46 research outputs found

    Towards a Self-Healing approach to sustain Web Services Reliability.

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    International audienceWeb service technology expands the role of the Web from a simple data carrier to a service provider. To sustain this role, some issues such as reliability continue to hurdle Web services widespread use, and thus need to be addressed. Autonomic computing seems offering solutions to the specific issue of reliability. These solutions let Web services self-heal in response to the errors that are detected and then fixed. Self-healing is simply defined as the capacity of a system to restore itself to a normal state without human intervention. In this paper, we design and implement a selfhealing approach to achieve Web services reliability. Two steps are identified in this approach: (1) model a Web service using two behaviors known as operational and control; and (2) monitor the execution of a Web service using a control interface that sits between these two behaviors. This control interface is implemented in compliance with the principles of aspect-oriented programming and case-based reasoning

    A formal ontology for industrial maintenance

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    International audienceThe rapid advancement of information and communication technologies has resulted in a variety of maintenance support systems and tools covering all sub-domains of maintenance. Most of these systems are based on different models that are sometimes redundant or incoherent and always heterogeneous. This problem has lead to the development of maintenance platforms integrating all of these support systems. The main problem confronted by these integration platforms is to provide semantic interoperability between different applications within the same environment. In this aim, we have developed an ontology for the field of industrial maintenance, adopting the METHONTOLOGY approach to manage the life cycle development of this ontology, that we have called IMAMO (Industrial MAintenance Management Ontology). This ontology can be used not only to ensure semantic interoperability but also to generate new knowledge that supports decision making in the maintenance process. This paper provides and discusses some tests so as to evaluate the ontology and to show how it can ensure semantic interoperability and generate new knowledge within the platform

    PETRA: Process Evolution using a TRAce-based system on a maintenance platform

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    To meet increasing needs in the field of maintenance, we studied the dynamic aspect of process and services on a maintenance platform, a major challenge in process mining and knowledge engineering. Hence, we propose a dynamic experience feedback approach to exploit maintenance process behaviors in real execution of the maintenance platform. An active learning process exploiting event log is introduced by taking into account the dynamic aspect of knowledge using trace engineering. Our proposal makes explicit the underlying knowledge of platform users by means of a trace-based system called “PETRA”. The goal of this system is to extract new knowledge rules about transitions and activities in maintenance processes from previous platform executions as well as its user (i.e. maintenance operators) interactions. While following a Knowledge Traces Discovery process and handling the maintenance ontology IMAMO, “PETRA” is composed of three main subsystems: tracking, learning and knowledge capitalization. The capitalized rules are shared in the platform knowledge base in order to be reused in future process executions. The feasibility of this method is proven through concrete use cases involving four maintenance processes and their simulation

    A contextual semantic mediator for a distributed cooperative maintenance platform.

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    International audiencePlatforms expand maintenance systems from centralized systems into e-maintenance platforms integrating various cooperative distributed systems and maintenance applications. This phenomenon allowed an evolution in services offered to maintenance actors by integrating more intelligent applications, providing decision support and facilitating the access to needed data. To manage this evolution, e-maintenance platforms must respond to a great challenge which is ensuring an interoperable communication between its integrated systems. By combining different techniques used in previous works, we propose in this work a semantic mediator system ensuring a high level of interoperability between systems in the maintenance platform

    Towards a maintenance semantic architecture.

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    International audienceTechnological and software progress with the evolution of processes within company have highlighted the need to evolve systems of maintenance process from autonomous systems to cooperative and sharing information system based on software platform. However, this need gives rise to various maintenance platforms. The first part of this study investigates the different types of existing industrial platforms and characterizes them compared to two criteria namely : information exchange and relationship intensity. This allowed identifying the e-maintenance architecture as the current most efficient architecture. despite its effectiveness, this latter can only guarantee technical interoperability between various components. Therefore, the second part of this study proposes a semantic-knowledge based architecture, thereby ensuring a higher level of semantic interoperability. To this end, specific maintenance ontology has been developed

    A Trace based system for decision activities in CBM Process.

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    International audiencePrognostics and Health Management platforms are founded on Condition Based Maintenance process. Major works on this topic are focused on the diagnostic and prognostic modules and neglect the Decision Support Module which must be investigated to give more efficiency to PHM platforms. To improve this module with intelligence and rapidity we propose in this work to integrate a Trace Based System (TBS) into the decision support module. This TBS provides three main services (Traceability, self-learning and self-management) which are developed in this work

    Contribution à la spécification et à l'élaboration d'une plateforme de maintenance orientée connaissances

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    Le maintien en condition opérationnelle des équipements industriels est un des enjeux importants de l'entreprise, et a fait passer la maintenance d'un centre de coût à un centre de profit, ce qui a eu pour conséquence une éclosion de logiciels d'aide à la maintenance allant de la GMAO aux plateformes de e-maintenance. Ces systèmes d'aide fournissent aux différents acteurs de la maintenance, un support à la décision et un ensemble de services permettant une gestion informatisée d'activités de base appartenant au processus de maintenance (exemple l'intervention, la planification, le diagnostic, etc.). Toutefois, les besoins des utilisateurs évoluent dans le temps en fonction de nouvelles contraintes, de leur expertise, des nouvelles connaissances. Par contre les services fournis n'évoluent pas et nécessitent une réactualisation. Afin de tenir compte de l'évolution de ces connaissances, pour que ces systèmes d'aide puissent répondre aux besoins des utilisateurs et puissent proposer des services à la demande et des services évolutifs nous avons fait le point dans cette thèse sur les avantages et limites des systèmes informatiques d'aide existants notamment les plateformes de e-maintenance (systèmes les plus avancés aujourd'hui en maintenance). Pour pallier le manque des systèmes existants, nous avons proposé le concept de s-maintenance qui est caractérisé principalement par les échanges collaboratifs entre applications et utilisateurs, par des connaissances communes du domaine de maintenance. Pour mettre en œuvre ce concept, nous avons proposé une plateforme orientée connaissances assurant des fonctionnalités auto-x (auto-traçabilité, auto-apprentissage, autogestion) qui permettent de répondre aux caractéristiques de la s-maintenance. L'architecture à base de composants de cette plateforme prend appui sur une base de connaissances partagée entre les différents composants qu'elle intègre au profit de l'interopérabilité sémantique ainsi que de la capitalisation des connaissances. Nous avons par ailleurs développé une ontologie du domaine de maintenance sur laquelle s'appuie cette base de connaissances. Finalement, afin de développer les fonctionnalités auto-x assurées par la plateforme nous avons proposé un système à base de traces exploitant la base de connaissances et l'ontologie associéeOperational condition maintenance of industrial equipment is a principal challenge for the firm production. This fact transfer the maintenance from the cost center to the profit center which has lead to massif development of maintenance support system starting from the GMAO to the e-maintenance platform. These systems provide to the maintenance agent, decision-support, and set of services allowing a computerized management of core activities for maintenance process. (e.g. intervention, planning, diagnostic,...). However, the user request continues evolving in time with respect of their expertise, their renewed knowledge and new constraints. On the other hand, the existing services are not following their requirements and they need to be updated. In this thesis, an overview on the advantage and drawback of existing computerized support system, in particular the e-maintenance platform (the most advanced maintenance system) is presented in order to meet the users needs and propose scalable and on-demand services. To overcome the existing system shortage, we propose the s-maintenance concept characterized by the collaborative exchange between users and applications and the common knowledge of the maintenance field. Thus, to implement this concept, a knowledge-oriented platform is proposed providing the auto-x functionalities (auto-traceability, auto-learning and auto-management) and meeting the s-maintenance characteristics. The architecture based on components of this platform, is also based on shared knowledge between integrated components for the benefit of the semantic interoperability as well as for the knowledge capitalization. Maintenance domain ontology is also developed on which the knowledge base is rested. Finally, in order to develop the auto-x functionalities, provided by the platform, a trace-based system is proposed by exploiting the knowledge base and the associated ontology.BESANCON-Bib. Electronique (250560099) / SudocSudocFranceF

    CASAS: A tool for composing automatically and semantically astrophysical services

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    Multiple astronomical datasets are available through internet and the astrophysical Distributed Computing Infrastructure (DCI) called Virtual Observatory (VO). Some scientific workflow technologies exist for retrieving and combining data from those sources. However selection of relevant services, automation of the workflows composition and the lack of user-friendly platforms remain a concern. This paper presents CASAS, a tool for semantic web services composition in astrophysics. This tool proposes automatic composition of astrophysical web services and brings a semantics-based, automatic composition of workflows. It widens the services choice and eases the use of heterogeneous services. Semantic web services composition relies on ontologies for elaborating the services composition; this work is based on Astrophysical Services ONtology (ASON). ASON had its structure mostly inherited from the VO services capacities. Nevertheless, our approach is not limited to the VO and brings VO plus non-VO services together without the need for premade recipes. CASAS is available for use through a simple web interface

    A component based system for S-maintenance.

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    International audienceThanks to ICT, Web emergency and Internet, the achievement of maintenance services and monitoring can be performed automatically, remotely and through various distributed information systems. Hence the emergence of the concept of services offered through maintenance architectures, ranging from autonomic systems to integrated systems where knowledge management, cooperation and collaboration are vital to any operation. Into this context, new services like intelligent maintenance, self maintenance, etc are required. To this end, a new concept called s-maintenance is emerged. This concept defines a new generation of maintenance systems founded on a knowledge based system. While existing systems don't respond to the characteristics of this new generation of systems, we design in this paper an architecture of a maintenance component based system respecting the characteristics of s-maintenance. Each component in the system is defined to respond to one or many characteristics of this concept
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