la suite), j’ai pu dĂ©velopper des activitĂ©s de recherche dans le domaine de la conception et de la reconfiguration des systĂšmes automatisĂ©s de type SystĂšmes Transitiques. Suite Ă  ma mutation Ă  l’Ecole Nationale d’IngĂ©nieurs de Tarbes en 2004, j’ai poursuivi mes activitĂ©s de recherche au Laboratoire GĂ©nie de Production (LGP) en lien avec le dĂ©veloppement d’outils d’aide ‘a la dĂ©cision dans les processus d’ingĂ©nierie systĂšme basĂ©s sur l’exploitation de connaissances et d’expĂ©riences. En enseignement, depuis 2001, mes activitĂ©s sont partagĂ©es entre le gĂ©nie industriel et l’informatique. Ce document est structurĂ© en deux parties : 1. la premiĂšre partie permet d’exposer, dans mon Curriculum Vitae dĂ©taillĂ©, un bilan de mes activitĂ©s d’enseignant-chercheur. Mon parcours professionnel, mes activitĂ©s d’enseignement et un bilan de mes activitĂ©s de recherche sont exposĂ©s de maniĂšre synthĂ©tique. Dans un premier temps, les enseignements dont j’ai eu la responsabilitĂ© (conception et ou rĂ©alisation) ainsi que les documents pĂ©dagogiques produits et les volumes horaires sont exposĂ©s. Ensuite, les encadrements de chercheurs (doctorants, masters et post-doctorat), les projets institutionnels (FUI et ANR) dans lesquels j’ai pris des responsabilitĂ©s, les partenariats avec des entreprises dans le cadre de contrats CIFRE, mes activitĂ©s d’animation de la recherche au niveau national et international font partie de ce bilan. Cette section se termine par la liste exhaustive de mes publications et communications (section 3.5) rĂ©alisĂ©es depuis le dĂ©but de mon activitĂ© de chercheur, en 1997, 2. la seconde partie synthĂ©tise mes activitĂ©s de recherche rĂ©alisĂ©es depuis 2001. Cette seconde partie est prĂ©sentĂ©e selon 6 chapitres. Le chapitre 1 permet d’exposer la problĂ©matique globale de mes travaux de recherche. Elle est orientĂ©e par un modĂšle Ă  trois niveaux (Processus, Outils, ExpĂ©riences / Connaissances) et Ă©tayĂ©e par un premier niveau d’étude bibliographique. Le niveau de dĂ©tail choisi permet de comprendre cette problĂ©matique dans sa globalitĂ©. Les processus ciblĂ©s, les outils dĂ©veloppĂ©s, les connaissances exploitĂ©es sont prĂ©sentĂ©s au regard de la littĂ©rature dans les diffĂ©rents domaines. Les chapitres 2 Ă  5 fournissent quant Ă  eux un niveau de dĂ©tail plus fin. Ils permettent de prĂ©senter les problĂ©matiques de maniĂšre affinĂ©e, les dĂ©veloppements rĂ©alisĂ©s et les contributions scientifiques majeures. L’objectif est de fournir des Ă©lĂ©ments qui soient utiles Ă  la comprĂ©hension de mon activitĂ© de recherche mais, Ă©galement, d’en favoriser l’exploitation ultĂ©rieure. Enfin, dans le chapitre 6, la conclusion permet de prendre le recul nĂ©cessaire au travaux rĂ©alisĂ©s et de proposer mon projet de recherche pour les annĂ©es Ă  venir

    Ethics in Higher Education : Values-driven Leaders for the Future

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    The values and virtues practised in universities heavily influence the leaders of the future, but outside the limelight of excelling education institutions there is a concerning violation of good practises and rise in unethical behaviour. This book offers diverse insights from 19 different authors, writing from eight countries in five continents, providing explanations and recommendations for the ethical crisis present around the world which can be mitigated by suitable education in ethics, particularly in higher education institutions

    Cultural values change in the rehabilitation of historic schools in Portugal

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    Despite the importance of the preservation of the historic built environment for the benefit of present and future generations, there is a lack of knowledge of the effects of architectural rehabilitation decisions on the cultural significance of historic buildings. Architectural heritage conservation literature has focused almost exclusively on providing principles and guidelines, describing intervention methodologies, and discussing predicted impacts of design on material values. This thesis argues that a focus on the actual effects is needed if the sociocultural sustainability of historic buildings significance is to be achieved. Supported by an extensive literature review and informed by personal insights from the researcher’s everyday practice, an adapted model of the Theory of Change based on Weiss (1995) was designed, providing a tool to evaluate the effects of rehabilitation on cultural significance [ERECS]. Using a selection of six recently rehabilitated historic secondary schools in Portugal (liceus), this research investigated architectural decisions and their effects on the cultural values of this building typology for education, focusing on three objectives, corresponding to three stages of interventions: understanding the existing cultural significance, identifying the design strategies applied and assessing the short-term effects of design decisions on the cultural values. Stressing the role of stakeholders in rehabilitation processes, data were collected from the buildings and architectural projects, the decision makers in the conservation process, and the school community. Although confirming that the evaluation of the effects of architectural decisions on cultural values is a complex task, the findings demonstrate that the historic liceus have historical, architectural and sociocultural values, and whilst strategies did not value social values, material cultural values were generally considered and preserved, contributing to the enhancement of intangible values. The implications of this theory-based and evidence-based research highlight the importance of evaluating actual effects for cultural heritage theory, architectural conservation practice and heritage management policy
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