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Vers une approche ontologique de l'évaluation de la continuité des activités
No full textInternational audienceBusiness Continuity (BC) methods use threat identification, continuous improvement, and recommendations to ensure running the organization's main activities in case of disruptive events. Information Systems, on the other hand, are increasingly based on service-based structures and are seen as fundamental instruments to guarantee business continuity. The paper presents the ontological foundations for representing business continuity semantics, which are based on a widely adopted information systems research framework. The overall aim of this work is to provide BC with formal semantics and business people with an emerging informal BC modeling method
System Configuration Models: Towards a Specialization Approach
No full textInternational audienceNowadays, system configuration helps to achieve mass customization and manage a wide variety of systems. System configuration is based on a model that gathers all relevant knowledge for a family of systems. This knowledge model can be difficult to formalize and keep up to date; indeed, the knowledge must be made explicit, and can come from different departments and experts within an organization. In addition, it must reflect the different variants and options of a family of systems. Therefore, we try to answer the following question: how to better formalize and structure knowledge for system configuration to define configuration models and use the benefits of specialization in terms of modeling? Thus, in our proposal, we introduce the elements required to formalize the knowledge and define configuration models. This formalization will be done in a structured way using the association of ontology and Constraint Satisfaction Problem (CSP). We use the abilities of ontology to model knowledge of the different artifacts, their characteristics, and composition, and the abilities of CSP to model the relations between artifacts. In our proposal, we also define artifacts at different levels of abstraction using specialization which allows experts to detail or refine the formalized knowledge. We illustrate our proposals on a simplified but realistic example of a bicycle
Making Decisions in Highly Uncertain and Opportunistic Environments: Towards a Decision Support System for Sales and Operations Planning
No full textInternational audienceSales and Operations Planning (S&OP) is a methodology used by most companies to make planning decisions on a medium-term horizon. This methodology and associated tools have been designed for a relatively stable environment. However, this assumption is not relevant anymore, and practitioners face difficulties to perform S&OP in highly uncertain and opportunistic environments. Therefore, this paper proposes to pave the way towards a solution to these difficulties, by introducing a conceptual framework for designing a decision support system for performing S&OP in highly uncertain and opportunistic environments. The paper concludes with a set of research avenues to make it real
The Impact of Reward Shaping in Reinforcement Learning for Agent-based Microgrid Control
No full textInternational audienceIn order to reduce CO2 emissions, electricity networks must increasingly integrate renewable energies. Microgrids are distributed electrical networks with their own generation and load, often supported by an electrical storage system. It can be connected to the external electrical network or isolated. Since electricity consumption, price and renewable production are stochastic phenomena, the control of microgrids must adapt to uncertainties. Data-driven models and in particular reinforcement learning (RL) have become efficient algorithms in high-level microgrid control. RL are agent-based algorithms, which interact with their environment and learn with a numerical reward signal. A certain behavior can implicitly be expected when the reward system is formulated. For example, a reward system that encourages the agent to interact as little as possible with the external network will explicitly increase the autonomy of the microgrid. Implicitly, it can be expected to schedule the battery to maximize the ratio of renewable energy used to the amount producible. Q-learning algorithm has been used due to its performance in discrete action space, which simplified the benchmark complexity. An agent is trained with different reward functions commonly found in the literature related to data-driven microgrid control algorithms. The agent parameters do not vary from one case study to another. Indicators are set up to evaluate the agent behavior. They are based on implicit behavioral criteria in the definition of the reward system such as the ratio of renewable energy used, the amount of energy stored during peak hours, etc. This study enables to find a way to rationalize the choice of a reward system to control in a near-optimal way microgrid while meeting implicit secondary objectives. It could lead to a choice on weighting coefficient in a combination of reward functions
Feasibility of additive manufacturing processes for lunar soil simulants
No full textArticle tiré d'une communication du congrès MMA 2021 - 14th International scientific conference MMA 2021 - Flexible technologiesInternational audienceCombination of In-situ Resource Utilization (ISRU) and on-site Additive Manufacturing (AM) is one of the “outer space applied technologies” candidates where free shape fabrication from micro (e.g., tools) to mega scale (e.g. lunar habitats) will allow in coming future to settle the Moon or potentially other celestial bodies. Within this research, Selected Laser Melting (SLM) of lunar soil (regolith) simulants (LHS-1 LMS-1 and JSC-2A) using a continuous wave 100 W 1090 nm fiber laser was applied. The resulting samples were mechanically and optically characterized. A numerical multiphysics model was developed to understand the heat transfer and optimize the SLM process. Results obtained are in good agreement with the numerical model. The physical and chemical characteristics of the various materials (granulometry, density, composition, and thermal properties) have a strong impact on the AM parameters
Assembling of Carbon Fibre/PEEK Composites: Comparison of Ultrasonic, Induction, and Transmission Laser Welding
No full textInternational audienceIn the present work, an ultrasonic, an induction, and a through transmission laser welding were compared to join carbon fibre reinforced polyetheretherketone (CF/PEEK) composites. The advantages and drawbacks of each process are discussed, as well as the material properties required to fit each process. CF/PEEK plates were consolidated at 395 °C with an unidirectional sequence and cross-stacking ply orientation. In some configurations, a polyetherimide (PEI) layer or substrate was used. The thermal, mechanical, and optical properties of the materials were measured to highlight the specific properties required for each process. The drying conditions were defined as 150 °C during at least 8 h for PEI and 24 h for CF/PEEK to avoid defects due to water. The optical transmission factor of PEI is above 40% which makes it suitable for through transmission laser welding. The thermal conductivity of CF/PEEK is at most 55 W·(m·K)−1, which allows it to weld by induction without a metallic susceptor. Ultrasonic welding is the most versatile process as it does not necessitate any specific properties. Then, the mechanical resistance of the welds was measured by single lap shear. For CF/PEEK on CF/PEEK, the maximum lap shear strength (LSS) of 28.6 MPa was reached for a joint obtained by ultrasonic welding, while an induction one brought 17.6 MPa. The maximum LSS of 15.2 MPa was obtained for PEI on CF/PEEK assemblies by laser welding. Finally, interfacial resistances were correlated to the fracture modes through observations of the fractured surfaces. CF/PEEK on CF/PEEK joints resulted in mixed cohesive/adhesive failure at the interface and within the inner layers of both substrates. This study presents a guideline to select the suitable welding process when assembling composites for the aerospace industry
Médias sociaux et résilience collective : la mobilisation des makers pendant la crise de Covid-19
No full textNational audienceCe chapitre étudie l'appropriation des médias sociaux par les communautés de makers au cours de la crise de Covid-19, pour s'organiser et combler un manque institutionnel dans la production et la distribution de matériel médical (masques, visières). Des entretiens demi-directifs ont été menés avec des makers contribuant à deux réseaux: Visière solidaire, et le réseau d'étudiants des Arts et Métiers. Les travaux montrent en quoi les usages des médias sociaux s'intègrent de manière transparente aux pratiques des citoyens, qui se les approprient pour répondre à des besoins spécifiques. Les initiatives étudiées s'inscrivent alors dans une cartographie plus vaste de la diversité d'initiatives menées au cours de la crise, couvrant partage d'informations, construction de la connaissance, organisation et réalisation d'opérations de réponse. Cette étude souligne enfin l'apport de cette diversité d'usages des médias sociaux pour construire pleinement la résilience collective au fil des crises
On the Phase Behaviour of the CO2 + N2O4 system at low temperatures
No full textInternational audienceCarbon dioxide capture transportation and storage is one of the technologies that can be employed to reduce CO 2 emissions from power plants. Unfortunately, in the post combustion capture process, CO 2 is not pure and contains impurities like SO 2 , NO x , N 2 , O 2 and Ar for example. In this paper, Vapour-Liquid-Equilibrium (VLE) of a binary system composed of CO 2 and N 2 O 4 /NO 2 have been investigated. The equipment used is based on the "staticsynthetic" method with a variable cell to determine the bubble pressure or saturated pressure of the system. The setup was used to obtain bubble point data at four isotherms (253.43, 273.43, 293.43, 303.43) K and pressures up to 7.3 MPa. The accuracies of the measured temperature and pressure were estimated to be 0.03 K and 0.12 kPa, respectively. The Peng-Robinson equation of state (PR78 EoS) is used to represent the isothermal P, x data
Stable Heuristic Miner: applying statistical stability to discover the common patient pathways from location event logs
No full textInternational audiencePurpose: The classic heuristic miner algorithm has received lots of attention in the healthcare sector for discovering patient pathways. The extraction of these pathways provides more transparency about patient activities. The previous versions of this algorithm receive an event log and discover several process models by using manually adjustable thresholds. Then, the expert is left with the difficult task of deciding which discovered model can serve as the descriptive reference process model. Such a decision is completely arbitrary and it has been seen as a major structural issue in the literature of process mining. This paper tackles this problem by proposing a new process discovery algorithm to facilitate patient pathways diagnosis.Approach:To address this scientific challenge, this paper proposes to consider the statistical stability phenomenon in an event log, and it introduces the stable heuristic miner algorithm as its contribution. To evaluate the applicability of the proposed algorithm, a case study has been presented to monitor patient pathways in a medical consultation platform.Originality:Thanks to this algorithm, the value of thresholds will be automatically calculated at the statistically stable limits. Hence, instead of several models, only one process model will be discovered. To the best of our knowledge, applying the statistical stability phenomenon in the context of process mining to discover a reference process model from location event logs has not been addressed before.Findings: Practical implications-The results enabled to remove the uncertainty to determine the threshold that represents the common patient pathways and consequently, leaving some room for potential diagnosis of the pathways
Improvements for a Fully Consistent Description of the New Semi-Empirical Vapor Density Model for Pure Compounds
No full textInternational audienceIn chemical engineering, surrogate functions are commonly used in modeling thermodynamic properties of pure compounds because they are often more accurate than equations of state. In 2020, we presented a semi-empirical model describing the vapor density from the reduced triple point temperature to about a reduced temperature of 0.97 with only one temperature-dependent term. However, in many cases the temperature range up to critical temperature is necessary. Therefore, the existing semi-empirical model was extended by another temperature-dependent term. This allows the vapor density to be described from the triple point temperature up to the critical temperature. This model has the additional advantage that it can predict the vapor pressure data from vapor density data. Therefore, this model can also be used for thermodynamic consistency testing. This is not possible with conventionally known surrogate models for describing vapor density. The model was successfully tested using fluoromethane (R41) and difluoromethane (R32) as examples