Jóvenes y política en Marruecos: Las causas de la no participación institucional

La non-participation à travers les institutions formelles de la politique est une forte tendance chez les jeunes marocains. Les données qualitatives et quantitatives d’une recherche menée en 2015 et 2016 montrent que la majorité des jeunes ne s’engage pas à travers les partis politiques et les élections. Ceci dit, ils ne sont pas politiquement apathiques, beaucoup d’entre eux expriment un grand intérêt pour la politique et un fort sentiment d'agencéité. Le fait que l'intérêt politique des jeunes ne se transforme pas en action suggère leur désenchantement avec l'offre politique. Bien que des facteurs tels que l'éducation, le genre et le niveau de connaissance politique soient importants pour comprendre les motifs de la participation ou de la non-participation des jeunes, cet article met en exergue l’impact de la centralité du pouvoir et des pratiques politiques établies sur le non engagement des jeunes. Au Maroc, la sphère de la participation politique a été élargie depuis les années 1990. Néanmoins, dans un régime caractérisé par la centralité du pouvoir entre les mains de la monarchie / makhzen, une scène partisane contrôlée et des institutions politiques discréditées, les citoyens sont conscients des limites de leur influence sur les décisions publiques. Le terrain que nous avons mené nous permet de conclure que les politiciens et les partis sont déconnectés des réalités et des préoccupations des jeunes. Par ailleurs, la majorité se sent exclue des processus décisionnels. Même lorsqu’ils participent à des discussions et débats au sein de leurs institutions d’appartenance, les jeunes estiment que leurs avis et attentes ne sont pas pris en considération. La non-participation peut être considérée comme un acte conscient susceptible de saper la légitimité du système. Le désengagement des jeunes de la sphère formelle de la participation et leur désenchantement avec l’offre politique peuvent contribuer à long terme au recours à des moyens antidémocratiques et non pacifiques pour faire entendre leurs voixLa no participación a través de las instituciones políticas formales es una tendencia muy marcada entre los jóvenes marroquíes. Los datos cualitativos y cuantitativos de una investigación llevada a cabo en 2015 y 2016 muestran que la mayoría de los jóvenes no participa en los partidos políticos y las elecciones. Dicho esto, no son políticamente apáticos, muchos de ellos expresan un gran interés por la política y un fuerte sentido de agencia. El hecho de que el interés político de los jóvenes no se convierta en acción sugiere su desencanto con la oferta política. Aunque factores como la educación, el género y el nivel de conocimiento político son importantes para comprender los motivos de la participación o no participación de los jóvenes, este artículo destaca el impacto de la centralidad del poder y las prácticas políticas establecidas sobre la existencia de este no compromiso de los jóvenes. En Marruecos, la esfera de la participación política se ha ampliado desde la década de 1990. Sin embargo, en un régimen caracterizado por la centralidad del poder en manos de la monarquía / makhzen, una escena partidista controlada e instituciones políticas desacreditadas, los ciudadanos son conscientes de los límites de su influencia en las decisiones públicas. El trabajo de campo que hemos realizado nos permite concluir que los políticos y los partidos están desconectados de las realidades y preocupaciones de los jóvenes. Además, la mayoría de estos últimos se siente excluida de los procesos de toma de decisiones. Incluso cuando participan en discusiones y debates dentro de sus propias organizaciones, los jóvenes sienten que sus opiniones y expectativas no se tienen en cuenta. La no participación puede considerarse como un acto consciente que socava la legitimidad del sistema. La separación de los jóvenes de la esfera formal de participación y su desencanto con la oferta política pueden contribuir a que, a largo plazo, recurran al uso de medios antidemocráticos y no pacíficos para hacer oír su vo

Hybrid prognostic method applied to mechatronic systems.

International audienceFault detection and isolation, or fault diagnostic, of mechatronic systems has been subject of several interesting works. Detecting and isolating faults may be convenient for some applications where the fault does not have severe consequences on humans as well as on the environment. However, in some situations, diagnosing faults may not be sufficient and one needs to anticipate the fault. This is what is done by fault prognostics. This latter activity aims at estimating the remaining useful life of systems by using three main approaches: data-driven prognostics, model-based prognostics and hybrid prognostics. In this paper, a hybrid prognostic method is proposed and applied on a mechatronic system. The method relies on two phases: an offline phase to build the behavior and degradation models and an online phase to assess the health state of the system and predict its remaining useful life

Scheduling predictive maintenance in flow-shop.

International audienceAvailability of production equipments is one major issue for manufacturers. Predictive maintenance is an answer to prevent equipment from risk of breakdowns while minimizing the maintenance costs. Nevertheless, conflicts could occur between maintenance and production if a maintenance operation is programmed when equipment is used for production. The case studied here is a flow-shop typology where machines could be maintained once during the planning horizon. Machines are able to switch between two production modes. A nominal one and a degraded one where machine run slowly but increase its remaining useful life. We propose a mixed integer programming model for this problem with the makespan and maintenance delays objective. It allows to find the best schedule of production operation. It also produces, for each machine, the control mode and if necessary the preventive maintenance plan

Joint prediction of observations and states in time-series based on belief functions

International audienceForecasting the future states of a complex system is a complicated challenge that is encountered in many industrial applications covered in the community of Prognostics and Health Management (PHM). Practically, states can be either continuous or discrete: Continuous states generally represent the value of a signal while discrete states generally depict functioning modes reflecting the current degradation. For each case, specific techniques exist. In this paper, we propose an approach based on case-based reasoning that jointly estimates the future values of the continuous signal and the future discrete modes. The main characteristics of the proposed approach are the following: 1) It relies on the K-nearest neighbours algorithm based on belief functions theory; 2) Belief functions allow the user to represent his partial knowledge concerning the possible states in the training dataset, in particular concerning transitions between functioning modes which are imprecisely known; 3) Two distinct strategies are proposed for states prediction and the fusion of both strategies is also considered. Two real datasets were used in order to assess the performance in estimating future break-down of a real system

Static et dynamic scheduling of maintenance activities under the constraints of skills.

International audienceSkill management in industry is one of the most important factors required in order to obtain optimal performance of the production system. This is of particular importance in the field of maintenance where the different practical knowledge or skills are the working tools used. We address, in this paper, both the assignment and scheduling problems that may be found in a maintenance service. Each task that has to be performed is characterized by the level of skill required. The problem lies with making the decision of which time is the right time for the assignment and scheduling of the correct resource to do the task. We introduce both static and dynamic scheduling, applied to the maintenance task assignment. To confer a maximum robustness to the obtained schedule, tha approach proposed in this paper is completed by a proactive methodology which takes into account possible variations

Dynamic scheduling of maintenance activities under uncertainties.

International audienceCompetencies management in the industry is one of the most important keys in order to obtain good performance with production means. Especially in maintenance services field where the dierent practical knowledges or skills are their working tools. We address, in this paper, the both assignment and scheduling problem that can be found in a maintenance service. Each task that has to be performed is characterized by a competence level required. Then, the decision problem of assignment and scheduling lead to find the good resource and the good time to do the task. For human resources, all competence levels are dierent, they are considered as unrelated parallel machines. Our aim is to assign dynamically new tasks to the adequate resources by giving to the maintenance expert a choice between the robustest possibilities

Novel failure prognostics approach with dynamic thresholds for machine degradation.

International audienceEstimating remaining useful life (RUL) of critical machinery is a challenging task. It is achieved through essential steps of data acquisition, data pre-processing and prognostics modeling. To estimate RUL of a degrading machinery, prognostics modeling phase requires precise knowledge about failure threshold (FT) (or failure definition). Practically, degrading machinery can have different levels (states) of degradation before failure, and prognostics can be quite complicated or even impossible when there is absence of prior knowledge about actual states of degrading machinery or FT. In this paper a novel approach is proposed to improve failure prognostics. In brief, the proposed prognostics model integrates two new algorithms, namely, a Summation Wavelet Extreme Learning Machine (SWELM) and Subtractive-Maximum Entropy Fuzzy Clustering (S-MEFC) to predict degrading behavior, automatically identify the states of degrading machinery, and to dynamically assign FT. Indeed, for practical reasons there is no interest in assuming FT for RUL estimation. The effectiveness of the approach is judged by applying it to real dataset in order to estimate future breakdown of a real machinery

Bayesian based fault diagnosis : application to an electrical motor

International audienceIn the literature, several fault diagnosis methods, qualitative as well quantitative, are proposed. The main objective of these methods is in one hand, to allow detection, isolation and identification of faults ; and in the other hand to insure safety, reliability and availability of systems. This paper presents a diagnosis method based on the use of a new and suitable mathematical tool : bayesian networks. Their learning and inference capabilities allow to model complex processes by taking into account the uncertainty and the incompleteness of the provided knowledge. Furthermore, the graphical representation of causal relations existing between variables, events or physical phenomena makes bayesian networks easy to use and leads to models which can be understandable by even a non specialist of the modeled domain

Residual-based failure prognostic in dynamic systems.

International audienceThis paper deals with failure prognostic in dynamic systems. The system's remaining useful life is estimated based on residual signals. This supposes the possibility to build a dynamic model of the system by using the bond graph tool, and the existence of a degradation model in order to predict its future health state. The choice of bond graph is motivated by the fact that it is well suited for modeling physical systems where several types of energies are involved. In addition, it allows to generate residuals for fault diagnostic and prognostic. The proposed method is then applied on a simple dynamic model of a hydraulic system to show its feasibility

A fuzzy approach of online reliability modeling and estimation.

International audienceIn maintenance field, traditional concepts like preventive and corrective strategies are progressively completed by new ones like predictive and proactive maintenance. For that purpose, a fundamental task is the estimation of the provisional reliability of equipment as well as its remaining useful life. However, traditional approach of reliability based on statistical analysis can be not suitable as very few knowledge can be available. Within this frame, the general purpose of the work is to explore the way of developing a fuzzy approach of on-line reliability modeling and estimation in order to take into account the uncertainty as welle as possible. A federative point of view of the reliability modeling process and of the prognostic of degradation activity is proposed. From that, two ways of considering uncertainty in reliability modeling are discussed (probabilistic, fuzzy/possibility approaches), and the inherent limits of both methods are pointed out