L’objectif de ces travaux est de développer une méthodologie de génération automatique de gammes d’usinage optimises et innovantes qui permettent aux sous-traitants aéronautiques de faire face aux problématiques de productivité et de compétitivité actuelles. Dans un premier temps, un état de l’art sur les systèmes existants de génération de gammes est présenté et permet d’introduire les limites des systèmes actuels. Une méthodologie en quatre étapes est ensuite proposée, permettant à l’utilisateur d’obtenir des gammes d’usinage optimisées respectant son savoir-faire et son expérience et introduisant de l’innovation. Cette méthodologie s’appuie sur une représentation du comportement décisionnel des méthodistes dans une situation donnée ainsi que face au risque à l’industrialisation et élargit la formalisation de la performance d’une gamme en prenant en compte d’autres critères de performance autres que le temps d’usinage ou le coût global. Ainsi, un état de l’art sur les méthodes d’aide à la décision multicritère permet de sélectionner la méthode pour l’agrégation des performances par rapport à la problématique industrielle. Après une description géométrique et technologique de la pièce et la création par les méthodistes, d’opérations d’usinage élémentaires, un algorithme génétique est utilisé pour générer des gammes optimisées. Lors d’une dernière étape, la méthodologie présente les meilleures gammes générées au méthodiste et l’utilisation de la théorie du choix social lui permet de cibler les gammes les plus performantes à implanter, en intégrant un critère de risque à l’industrialisation. Cette méthodologie a été appliquée à une pièce de train d’atterrissage usinée en alliage de Titane et a permis une diminution de 25% du temps d’usinage tout en augmentant la fiabilisation. Des perspectives d’amélioration de l’outil d’aide à la décision, à diverses étapes de la méthodologie, sont enfin proposées. / The objective of this work is to develop a Computer-Aided Process Planning (CAPP) methodology to allow aeronautical subcontractors to face the current productivity and competitiveness problems. To start, a state of the art on the existing CAPP systems is presented and introduce the limits of the current systems. A four-step methodology is then proposed, allowing the user to obtain optimized machining ranges respecting his know-how and experience and introducing innovation. This methodology is based on a representation of the decision-making behavior of the process planners in a given situation as well as the risk of industrialization and broadens the formalization of the performance by taking into account performance criteria other than the machining time or cost. Thus, a state of the art on multicriteria decision-making methods helps to select the method for the aggregation of performance in relation to the industrial problem. After a geometrical and technological description of a mechanical part and the creation by the process planners of elementary machining operations, a genetic algorithm is used to generate optimized ranges. In a final step, the methodology presents the best process plans generated to the process planners and the use of the social choice theory allows to target the most efficient ones to choose, integrating a risk criterion based on tool deflection. This methodology was applied to a Titanium alloy machined landing gear part and allowed a 25% reduction in machining time while increasing reliability. Finally, prospects for improving the decision-making tool at various stages of the methodology are proposed.

The diploma thesis focuses on decision-making process during choosing the form of business. It finds and describes the criteria that should be considered in this selection. These criteria compares and evaluates on a model situation in relation to the five chosen variants. The thesis contains suggestions of precedures leading to the choosing the suitable form of business, characterizes their advantages and disadvantages and presents situations in which the procedure is convenient to use.

Dans cette thèse, nous nous sommes intéressés à l'analyse des données de simulation issues du modèle agro-hydrologique TNT. Les objectifs consistaient à élaborer des méthodes d'analyse des résultats de simulation qui replacent l'utilisateur au coeur du processus décisionnel, et qui permettent d'analyser et d'interpréter de gros volumes de données de manière efficace. La démarche développée consiste à utiliser des méthodes d'analyse multidimensionnelle interactive. Tout d'abord, nous avons proposé une méthode d'archivage des résultats de simulation dans une base de données décisionnelle (i.e. entrepôt de données), adaptée au caractère spatio-temporel des données de simulation produites. Ensuite, nous avons suggéré d'analyser ces données de simulations avec des méthodes d'analyse en ligne (OLAP) afin de fournir aux acteurs des informations stratégiques pour améliorer le processus d'aide à la prise de décision. Enfin, nous avons proposé deux méthodes d'extraction de skyline dans le contexte des entrepôts de données afin de permettre aux acteurs de formuler de nouvelles questions en combinant des critères environnementaux contradictoires, et de trouver les solutions compromis associées à leurs attentes, puis d'exploiter les préférences des acteurs pour détecter et faire ressortir les données susceptibles de les intéresser. La première méthode EC2Sky, permet un calcul incrémental et efficace des skyline en présence de préférences utilisateurs dynamiques, et ce malgré de gros volumes de données. La deuxième méthode HSky, étend la recherche des points skyline aux dimensions hiérarchiques. Elle permet aux utilisateurs de naviguer le long des axes des dimensions hiérarchiques (i.e. spécialisation / généralisation) tout en assurant un calcul en ligne des points skyline correspondants. Ces contributions ont été motivées et expérimentées par l'application de gestion des pratiques agricoles pour l'amélioration de la qualité des eaux des bassins versants agricoles, et nous avons proposé un couplage entre le modèle d'entrepôt de données agro-hydrologiques construit et les méthodes d'extraction de skyline proposées. / This thesis concerns the analysis of simulation data generated by the agrohydrological model TNT. Our objective is to develop analytical methods for massive simulation results. We want to place the user at the heart of the decision-making process, while letting him handle and analyze large amounts of data in a very efficient way. Our first contribution is an original approach N-Catch, relying on interactive multidimensional analysis methods for archiving simulation results in a decisional database (i.e. data warehouse) adapted to the spatio-temporal nature of the simulation data. In addition, we suggest to analyze the simulation data with online analytical methods (OLAP) to provide strategic information for stakeholders to improve the decision making process. Our second contribution concern two methods for computing skyline queries in the context of data warehouses. These methods enable stakeholders to formulate new questions by combining conflicting environmental criteria, to find compromise solutions associated with their expectations, and to exploit the stakeholder preferences to identify and highlight the data of potential interest. The first method EC2Sky, focuses on how to answer efficiently and progressively skyline queries in the presence of several dynamic user preferences despite of large volume of data. The second method HSky, extends the skyline computation to hierarchical dimensions. It allows the user to navigate along the dimensions hierarchies (i.e. specialize / generalize) while ensuring the online computation of associated skylines. Finally, we present the application of our proposals for managing agricultural practices to improve water quality in agricultural watersheds. We propose a coupling between the agro-hydrological data warehouse model N-Catch and the proposed skyline computation methods.

À l'heure où toute décision stratégique doit être conforme aux principes de la durabilité, l'évaluation des conséquences environnementales, économiques et sociales d'un choix d'ingénierie s'avère nécessaire. Parmi les outils d'évaluation des systèmes et de leurs conséquences, l'analyse de cycle de vie (ACV) dérivée de la pensée cycle de vie s'est imposée comme la méthode la plus adaptée à un tel niveau de décision. Historiquement focalisée sur les impacts environnementaux, l'ACV a naturellement étendue son champ d'évaluation aux aspects économiques, sociaux et d'ingénierie pour devenir une analyse de la durabilité (AdCV) des systèmes. L'AdCV est ainsi en train d'émerger et nécessite des propositions d'améliorations méthodologiques et des applications concrètes pour devenir robuste et applicable. Cette étude présente l'évaluation de la durabilité d'un système dans le contexte de l'agro-industrie oléicole. À cet effet, elle propose une approche intégrée d’évaluation de la durabilité basée sur l’AdCV couplée à la modélisation des processus et des procédés et, l'analyse multicritère pour l'aide à la décision. Une première partie traite des concepts de durabilité, d'ingénierie et d'agro-industrie oléicole à travers une analyse de la littérature scientifique. Dans la deuxième partie, l'approche d'évaluation de la durabilité proposée est décrite, formalisée et implémentée dans la solution logicielle « EcOlive » à l'aide d'outils empruntés à la modélisation des systèmes. Enfin, la troisième partie présente les résultats de l’application de l’approche à l’agro-industrie oléicole en s’appuyant sur un ensemble de données terrain récoltées dans le cadre du projet européen OiLCA. / Nowadays, any strategic decision must be in accordance with the sustainability principles. Therefore, companies need to evaluate the consequences of their activities and products onto environment, economy and society. Life cycle assessment (LCA) from Life cycle thinking (LCT) is one of the major environmental impact evaluation methods for product, process or service and the trends is to integrate economic and social aspects to become a life cycle sustainability assessment (LCSA). However, LCSA is still in its infancy and needs methodological proposals to be applicable. This study presents sustainability assessment in the olive oil agro-industrial context. In doing so, a systemic approach based on the coupling between LCSA, enterprise modeling, chemical process modeling and multicriteria analysis is proposed. The approach is then validated by the development of the software solution “ Ecolive ” for sustainability assessment of olive oil production. This application relies on field data collected under the European OiLCA project.

This diploma thesis targets the evaluation of fifteen chosen EU countries using the methods of multicriteria decision-making. The topic is elaborated from the perspective of a student of the University of Economics, Prague, who chooses a suitable country to gain experience abroad. Students' preferences are recorded in a questionnaire and grouped using direct weights estimation method. The ORESTE, WSA, TOPSIS, PROMETHEE II and MAPPAC methods are described in the thesis and applied to the data using an add-on of Microsoft Excel -- Sanna. Since the questionnaire contains a question on the students' subjective ranking of countries, it is possible to compare the two rankings (subjective and calculated) to determine whether they are comparable and the students' decision-making is consistent.

A competitividade de uma organização e, consequentemente, sua prosperidade perante concorridos mercados, depende muito da capacidade de inovação e aprimoramento de seus produtos/serviços e processos. A procura por melhores padrões de manufatura e serviços prestados aos clientes, além das aplicações de novas técnicas gerenciais, de melhoria contínua, de otimização e de tomada de decisão, têm atraído a atenção das organizações. O esforço criativo humano deve propor abordagens de caráter competitivo, combinando ferramentas e técnicas, conhecidas ou não, a fim de melhorarem seus desempenhos. Assim, o objetivo desta tese foi propor uma estrutura analítica integrando de forma sequencial o processo de melhoria contínua DMAIC e o método de análise multicriterial para tomada de decisão Analytic Hierarchy Process (AHP), com vistas às aplicações em operações de distribuição física de bebidas. Em um primeiro momento, por meio de uma pesquisa bibliográfica, foi proposta uma estrutura geral, denominada Estrutura Analítica DMAIC/AHP, envolvendo as teorias supracitadas. Além disso, com o auxílio de um estudo de caso, foi proposta uma estrutura detalhada para a tentativa de melhoria da operação de distribuição física de bebidas em uma empresa na cidade de Ribeirão Preto. O foco esteve também na oportunidade de se obter maior conhecimento do processo em estudo e melhorar o embasamento para a tomada de decisão. A aplicação da estrutura analítica foi dividida em três fases: fase 1 - definições para o projeto de melhoria; fase 2 - condução do processo de melhoria em si; e fase 3 (denominada metafase) - responsável por monitorar/acompanhar as atividades do projeto. A aplicação em um caso real permitiu a proposta de atividades e ferramentas para entendimento e aperfeiçoamento do processo; além de alternativas de decisão frente aos problemas encontrados; deu embasamento para a tomada de decisão no momento de se implementarem as melhorias e apresentou instrumentos para manutenção e controle das alterações propostas no projeto. Um ganho evidente com a junção das teorias foi que houve um auxílio mútuo entre elas. Dessa forma, o processo de melhoria contínua DMAIC, por meio de suas etapas minuciosas de conhecimentos de processos e de causas de problemas, pôde embasar de forma robusta a definição do modelo hierárquico do AHP, desde o objetivo geral a ser atingido, passando pelos critérios de decisão, até se chegar às alternativas de decisão propostas para o processo em estudo. Por outro lado, como o DMAIC não apresenta um método de tomada de decisão atraente, o AHP pôde auxiliar na tomada de decisão multicriterial de forma mais organizada, consistente e assertiva. / The competitiveness of an organization and consequently its prosperity before competitive markets, depends widely on the capacity for innovation and improvement of its products/services and processes. The pursuit for better manufacturing standards and services provided to customers, in addition to the applications of new management techniques, continuous improvement, optimization and decision-making, have attracted attention of organizations. The human creative effort should propose approaches of competitive basis, combining tools and techniques, known or not, in order to improve their performance. Thus, the objective of this thesis was to propose an analytical structure integrating sequentially the process of continuous improvement DMAIC of Six Sigma and the multi-criteria analysis method for decision making Analytic Hierarchy Process (AHP), in order to apply in real cases in beverage industries. At first, through a literature search, it was proposed a general structure, called Analytical Structure DMAIC/AHP, involving the above theories. In addition, with a case study aid, it was proposed a detailed structure attempting to improve the operation of physical distribution for beverages in a company in the city of Ribeirão Preto. The focus was also on the opportunity to gain greater knowledge of the process under study and improve the foundation for decision making. The application of analytical structure was divided into three phases: phase 1 - definitions for the improvement project; phase 2 - implementation of the improvement process itself; and phase 3 (called metaphase) - responsible for monitoring/following the activities of the project. The application in a real case allowed the proposal of activities and tools for the understanding and improvement of the process, as well as possibilities for more alternatives to problems encountered; provided foundation for decision making at the time of implementing the improvements and presented tools for maintenance and control of changes proposed in the project. An obvious gain from the junction of the theories was that there was a mutual aid between them. Thus, the process of continuous improvement DMAIC, through its detailed stages of knowledge of processes and causes of problems could robustly base the definition of the hierarchical model of AHP, since the overall objective to be attained, passing through the decision criteria, until they get to the alternatives of decisions proposed for the process under study. On the other hand, as the DMAIC does not present an attractive method of decision-making, AHP could assist in multi-criteria decision making more organized, consistent and assertive.

A seleção de fornecedores tem impacto significante no custo e na qualidade de produtos manufaturados. Por isso, a seleção de fornecedores passou a ser vista como uma atividade bastante crítica para o desempenho da empresa compradora. Muitos estudos da literatura propõem o uso dos métodos multicritério fuzzy TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) e fuzzy AHP (Analytic Hierarchy Process) para apoiar a seleção de fornecedores. Contudo, não são encontrados estudos que avaliem o desempenho destes métodos quando usados neste domínio de problema. Diante desta lacuna, este estudo compara os métodos fuzzy TOPSIS (CHEN, 2000) e fuzzy AHP (CHANG, 1996) no apoio à seleção de fornecedores. Esta pesquisa utiliza uma abordagem quantitativa descritiva empírica, baseada em modelagem e simulação. Os métodos fuzzy TOPSIS e fuzzy AHP foram aplicados em um caso ilustrativo de seleção de fornecedores. O desempenho dos fornecedores e o peso dos critérios foram avaliados por um especialista de uma empresa. Modelos de simulação foram implementados usando MATLAB® e aplicados na seleção de fornecedores de uma empresa de uma cadeia de suprimentos automotiva. Cinco fornecedores foram avaliados em relação à qualidade, custo, entrega, perfil e relacionamento. O peso dos critérios e o desempenho dos fornecedores foi avaliado por meio da opinião de um especialista da empresa. Posteriormente, os métodos fuzzy TOPSIS e fuzzy AHP foram comparados em relação à capacidade de apoiar a decisão em grupo, qualificação de fornecedores, escolha final de fornecedores, situações de compra e modelagem de decisões sob incerteza. A eficiência dos métodos em relação à complexidade computacional e à interação requerida com o usuário também foi comparada. Os resultados mostraram que o fuzzy TOPSIS é mais flexível e mais adequado que o fuzzy AHP para modelar diferentes tipos de cenários de seleção de fornecedores. A realização desta discussão é sugerida por Ertugrul e Karakasoglu (2008), e é relevante para ajudar pesquisadores e gestores na escolha de abordagens efetivas para lidar com diferentes cenários de seleção de fornecedores. / Supplier selection has a significant influence on the cost, quality and delivery of products of the buying company. Therefore, supplier selection has become a very critical activity to the performance of the buying company. Several studies presented in the literature propose the use of fuzzy TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) and fuzzy AHP (Analytic Hierarchy Process) to aid the decision process of supplier selection. However, there are no comparative studies of these two methods when applied to the problem of supplier selection. Thus, this paper presents a comparative analysis of the methods fuzzy TOPSIS (Chen, 2000) and fuzzy AHP (Chang, 1996) applied to the problem of supplier selection. A descriptive quantitative approach was adopted as the research method. Algorithms of the methods fuzzy TOPSIS and fuzzy AHP were developed in Matlab© and applied to the selection of suppliers of a company in the automotive production chain. Five suppliers were evaluated regarding quality of conformance, cost, delivery, profile and relationship. The weight of the criteria and the performance of the suppliers were evaluated by specialist opinion from the studied company. The methods Fuzzy TOPSIS e Fuzzy AHP were compared in terms of ability to support the group decision, supplier qualification, final choice of suppliers, buying situations and modeling decisions under uncertainty. The efficiency of the methods with respect to computational complexity and the required user interaction was also compared. The comparative analysis shows that Fuzzy TOPSIS presents better than Fuzzy AHP performance, especially in scenarios in wich many alternatives are evaluated. Thus, Fuzzy TOPSIS is more flexible and appropriate than Fuzzy AHP to deal with supplier selection problem. This paper presents a new study, comparing the methods Fuzzy TOPSIS and Fuzzy AHP. As commented by Ertugrul and Karakasoglu (2008), a study such as this can contribute to the advance of knowledge, helping researchers and practitioners choosing more effective approaches to supplier selection.

The aim of this thesis is to analyze a management problem in the organization Bohemians 1905, a.s. and submit recommendations to the board of the club for strategic choice options how to solve the management problem. The correct formulation of the problem will need to be analyze the current situation, put it in a strategic context and find the cause of the problem. This is done by Kepner-Tregoe methodology, C-E diagram and cognitive map. It will also need to develop objective solutions, design criteria, specify the possible solutions and determine the consequences of various options due to the proposed set of criteria. This is done by the value tree, a combination of multi-criteria evaluation under risk and certainty, probability trees and decision matrices. As a form of multi-criteria evaluation will be used in a specific form of the transfer bridge in the form of aggregated criteria of price/performance ratio of the options that allows create a list of preferred options.

A seleção de fornecedores tem impacto significante no custo e na qualidade de produtos manufaturados. Por isso, a seleção de fornecedores passou a ser vista como uma atividade bastante crítica para o desempenho da empresa compradora. Muitos estudos da literatura propõem o uso dos métodos multicritério fuzzy TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) e fuzzy AHP (Analytic Hierarchy Process) para apoiar a seleção de fornecedores. Contudo, não são encontrados estudos que avaliem o desempenho destes métodos quando usados neste domínio de problema. Diante desta lacuna, este estudo compara os métodos fuzzy TOPSIS (CHEN, 2000) e fuzzy AHP (CHANG, 1996) no apoio à seleção de fornecedores. Esta pesquisa utiliza uma abordagem quantitativa descritiva empírica, baseada em modelagem e simulação. Os métodos fuzzy TOPSIS e fuzzy AHP foram aplicados em um caso ilustrativo de seleção de fornecedores. O desempenho dos fornecedores e o peso dos critérios foram avaliados por um especialista de uma empresa. Modelos de simulação foram implementados usando MATLAB® e aplicados na seleção de fornecedores de uma empresa de uma cadeia de suprimentos automotiva. Cinco fornecedores foram avaliados em relação à qualidade, custo, entrega, perfil e relacionamento. O peso dos critérios e o desempenho dos fornecedores foi avaliado por meio da opinião de um especialista da empresa. Posteriormente, os métodos fuzzy TOPSIS e fuzzy AHP foram comparados em relação à capacidade de apoiar a decisão em grupo, qualificação de fornecedores, escolha final de fornecedores, situações de compra e modelagem de decisões sob incerteza. A eficiência dos métodos em relação à complexidade computacional e à interação requerida com o usuário também foi comparada. Os resultados mostraram que o fuzzy TOPSIS é mais flexível e mais adequado que o fuzzy AHP para modelar diferentes tipos de cenários de seleção de fornecedores. A realização desta discussão é sugerida por Ertugrul e Karakasoglu (2008), e é relevante para ajudar pesquisadores e gestores na escolha de abordagens efetivas para lidar com diferentes cenários de seleção de fornecedores. / Supplier selection has a significant influence on the cost, quality and delivery of products of the buying company. Therefore, supplier selection has become a very critical activity to the performance of the buying company. Several studies presented in the literature propose the use of fuzzy TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) and fuzzy AHP (Analytic Hierarchy Process) to aid the decision process of supplier selection. However, there are no comparative studies of these two methods when applied to the problem of supplier selection. Thus, this paper presents a comparative analysis of the methods fuzzy TOPSIS (Chen, 2000) and fuzzy AHP (Chang, 1996) applied to the problem of supplier selection. A descriptive quantitative approach was adopted as the research method. Algorithms of the methods fuzzy TOPSIS and fuzzy AHP were developed in Matlab© and applied to the selection of suppliers of a company in the automotive production chain. Five suppliers were evaluated regarding quality of conformance, cost, delivery, profile and relationship. The weight of the criteria and the performance of the suppliers were evaluated by specialist opinion from the studied company. The methods Fuzzy TOPSIS e Fuzzy AHP were compared in terms of ability to support the group decision, supplier qualification, final choice of suppliers, buying situations and modeling decisions under uncertainty. The efficiency of the methods with respect to computational complexity and the required user interaction was also compared. The comparative analysis shows that Fuzzy TOPSIS presents better than Fuzzy AHP performance, especially in scenarios in wich many alternatives are evaluated. Thus, Fuzzy TOPSIS is more flexible and appropriate than Fuzzy AHP to deal with supplier selection problem. This paper presents a new study, comparing the methods Fuzzy TOPSIS and Fuzzy AHP. As commented by Ertugrul and Karakasoglu (2008), a study such as this can contribute to the advance of knowledge, helping researchers and practitioners choosing more effective approaches to supplier selection.

The surveillance of geographic borders and critical infrastructures using limited sensor capability has always been a challenging task in many homeland security applications. While geographic borders may be very long and may go through isolated areas, critical assets may be large and numerous and may be located in highly populated areas. As a result, it is virtually impossible to secure each and every mile of border around the country, and each and every critical infrastructure inside the country. Most often, a compromise must be made between the percentage of border or critical asset covered by surveillance systems and the induced cost. Although threats to homeland security can be conceived to take place in many forms, those regarding illegal penetration of the air, land, and maritime domains under the cover of day-to-day activities have been identified to be of particular interest. For instance, the proliferation of drug smuggling, illegal immigration, international organized crime, resource exploitation, and more recently, modern piracy, require the strengthening of land border and maritime awareness and increasingly complex and challenging national security environments. The complexity and challenges associated to the above mission and to the protection of the homeland may explain why a methodology enabling the design and optimization of distributed detection systems architectures, able to provide accurate scanning of the air, land, and maritime domains, in a specific geographic and climatic environment, is a capital concern for the defense and protection community. This thesis proposes a methodology aimed at addressing the aforementioned gaps and challenges. The methodology particularly reformulates the problem in clear terms so as to facilitate the subsequent modeling and simulation of potential operational scenarios. The needs and challenges involved in the proposed study are investigated and a detailed description of a multidisciplinary strategy for the design and optimization of detection architectures in terms of detection performance and cost is provided. This implies the creation of a framework for the modeling and simulation of notional scenarios, as well as the development of improved methods for accurate optimization of detection architectures. More precisely, the present thesis describes a new approach to determining detection architectures able to provide effective coverage of a given geographical environment at a minimum cost, by optimizing the appropriate number, types, and locations of surveillance and detection systems. The objective of the optimization is twofold. First, given the topography of the terrain under study, several promising locations are determined for each sensor system based on the percentage of terrain it is covering. Second, architectures of sensor systems able to effectively cover large percentages of the terrain at minimal costs are determined by optimizing the number, types and locations of each detection system in the architecture. To do so, a modified Genetic Algorithm and a modified Particle Swarm Optimization are investigated and their ability to provide consistent results is compared. Ultimately, the modified Particle Swarm Optimization algorithm is used to obtain a Pareto frontier of detection architectures able to satisfy varying customer preferences on coverage performance and related cost.