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La recherche d'adaptativité et de réactivité dans le pilotage des cellules de production implique la répartition de l'intelligence décisionnelle. Une corollaire en est la difficulté à maitriser et à optimiser la prise de décision en temps réel. Le but de ces travaux est d'étudier l'apport des systèmes multi-agents pour le pilotage des cellules adaptatives de production. L'intérêt de modéliser le système de pilotage par un systeme multi-agents est d'une part de construire le comportement de la cellule non plus par une approche fonctionnelle descendante, mais par un assemblage de comportements locaux, ce qui permet de décrire le fonctionnement d'un systeme complexe, alors qu'une description globale n'est pas forcement possible. Cela permet d'autre part de décrire le scenario de production sous la forme d'une succession d'états a obtenir, et non plus comme une séquence d'actions a réaliser, ce qui permet a la cellule de s'auto organiser en fonction des objectifs a obtenir et de l'état actuel de la cellule. Une population d'agents réactifs modélisant les comportements locaux est confrontée a des décisions multiplaces et conflictuelles et s'organise grâce a l'interaction de leur comportement afin d'obtenir un comportement global cohérent. Pour valider notre approche, nous l'avons applique au contrôleur de la cellule expérimentale de fraisage de LURPA. Deux exemples de production sur la cellule sont traités, une production dite normale permet de mettre en évidence le séquencement en temps réel des taches de la cellule et une production à statut prioritaire permet de mettre en évidence la capacité du contrôleur de cellule à réagir à cette perturbation, qu'est le lancement de cette production
This proceedings contains numerous papers presenting the latest results of applied research and the most advanced industrial applications in engineering and manufacturing. Topics include: a panorama of the main international research programmes in the field of CIM in Japan, the United States, and in Europe (ESPRIT, EUREKA) and a number of presentations of the most advanced CIM applications in the world. Also presented is current technology concerning such topical subjects as: feature-based reasoning in engineering, CAD modelling techniques, concurrent engineering, modelling techniques for manufacturing systems, the various aspects of integration in CIM between the manufacturing functions (e.g., robotics, flexible manufacturing system, quality control), expert systems in maintenance, methodological approaches to design and implement CIM systems, human and economic aspects, planning and scheduling as tools for integration, and the design of information systems in CIM (structures, object-oriented approach).
Many, if not most, industrially important fermentation and bioreactor operations are carried out in fed-batch mode, producing a wide variety of products. In spite of this, there is no single book that deals with fed-batch operations. This is the first book that presents all the necessary background material regarding the 'what, why and how' of optimal and sub-optimal fed-batch operations. Numerous examples are provided to illustrate the application of optimal fed-batch cultures. This unique book, by world experts with decades of research and industrial experience, is a must for researchers and industrial practitioners of fed-batch processes (modeling, control and optimization) in biotechnology, fermentation, food, pharmaceuticals and waste treatment industries.
The purpose of this study is to identify new synergistic pathways between climate change mitigation and adaptation policies in Cameroon using an approach based on a literature review of the political processes that led to the introduction of the two strategies. The common feature of the two political processes is the absence of strategy in Cameroon. The country is finding it difficult to assimilate and coordinate these processes at the national level. More attention is being given to mitigation than to adaptation. In any case, it is difficult to formulate any political options without complete studies on the responses to the drivers of deforestation and forest degradation and on the vulnerability of the forest populations and their capacity to absorb climate shocks.
This book is concerned with Artificial Intelligence (AI) concepts and techniques as applied to industrial decision making, control and automation problems. The field of AI has been expanded enormously during the last years due to that solid theoretical and application results have accumulated. During the first stage of AI development most workers in the field were content with illustrations showing ideas at work on simple problems. Later, as the field matured, emphasis was turned to demonstrations that showed the capability of AI techniques to handle problems of practical value. Now, we arrived at the stage where researchers and practitioners are actually building AI systems that face real-world and industrial problems. This volume provides a set of twenty four well-selected contributions that deal with the application of AI to such real-life and industrial problems. These contributions are grouped and presented in five parts as follows: Part 1: General Issues Part 2: Intelligent Systems Part 3: Neural Networks in Modelling, Control and Scheduling Part 4: System Diagnostics Part 5: Industrial Robotic, Manufacturing and Organizational Systems Part 1 involves four chapters providing background material and dealing with general issues such as the conceptual integration of qualitative and quantitative models, the treatment of timing problems at system integration, and the investigation of correct reasoning in interactive man-robot systems.
This volume constitutes refereed proceedings of the Third International Conference on Smart Applications and Data Analysis, SADASC 2020, held in Marrakesh, Morocco. Due to the COVID-19 pandemic the conference has been postponed to June 2020. The 24 full papers and 3 short papers presented were thoroughly reviewed and selected from 44 submissions. The papers are organized according to the following topics: ontologies and meta modeling; cyber physical systems and block-chains; recommender systems; machine learning based applications; combinatorial optimization; simulations and deep learning.
Modelling environmental dynamics is critical to understanding and predicting the evolution of the environment in response to the large number of influences including urbanisation, climate change and deforestation. Simulation and modelling provide support for decision making in environmental management. The first chapter introduces terminology and provides an overview of methodological modelling approaches which may be applied to environmental and complex dynamics. Based on this introduction this book illustrates various models applied to a large variety of themes: deforestation in tropical regions, fire risk, natural reforestation in European mountains, agriculture, biodiversity, urbanism, climate change and land management for decision support, etc. These case studies, provided by a large international spectrum of researchers and presented in a uniform structure, focus particularly on methods and model validation so that this book is not only aimed at researchers and graduates but also at professionals.
Innovate Bristol highlights and celebrates those companies and individuals that are actively working at building a better tomorrow for all. Innovation Ecosystems thrive through the involvement and support of companies and individuals from all industries, which is why the Innovate series not only focuses on the innovators but also those people whom the Innovation Ecosystem, would not be able to thrive without.