In today’s market, sustainability has become an important competitive priority, affecting the way manufacturing companies need to develop their production systems. Increased external pressure from stakeholders, customers, law and regulations, as well as the undeniable consequences of the environmental crisis, causes a need for more sustainable production patterns. This affects manufacturing companies, since the social and environmental dimension of sustainability no longer can be ignored if companies want to retain their competitive position. Therefore, this thesis proposes a conceptual modeling framework that includes both sustainability and operational goals, with purpose to support manufacturers who want to develop sustainable production systems with the help of discrete event simulation. Empirical evidence from Swedish automotive industry indicates an unlocked potential in applying this framework to a discrete event simulation project, and findings in current research shows that alignment of sustainability and operational goals during production system development can help manufacturing companies achieve increased competitive advantage. However, there is two limitations to current knowledge; firstly, on how to align sustainability and operation goals in the early phases of a discrete event simulation project, namely at conceptual modeling; secondly, a lack of focus on conceptual modeling in discrete event simulation. In order to examine how to address this gap, a case study was conducted within the Swedish automotive industry, along with a literature study. As guidance in this work, four research questions were formulated and answered: RQ 1:    Why is the alignment between sustainability and operational goals important in development of production systems? RQ 2:    What sustainability goals may be included in a conceptual model in development of production systems? RQ 3:    What operational goals may be included in a conceptual model in development of production systems? RQ 4:    How can operational and sustainability goals be aligned in a conceptual model in development of production systems? As for the environmental dimension of sustainability, the goals that could be included at conceptual modeling are: pollution; emissions; and resource consumption. The most commonly involved operational goals at conceptual modeling are: quality and design; throughput; production layout and flow; automation levels; production volume; cycle times; lead times and change-over times; material handling; buildings and plant properties; storage and stock; capacity; price and costs. / Under de senaste åren har den alltmer påtagliga klimatkrisen och ändrade krav från intressenter, kunder och lagar, kommit att påverka faktorerna för hur tillverkande företag konkurrerar. Inom den tillverkande industrin finns det inte längre utrymme att se bort ifrån metoder som skapar hållbara tillverkningsmönster och produkter, i och med att hållbarhet numera även är kopplat till företagets förmåga att konkurrera. I linje med detta, föreslår denna uppsats ett ramverk för hur hållbarhetsmål och operationella mål kan inkluderas i den konceptuella fasen av en diskret händelsesimulering. Syftet med ramverket är att ge företag ett verktyg som kan appliceras vid utveckling av hållbara produktionssystem med hjälp av diskret händelsesimulering. Empiriska data från tillverkningsindustrin indikerar att det finns dold potential för applicering av det föreslagna ramverket inom projekt som använder sig av diskret händelsesimulering. Fynd i nutida forskning visar att en förening av hållbarhetsmål och operationella mål under utveckling av produktionssystem kan leda till att tillverkande företag uppnår fler konkurrensfördelar. Däremot saknas forskning på hur hållbarhetsmål och operationella mål skulle kunna förenas i en konceptuell modell under de tidiga faserna av ett simuleringsprojekt. Dessutom visar tidigare forskning att konceptuell modellering inte får tillräckligt med fokus vid simuleringsprojekt. I och med att den konceptuella modellen är den mest avgörande fasen i simuleringen kan det anses motiverat att förena hållbarhetsmål och operationella mål redan i denna fas, dock krävs mer forskning på området för att detta ska kunna realiseras. Med denna information som bakgrund genomfördes en litteraturstudie på området och en fallstudie inom den svenska tillverkningsindustrin. Som vägledning i forskningsstudien formulerades och besvarades fyra frågeställningar: Fråga 1:     Varför bör hållbarhetsmål och operationella mål förenas vid utveckling av produktionssystem? Fråga 2:     Vilka hållbarhetsmål är möjliga att inkludera i en konceptuell modell vid utveckling av produktionssystem? Fråga 3:     Vilka operationella mål är möjliga att inkludera i en konceptuell modell vid utveckling av produktionssystem? Fråga 4:     Hur kan hållbarhetsmål och operationella mål bli inkluderade i en konceptuell modell vid utveckling av produktionssystem? De miljömål som är möjliga att inkludera i en konceptuell modell är föroreningar, utsläpp och resursförbrukningar. De vanligaste operationella målen att inkludera i en konceptuell model är kvalitet och design, produktionstakt, produktionslayout och produktionsflöde, automationsnivåer, produktionsvolym, cykeltider, ledtider och ställtider, materialhantering, byggnader och fabriksegenskaper, lager och förråd, kapacitet, pris och kostnader.

Le développement des technologies de l’information et de la communication que connait notre siècle a grandement facilité les pratiques d’échanges d’informations au sein des chaînes logistiques. Ces pratiques ont pu ainsi évoluer vers de nouvelles formes de collaborations entre entreprises, telles que le Partage d’Informations (PI) et le Vendor Managed Inventory (VMI). Le VMI est un mécanisme de coordination dans lequel le fournisseur a la responsabilité de la gestion des stocks de son client. Ce mécanisme repose sur plusieurs principes parmi lesquels un partage d’informations très développé entre les parties qui s’y engagent. Le PI et le VMI sont adoptés par les entreprises pour permettre une augmentation des profits et une réduction des coûts. Toutefois, leurs résultats sont mitigés et nécessitent encore un approfondissement de leur compréhension. La contribution de cette thèse se situe dans l’analyse des impacts de ces mécanismes sur des chaînes logistiques où tous les maillons sont des entreprises de production dont les efficacités peuvent être différentes. Pour ce faire, plusieurs scénarios ont été étudiés sur des chaînes logistiques constituées de trois échelons, chaque échelon peut appartenir à quatre classes d’efficacité. Ces chaînes peuvent répondre à deux types de demande du marché final ; une demande stable ou une demande variable. De plus, plusieurs mécanismes de coordination sont étudiés : les mécanismes de gestion standard, de partage d’informations entre deux échelons, de partage d’informations entre trois échelons, de VMI entre deux échelons, puis de VMI étendu aux trois échelons. L’outil utilisé pour mener ces expérimentations est le logiciel de simulation à évènements discrets Arena. L’interprétation des résultats a montré que le mécanisme de coordination avec partage d’informations n’a pas eu d’amélioration très significative sur les résultats. En effet, puisque les entreprises ont des capacités de production finies, la disponibilité de l’information n’a pas permis d’obtenir des résultats différents. Le VMI, de son côté, a pu réaliser des réductions des stocks et des coûts de la chaîne logistique. Ces réductions ont été plus importantes chez les chaînes logistiques dont les maillons sont de faibles efficacités. Chez ces dernières, ce sont les deux parties concernées par le VMI (le fournisseur et le donneur d’ordres) qui ont tiré des avantages du VMI. Chez les chaînes logistiques constituées de maillons de haute efficacité, le VMI a permis une réduction des coûts moins importante, car ces chaînes logistiques sont déjà de performance élevée. Pour celles ci, c’est le client qui a tiré profit du VMI, alors que le fournisseur VMI a subi une augmentation des coûts suite à l’augmentation de la fréquence de transport qu’a impliqué ce mécanisme. / The advent of new information and communication technology has greatly facilitated the information exchange practices within supply chains. These practices recently evolved into new forms of collaborations between companies such as Information Sharing (IS) and Vendor Managed Inventory (VMI). The VMI is a coordination mechanism where the supplier is responsible for the inventory management of his customer. This mechanism is based on several principles, including developed information sharing between involved parties. The use of IS and VMI allow companies to increase profits and reduce costs. However, the results about the benefits from their use remain not clear. This motivates the need for new assessments and a better understanding of their effects. This thesis main contribution lies in the analysis and comprehension of IS and VMI’s impacts on supply chains. Especially, we address the issue of supply chains where tiers are production companies with different effectiveness levels. The examined scenario is based on a three tiers supply chain where each tier can belong to four effectiveness classes. The supply chain can respond to two types of end market demands: stable demands or fluctuant demands. In addition, several coordination mechanisms are studied: (i) standard management mechanism, (ii) information sharing between two enterprises, (iii) information sharing between three enterprises, (iv) VMI and (v) Extended VMI to all the three enterprises. The tool used to conduct these experiments is the discrete event simulation software “Arena”. The interpretation of the results showed that the IS coordination mechanism has not very significant improvement. Indeed, as companies have finite capacity, the availability of information did not yield better results. Whereas, the VMI could achieve reductions in both inventory and supply chain costs. In addition, VMI improved profits of the two parties, the vendor and the customer. Finally, the advantages of VMI appear to be stronger when the overall supply chain is less effective.

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / O gerenciamento do tempo nos projetos de construção civil usualmente utiliza algoritmos determinísticos para o cálculo dos prazos de finalização e algoritmos PERT para avaliação da probabilidade de o mesmo terminar até uma determinada data. Os resultados calculados pelos algoritmos tradicionais possuem defasagens nos prazos se comparados aos encontrados na realidade o que vem fazendo com que a simulação venha se tornando uma ferramenta cada vez mais utilizada no gerenciamento de projetos. O objetivo da dissertação é estudar o problema dos prazos de finalização dos projetos desenvolvendo novas técnicas de cálculo que reflitam melhor os prazos encontrados na vida real. A partir disso é criada uma ferramenta prática de gerenciamento do tempo de atividades de projetos de construção enxuta baseada em planilha eletrônica onde serão utilizadas técnicas de simulação a eventos discretos, com base em distribuições de probabilidade como, por exemplo, a distribuição beta. / Time management in construction projects usually use deterministic algorithms to calculate the time of fulfillment, and PERT algorithms to evaluate the probability of such project ending by a certain date. The results achieved by traditional algorithms are not accurate when compared to those found in the field, which is increasing the use of simulation as a tool in project management. The aim of this dissertation is to study the deadline fulfillment problems of projects, developing new calculation techniques that better represent the deadlines found in real life. For such study is developed a practical tool for time management of lean construction projects based on spreadsheet which will be used discrete event simulation techniques based in probability distributions, such as, the beta distribution.

Made available in DSpace on 2016-06-02T19:52:09Z (GMT). No. of bitstreams: 1 6571.pdf: 4032074 bytes, checksum: e0d2561f673f9fff989f2b9d7c179d5e (MD5) Previous issue date: 2015-02-20 / Financiadora de Estudos e Projetos / This paper aims to diagnose the passenger boarding and landing processes of the Uberlândia airport using the mapping process and computer simulation. The paper presents a review of literature about the airport sector, techniques of mapping process, data collection, queue management and computer simulation. The objective is to analyze each subsystem used by the passenger during their boarding and landing, from the vehicle access areas and check- in counters until the departure lounge and the receipt of baggage. In conclusion, alternatives are proposals to reduce the total time of the passengers in queues, contributing to a possible improvement project for the airport. / O presente trabalho tem como proposta diagnosticar os processos de embarque e desembarque de passageiros no aeroporto de Uberlândia por meio do uso do mapeamento de processo e da simulação computacional. O trabalho apresenta uma revisão da literatura acerca do setor aeroportuário, técnicas de mapeamento de processos, coleta de dados, gestão de filas e simulação computacional. O objetivo é analisar cada subsistema utilizado pelo passageiro durante seu embarque e desembarque, desde as áreas de acesso de veículos e de balcões de check-in até as áreas de embarque e de recebimento de bagagens. Como conclusão são propostas alternativas capazes de reduzir o tempo total dos passageiros em filas, contribuindo para um possível projeto de melhoria para o aeroporto.

A simulação de eventos discretos é uma das mais poderosas ferramentas disponíveis para modelagem e análise de problemas. Freqüentemente ela é utilizada para o planejamento, projeto e controle de sistemas complexos em diversos segmentos; entre eles, a área de sistemas logísticos, que a tem aplicado extensivamente para analisar as capacidades logísticas, avaliar os impactos de mudanças nos processos produtivos, testar diferentes configurações na alocação de recursos limitados, determinar parâmetros das operações, validar novos projetos, entre outras aplicações. Esta popularização da simulação despertou o interesse das empresas especializadas no desenvolvimento de softwares, resultando em diversas opções com diferentes características e custos. Desta forma, identificou-se a necessidade de um método para seleção de softwares de simulação de eventos discretos voltados à resolução de problemas logísticos, pois os trabalhos disponíveis na Literatura abordam somente a escolha de softwares para fins genéricos. Para preencher essa lacuna, foi proposto um conjunto de critérios que endereçam as necessidades específicas do desenvolvimento de modelos voltados à análise de sistemas logísticos. Esses critérios formaram a base do método proposto, que incorporou as melhores características dos trabalhos identificados na Literatura. Sua primeira fase gerou uma lista com os softwares que suportaram os critérios definidos como essenciais por meio da aplicação de um método de atribuição de pesos e pontuação, cuja eficiência e simplicidade são amplamente reconhecidas; já a segunda fase, utilizou o método de análise hierárquica (AHP), recomendado para a tomada de decisão baseada em múltiplos critérios, por permitir a identificação e correção das inconsistências geradas pelo julgamento humano. Dois problemas testes também foram propostos para o desenvolvimento de aplicações em sistemas logísticos e condução de experimentos durante a segunda fase. Os softwares Arena, ProModel e @Risk, extensivamente utilizados para ensino e pesquisa na Escola Politécnica da Universidade de São Paulo, foram avaliados durante a aplicação prática do método proposto. Os resultados obtidos confirmaram a percepção, adquirida durante a segunda fase do método, de que os softwares Arena e ProModel apresentam características semelhantes, dada a discreta diferença em suas pontuações totais. Os diversos cenários desenvolvidos na análise de sensibilidade também ratificaram essa tendência. / The discrete event simulation is one of the most powerful tools available for modeling and problem analysis. Frequently it is used for planning, designing and controlling complex systems in several segments. The logistic system area has also applied it extensively to analyse the logistic capacities, evaluate the impacts of changes in the productive processes, test different configurations in the allocation of limited resources, determine operation parameters, validate new projects, among other applications. Thus, the growth of the simulation awoke the interest of the companies specialized in software development. This fact resulted in several options with different characteristics and costs. Because of this, it was identified the necessity of a selection method for discrete event simulation software dedicated to the resolution of logistic problems. The available works in Literature only approach the choice of softwares for generic purposes. To fill in this gap, a set of criteria that address the specific necessities of the development of models dedicated to the analysis of logistic systems was proposed. These criteria formed the base of the proposed method. It has incorporated the best characteristics of the works identified in Literature. Its first phase generated a list with softwares with widely recognized efficiency and simplicity that supported the essential criteria through the application of a scoring model. Its second phase used the Analytic Hierarchy Process (AHP) which is recommended for the decision taking based on multiple criteria because it allows the identification and correction of the inconsistencies generated by the human judgment. Two test problems have also been proposed for the development of applications in logistic systems and performance of experiments during the second phase. Arena, ProModel and @Risk, extensively used for education and research in the Polytechnical School of the University of São Paulo, were evaluated during the practical application of the proposed method. The results confirmed the perception acquired during the second phase of the method that Arena and ProModel present similar characteristics. They presented a discrete difference in their total score. The several scenes developed in the sensitivity analysis also ratified this trend.

Submitted by Nadir Basilio (nadirsb@uninove.br) on 2017-04-27T18:29:45Z No. of bitstreams: 1 Elizangela de Jesus Gibelati.pdf: 1199243 bytes, checksum: 831f7c88b077b3f5860a082343d6d0e5 (MD5) / Made available in DSpace on 2017-04-27T18:29:45Z (GMT). No. of bitstreams: 1 Elizangela de Jesus Gibelati.pdf: 1199243 bytes, checksum: 831f7c88b077b3f5860a082343d6d0e5 (MD5) Previous issue date: 2015-08-31 / The discrete event simulation is one of the most used techniques in operational research area. It is a support decision technique, in which the search for problem solving is done by analyzing a computer model that describes the behavior of the system under study. Applications of this technique are found in several areas and have very significant results, especially for manufacturing and logistics industry. This paper presents the construction of a simulation discrete event model in the computer system Arena® to analyze a part of the supply chain of a service company, aiming to help define the minimum stock level of material in a distribution center. The adopted simulation approach considers the material as the main entity, and it represents the volume of stock in the links in the chain as lines on the template simulation modules, which simplifies the modeling and gives a uniqueness of character to the proposal. As a result, you can determine the best inventory security levels of in different stochastic demand scenarios with high variability, considering pre-established service levels and uncertainty in delivering the material. / A simulação a eventos discretos é uma das técnicas mais utilizadas na área de pesquisa operacional. Trata-se de uma técnica de apoio à decisão, em que a busca pela solução de um problema é feita pela análise de um modelo computacional que descreve o comportamento do sistema em estudo. Aplicações dessa técnica são encontradas em diversas áreas e apresentam resultados muito significativos, com destaque para a manufatura e logística na indústria. Este trabalho apresenta a construção de um modelo de simulação a eventos discretos, no sistema computacional Arena®, para analisar uma parte da cadeia de suprimentos de uma empresa de serviços, visando auxiliar na definição do nível de estoque mínimo de material em um centro de distribuição. A abordagem de simulação adotada considera o material como entidade principal, e representa o volume de estoque nos elos da cadeia como filas nos módulos do modelo, o que permite simplificar a modelagem e confere um caráter de originalidade à proposta. Como resultado, é possível determinar os melhores níveis de estoque de segurança em diferentes cenários de demanda estocástica com alta variabilidade, considerando níveis de atendimento preestabelecidos e incertezas na entrega do material.

O estudo de sistemas logísticos envolve a concatenação de elementos estratégicos e operacionais, comumente compondo sistemas com múltiplas facetas, objetivos antagônicos e grande número de alternativas. Nesse contexto, o presente trabalho discute a utilização de análise de decisão multicritério (MCDA), simulação de eventos discretos (SED) e otimização para simulação. A metodologia MCDA captura, mensura e pondera os objetivos e valores dos tomadores de decisão. Por sua vez, a SED representa o sistema estudado com alto nível de detalhamento, permitindo a avaliação de diversas configurações do sistema. Por fim, métodos de otimização para simulação possibilitam a busca e comparação de alternativas mais eficientes. As três metodologias são avaliadas, identificando suas vantagens, desvantagens e complementaridades quando aplicadas a sistemas logísticos. Através da aplicação de um estudo de caso sobre o dimensionamento de um sistema de transporte, constatou-se que: a) a SED incorporou detalhes importantes para a avaliação mais precisa de vários indicadores de desempenho b) a metodologia MCDA possibilitou a captura de vários objetivos e valores, propiciando a realização de tradeoffs robustos; c) um método de busca exaustiva e técnicas de redução de variância permitiram a comparação das alternativas em tempos computacionais reduzidos. Por fim, conclui-se que a metodologia híbrida apresentada expande o potencial de aplicação da SED em sistemas logísticos complexos. / A logistic system study involves strategic and operational elements, commonly composing multi-faceted systems with antagonistic goals and large number of alternatives. In this context, this thesis discusses the use of multi-criteria decision analysis (MCDA), discrete event simulation (DES) and optimization for simulation. The MCDA methodology captures, measures and weighs the goals and values of decision makers. DES is useful for representing systems with high level of detail, allowing the evaluation of several system configurations. Finally, optimization for simulation procedures are useful for searching and comparing more efficient alternatives. These three methodologies are assessed and their advantages, disadvantages, and complementarities are identified for logistics systems applications. Through a case study of a transportation system, we conclude that: a) the SED incorporated important details for more precise evaluation of various performance indicators b) the MCDA methodology was useful to capture several goals and values, so that robust tradeoffs could be carried out c) an exhaustive search routine and variance reduction techniques allowed the comparison of several alternatives in feasible computational times. Finally, we conclude that the presented hybrid methodology expands the application of DES to complex logistics systems.

Realizar a análise econômica de uma produção agropecuária não é algo trivial, seja pela enorme heterogeneidade entre cada unidade produtiva, seja porque utiliza muitos recursos naturais, alguns de difícil mensuração. Há diversos métodos disponíveis para o cálculo do custo de produção, que é o indicador chave para a análise da viabilidade de um empreendimento. O desafio é permitir que a projeção da atividade no horizonte produtivo seja a mais real e dinâmica possível. A simulação computacional é atualmente uma das mais poderosas ferramentas de análise disponível para o planejamento, projeto e controle de sistemas complexos, e vem sendo cada vez mais utilizada e difundida. Simular compreende a elaboração de um método de experimentação que, através da construção de modelos de um sistema real, procura descrever comportamentos, construir teorias ou hipóteses por meio do observado e predizer comportamentos futuros. O uso de modelos de simulação, que incorporem o risco e a probabilidade dentro produção animal, pode ser uma alternativa tanto técnica - auxiliando na tomada de decisão, gestão e planejamento pecuário, quanto científica - permitindo a avaliação de efeitos de resultados da pesquisa e identificação de limitantes que podem incentivar o desenvolvimento de pesquisas futuras. O modelo de simulação híbrido - baseado em simulação de eventos discretos e baseado em agentes, aqui proposto - visou identificar coeficientes zootécnicos e os critérios de manejo que mais impactam a produção de ovinos de corte. Esse modelo de simulação computacional híbrido possui caráter dinâmico e probabilístico, com eventos marcados no tempo (estação de monta, gestação, parição, desmame, engorda, abate, entre outras) e complexos o suficiente para que seus agentes sofram alterações tanto no tempo quanto em resposta a ocorrência ou não das variáveis ligadas a eles. Os resultados dos experimentos e dos cenários estudados revelaram que dentre os índices zootécnicos das matrizes, a ocorrência de aborto gera maior impacto na taxa de abate e financeiramente na margem líquida operacional. Contudo, analisando as variáveis tanto para matrizes como para cordeiros, a mortalidade neonatal, até os cinco dias de vida dos cordeiros, demonstrou ser o ponto fundamental para a lucratividade da atividade. A estabilização do rebanho foi mais afetada pela presença de matrizes adultas no plantel, que culminaram no aumento no número de cordeiros por matriz. Os resultados da análise dos fluxos de caixa de 30 anos, a uma taxa mínima de atratividade de 6,17% aa, permitiram constatar que iniciar a atividade com número muito reduzido de matrizes é o cenário menos interessantes, com taxa interna de retorno negativa para o período de análise. O estudo do fluxo de caixa permitiu atribuir a 200 matrizes como o tamanho de rebanho inicial mais interessante (TIR = 3,30% aa). Assim, o uso de simuladores híbridos baseados em simulação de eventos discretos e baseados em agentes, para estudos na pecuária nacional, apresentou-se como ferramenta com grande potencial de contribuição, no sentido de permitir conhecer os resultados possíveis das diferentes combinações tecnológicas disponíveis. O modelo ainda permite ser utilizado como ferramenta de estudo e análise para a cadeia produtiva, contribuindo na orientação aos cientistas, auxiliando no direcionamento de seus esforços no desenvolvimento de futuras pesquisas / Conduct an economic analysis of agricultural production is not trivial, either by its enormous heterogeneity between each production unit, or because it uses many natural resources, some of which are difficult to measure. There are several methods available for calculating the cost of production, which is the key indicator for assessing the feasibility of a project. The challenge is to allow the projection of activity in the productive horizon in the most real and dynamic form as possible. The computer simulation is currently one of the most powerful analysis tools available for planning, design and control of complex systems and is being increasingly used and disseminated. Simulate includes the development of a method of testing by building models of a real system, that seeks to describe behaviors, build theories or hypotheses through noted and predicted future behaviors. The use of simulation models that incorporate uncertainty and probability in animal production can be both an alternative technique - assisting in decision-making, management and livestock planning; as scientific - allowing the evaluation of the research results of effects and identification of limiting that may encourage the development of future research. The model of hybrid simulation - based on discrete event simulation and on agent-based, proposed here - aimed to identify factors husbandry and management criteria that most affect the production of meat sheep. The model of hybrid computer simulation have dynamic and probabilistic characteristics, with events scheduled in time (breeding season, pregnancy, parturition, weaning, fattening, slaughter, etc.) and enough complexity that its agents be adversely affected both in time and in response to the occurrence or not of variables linked to them. The results of the experiments and the scenarios studied showed that among the zootechnical indexes of the sheep, the occurrence of abortion generates a greater impact on the slaughter rate and financially in the net operating margin. However, analyzing the variables for both sheep and lambs, neonatal mortality, up to the lambs\' five days of life, proved to be the fundamental point for the profitability of the activity. The stabilization of the herd was more affected by the presence of adult sheep in the herd, which culminated increasing the number of lambs per sheep. The results of the analysis of the 30-year cash flows, at a minimum attractiveness rate of 6.17% per year, showed that starting the activity with a very small number of sheep was the least interesting scenario, with a negative internal rate of return for the analysis period. The study of the cash flow allowed to assign to 200 sheep as the most interesting initial herd size (IRR = 3.30% per year). Thus, the use of hybrid simulators, based on discrete event simulation and agent-based for studies in national livestock, is presented as a tool with great potential to contribute, to allow knowing the possible outcomes of different combinations of available technology. The model also allows to be used as a study tool and assessment of different technological combinations for the production chain, contributing to the guidance of scientists, assisting their efforts in the development of future research

Ce travail de recherche met en avant l'intérêt qu'offre la simulation en ligne comme outil d'aide à la décision, outil centré sur le pilotage d'atelier vis-à-vis d'événements se produisant en temps réel et pour un horizon à très court terme. Après avoir présenté le contexte général du pilotage des systèmes de production, nous avons étudié les outils existants et utilisés industriellement pour l'exploitation de la production, de même que les outils d'aide au pilotage permettant d'assurer le respect optimal des objectifs fixés. Après un travail préalable sur la simulation hors ligne, nous proposons de coupler un outil de simulation en ligne à un outil d'exécution d'atelier de type MES afin de piloter en temps réel le processus de production. Une démarche de modélisation faisant appel de façon complémentaire à deux approches, analytique et simulatoire, est finalement mise en place. Nous mettons en exergue l'utilisation de la simulation de flux en ligne pour aider au pilotage d'un processus opérationnel. Ainsi nous modélisons le processus de pilotage en temps réel afin de décrire les fonctions requises. Pour cela, nous utilisons différentes stratégies d'utilisation des simulateurs en ligne pour le pilotage, avec un ou deux modèles et avec plusieurs méthodes d'utilisation de ces modèles. La simulation en ligne apporte alors des informations objectives sur les conséquences à court terme d'un événement, ainsi que sur les divers scenarii de correction envisagés. Pour mieux convaincre les industriels de l'intérêt de la simulation en ligne, nous présentons des solutions pratiques aux spécifications et besoins énoncés précédemment en nous appuyant sur une plate-forme expérimentale. / This research work highlights the interest of online simulation as a decision support tool. This tool is focused on workshop control in relation with real time and short-term events. Online simulation enables to analyze and compare scenarios affecting the production, such as failures or unexpected orders. Moreover online simulation allows a very short term projection in the future in order to quantify the consequences of some unexpected event: we call it projection simulation. Finally, online simulation is helpful to choose the solution that will reduce the impact of a critical event, through the simulation of several scenarios. To conclude, online simulation is one the most interesting decision support tool in workshop piloting. However, there are few industrial applications in manufacturing systems. The first part of this research work introduces the overall context of production system management. The different generic functions of controlling the production, the modes of piloting and the evolutions of workshop are detailed. We also explain piloting typologies according to their reactivity. In the second part, we study the existing software tools used in industry for the operation of production, and support tools that ensure optimal compliance in regard to the objectives. After a preliminary work on the offline simulation, we propose to couple an online simulation tool with a type MES delivery tool in order to control the production process in real time. A modeling approach using two complementary approaches, an analytical one and simulation, is then introduced. The objective of the third part is to emphasize the use of online flow simulation to assist in operating a production process. Thus we model the process in real time to describe the required functions. Therefore we try out different strategies of use of online simulators, through one or two models and several methods of using these models. Online simulation then provides realistic information on the short-term consequences of an event, as well as on the different ways of correcting the scenarios. To convince industry of the relevance of online simulation, the fourth part presents practical solutions to the specifications and requirements previously stated. An experimental platform helped us validate the concept of online simulation as piloting support tool, but also underline the difficulties of development.

Event-based models find frequent usage in fields such as computational physics and biology as they may contain both continuous and discrete state variables and may incorporate both deterministic and stochastic state transitions. If the state transitions are stochastic, computer-generated random numbers are used to obtain the model solution. This type of event-based computations is also known as Monte-Carlo simulation. In this thesis, I study different approaches to execute event-based computations on parallel computers. This ultimately allows users to retrieve their simulation results in a fraction of the original computation time. As system sizes grow continuously or models have to be simulated at longer time scales, this is a necessary approach for current computational tasks. More specifically, I propose several ways to asynchronously simulate such models on parallel shared-memory computers, for example using parallel discrete-event simulation or task-based computing. The particular event-based models studied herein find applications in systems biology, computational epidemiology and computational neuroscience. In the presented studies, the proposed methods allow for high efficiency of the parallel simulation, typically scaling well with the number of used computer cores. As the scaling typically depends on individual model properties, the studies also investigate which quantities have the greatest impact on the simulation performance. Finally, the presented studies include other insights into event-based computations, such as methods how to estimate parameter sensitivity in stochastic models and how to simulate models that include both deterministic and stochastic state transitions. / UPMARC