Ce projet de thèse s’intéresse à la problématique de la modélisation analytique de la planification de production et des capacités, des stratégies de sous-traitance, de la politique de maintenance et de contrôle de la qualité et à son optimisation grâce à des modèles plus aptes à prendre en compte le couplage entre ces fonctions. Quelques études existent déjà, mais elles n’intègrent cependant pas toujours tous les paramètres, ni la collaboration qui peut se créer au sein d’une chaîne logistique. L’idée est de proposer des modèles les plus généraux possible, et surtout facilement adaptable aux données réelles de l’entreprise, ces modèles seront ensuite utilisés pour évaluer les performances et optimiser ces stratégies. Le développement durable est un sujet en plein essor du fait des enjeux sociétaux qui y sont attachés. Nous nous proposons d’intégrer plusieurs questions environnementales qui peuvent être liées à la production, à la sous-traitance, à la maintenance et à la qualité. L’objectif est d’évaluer les implications environnementales de la chaîne dans un contexte de la logistique inverse. Ces contributions, ainsi que les coûts associés ne peuvent être ignorées dans nos modèles. Dans nos travaux, les méthodes exactes seront utilisées pour résoudre et valider des problèmes. Parfois, il est difficile de résoudre des problèmes complexes en utilisant les techniques d'optimisation classiques. La complexité augmente également avec l'augmentation du nombre de paramètres et/ou des variables de décision. Dans de tels cas, des algorithmes heuristiques ou métaheuristiques seront utilisés, ces algorithmes sont jugés plus efficaces pour générer une solution optimale/quasi-optimale pour des problèmes complexes avec des temps de calcul moins. Intégrer dans les modèles d’optimisation l’aspect incertain pourra apporter des réponses plus réalistes que celles disponibles à l’heure actuelle. La logique floue, la théorie des probabilités floues ou des possibilités peuvent être adaptés pour prendre en compte les contraintes spécifiquement industrielles. Une telle approche est originale et peu de publications traitent actuellement cette problématique.

We propose a new approach for modeling a High Electron Mobility Transistor (HEMT) using that of Gaussian Process Regression one (GPR), to improve the current-voltage characteristics of HEMT transistor for using in electronic and biological domain or any other domain that needs it. The study and development of a new Atlas Silvaco device are taking into account the impact of several geometric and electric parameters; we focus on the electrical performances of the double gate field plate In0.2Ga0.8As/Al0.3Ga0.7As HEMT including double heterostructure; we compare the numerical simulation using 2D Atlas Silvaco simulator with the extracted experimental results. Then we validate our model by GPR approach. The GPR approach opens promising opportunities for devices modeling without knowing too much the device physics properties. The obtained results give better performances which lead to fabricate devices with better electrical properties for promoting further investigation.

We propose a new approach for modeling a High Electron Mobility Transistor (HEMT) using that of Gaussian Process Regression one (GPR), to improve the current-voltage characteristics of HEMT transistor for using in electronic and biological domain or any other domain that needs it. The study and development of a new Atlas Silvaco device are taking into account the impact of several geometric and electric parameters; we focus on the electrical performances of the double gate field plate In0.2Ga0.8As/Al0.3Ga0.7As HEMT including double heterostructure; we compare the numerical simulation using 2D Atlas Silvaco simulator with the extracted experimental results. Then we validate our model by GPR approach. The GPR approach opens promising opportunities for devices modeling without knowing too much the device physics properties. The obtained results give better performances which lead to fabricate devices with better electrical properties for promoting further investigation.

We propose a new approach for modeling a High Electron Mobility Transistor (HEMT) using that of Gaussian Process Regression one (GPR), to improve the current-voltage characteristics of HEMT transistor for using in electronic and biological domain or any other domain that needs it. The study and development of a new Atlas Silvaco device are taking into account the impact of several geometric and electric parameters; we focus on the electrical performances of the double gate field plate In0.2Ga0.8As/Al0.3Ga0.7As HEMT including double heterostructure; we compare the numerical simulation using 2D Atlas Silvaco simulator with the extracted experimental results. Then we validate our model by GPR approach. The GPR approach opens promising opportunities for devices modeling without knowing too much the device physics properties. The obtained results give better performances which lead to fabricate devices with better electrical properties for promoting further investigation.

We propose a new approach for modeling a High Electron Mobility Transistor (HEMT) using that of Gaussian Process Regression one (GPR), to improve the current-voltage characteristics of HEMT transistor for using in electronic and biological domain or any other domain that needs it. The study and development of a new Atlas Silvaco device are taking into account the impact of several geometric and electric parameters; we focus on the electrical performances of the double gate field plate In0.2Ga0.8As/Al0.3Ga0.7As HEMT including double heterostructure; we compare the numerical simulation using 2D Atlas Silvaco simulator with the extracted experimental results. Then we validate our model by GPR approach. The GPR approach opens promising opportunities for devices modeling without knowing too much the device physics properties. The obtained results give better performances which lead to fabricate devices with better electrical properties for promoting further investigation.

The purpose of this paper is to present a simplified model of inductively coupled plasma (ICP). The study of the effect of parameters such as current and number of turns in the coil is simulated using Comsol Multiphysics 3.5 by applying the fluid dynamic models that are generally appropriate for the investigation of inductively coupled plasmas.

The purpose of this paper is to present a simplified model of inductively coupled plasma (ICP). The study of the effect of parameters such as current and number of turns in the coil is simulated using Comsol Multiphysics 3.5 by applying the fluid dynamic models that are generally appropriate for the investigation of inductively coupled plasmas.