L’application des approches probabilistes pour tenir compte des incertitudes dans le domaine des barrages est un sujet en développement. Cependant, la plupart des études ont été réalisées sur l’évaluation de la sécurité des barrages pendant leur service. Ce travail de thèse vise à appliquer ce type d’approches et à faire une contribution à l’analyse de risque des barrages en béton compacté au rouleau (BCR) d`es sa construction, à l’aide d’une simulation numérique. Les travaux présentés dans ce manuscrit proposent l’application d’une méthodologie qui vise à quantifier la vulnérabilité vis-à-vis de l’apparition de la fissuration pendant la construction du barrage, ce qui peut affecter `a long-terme la perméabilité et par conséquent, compromettre son comportement structurel. Pour ce faire, l’accent est mis sur les incertitudes liées à quelques caractéristiques des matériaux (e.g., résistance, rapport eau-ciment, entre autres) et aux conditions environnementales pendant la phase de construction. Un modèle thermo-chemo-mécanique est utilisé pour décrire le comportement du BCR. En ce qui concerne le modèle probabiliste, deux aspects sont étudiés: i) comment les incertitudes liées aux variables d’entrée sont propagées dans le modèle, et ii) quelle est l’influence de leur dispersion par rapport à la dispersion totale de la sortie. Ce dernier est évalué par l’intermédiaire d’une analyse de sensibilité globale effectuée avec la méthode RBD-FAST. En outre, la variabilité spatiale des paramètres d’entrée est aussi prise en compte à travers des champs aléatoires bidimensionnels. Par ailleurs, un couplage entre des méthodes de fiabilité et la méthode d’éléments finis est effectué de façon à évaluer le potentiel de fissuration dans chaque couche de BCR lors de sa construction en utilisant un concept de densité de fissuration. Comme résultat important issu de ce travail de recherche, des courbes de probabilité pour la densité de fissuration sont obtenues au niveau de chaque couche en fonction de leur âge et des conditions aux limites, ce qui est considérée comme étant une contribution originale de cette thèse.La méthodologie proposée peut être utilisé pour aider à comprendre comment les incertitudes vont affecter le comportement du barrage pendant sa construction et servir d’appui dans le futur pour améliorer et soutenir la phase de conception du projet de barrage. / The use of fully probabilistic approaches to account for uncertainties within dam engineering is a recently emerging field on which studies have been mostly done concerning the safety evaluation of dams under service. This thesis arises within this framework as a contribution on moving the process of risk analysis of dams beyond empirical knowledge, applying probabilistic tools on the numerical modelling of a roller compacted concrete (RCC) dam during its construction phase.The work developed here aims to propose a methodology so as to account for risks related to cracking during construction which may compromise the dam’s functional and structural behaviour.In order to do so, emphasis is given to uncertainties related to the material itself (i.e.strength, water-to-cement ratio, among others) as well as to ambient conditions during the construction phase of RCC dams. A thermo-chemo-mechanical model is used to describe theRCC behaviour. Concerning the probabilistic model, two aspects are studied : how the uncertainties related to the input variables are propagated through the model, and what is the influence of their dispersion on the dispersion of the output, assessed by performing a global sensitivity analysis by means of the RBD-FAST method. Also, spatial variability of some input parameters is accounted for through bi-dimensional random fields. Furthermore, a coupling between reliability methods and finite element methods is performed in order to evaluate the cracking potential of each casted RCC layer during construction by means of a cracking density concept. As an important outcome of this applied research,probability curves for cracking density within each casted layer as functions of both age and boundary conditions are predicted, which is believed to be an original contribution of this thesis. The proposed methodology may therefore be seen as a contribution to help engineers understand how uncertainties will affect the dam behaviour during construction and rely on it inthe future to improve and support the design phase of the dam project.

Incertezas são inerentes ao planejamento de fechamento de mina, atividade que requer o trato de complexas questões técnicas, sociais, econômicas e ambientais em perspectiva de longo prazo e com base em informação e conhecimentos fragmentados e não sistemáticos. Incertezas nas tomadas de decisões podem resultar em ações de fechamento ineficazes e/ou ineficientes, ou seja, que não alcancem os objetivos esperados e/ou demandem vultosos recursos financeiros, humanos e outros. Esta pesquisa procurou compreender a natureza das incertezas presentes no processo de planejamento de fechamento de mina por meio da definição de suas causas, tipos e formas de tratamento e analisar como são abordadas em guias de boas práticas. Incerteza, no contexto do planejamento de fechamento de mina, é entendida como uma situação na qual há conhecimento incompleto, imprevisibilidade ou não há um único entendimento do processo a ser gerenciado. Nesse contexto, as principais causas das incertezas são, respectivamente, insuficiência de conhecimento, variabilidade do comportamento dos componentes do processo, no tempo e no espaço e diferentes enfoques ou recortes da situação analisada. Foram definidos oito tipos de incertezas pertinentes ao planejamento de fechamento de mina, agrupadas em três componentes (i) naturais (incertezas ambientais, geológicas, geotécnicas), (ii) técnicos (incertezas operacionais, tecnológicos), (iii) socioeconômicos (incertezas sociais, regulatórias, gerenciais, econômicas). Associações de empresas e órgãos públicos têm publicado guias e documentos de diretrizes para orientar as empresas a planejar o fechamento de mina. No entanto, esses guias não parecem ser explícitos quanto ao reconhecimento e tratamento de incertezas no planejamento de fechamento. Assim, por meio da técnica de análise de conteúdo, quatro guias de boas práticas foram examinados para verificar, se e como, abordam ou recomendam diretrizes para lidar com incertezas no planejamento de fechamento. Os resultados mostraram que certos tipos de incerteza são reconhecidos pelos guias, que recomendam algumas diretrizes para lidar, em especial, com incertezas ambientais, sociais, regulatórias e econômicas. Porém, (i) os guias não demonstram uma clara concepção ou entendimento das incertezas inerentes ao planejamento de fechamento de mina, embora em algumas situações reconheçam sua existência e influência; (ii) a maior ênfase dos guias em relação aos aspectos ambientais pode induzir as empresas a alocarem responsabilidades para tratar questões relativas ao fechamento ao departamento de meio ambiente ou de relações comunitárias e não induzirem que sejam tratadas a nível estratégico pela alta direção da empresa e (iii) a maioria dos guias, não fornece diretrizes para melhorar e avaliar a qualidade das informações/conhecimento nas tomadas de decisões. É proposto um esquema analítico para lidar com as incertezas no planejamento de fechamento, composto por três etapas: (i) identificação dos tipos de incertezas; (ii) definição das causas das incertezas e (iii) definição de ações e estratégias para lidar com as incertezas. Espera-se que a proposta possa contribuir para que as empresas de mineração considerem, de maneira estruturada, as incertezas em suas decisões relativas ao fechamento, e que órgãos públicos possam utilizá-la para avaliar as informações apresentadas em planos de fechamento e demais estudos técnicos relativos à autorização e licenciamento de projetos. / Uncertainties are intrinsic to the mine closure planning, activity which involves complex long-term technical, social, economic and environmental questions, based on fragmented and non-systematic information and knowledge. Uncertainties in decision-making may lead to inefficacious closing actions, which do not achieve the expected goals and/or demand a lot of financial, human and other types of resources. This research aimed at understanding the nature of the uncertainties involved in the mine closure planning process by defining their causes, types and ways to deal with them and analyzing how they are treated in best-practice guidelines. Uncertainty in the context of mine closure planning is understood as a situation in which there is incomplete knowledge, unpredictability or no single way to understand the process to be managed. In this context, the main causes of uncertainties are respectively: lack of knowledge, time and space variability of the behavior of the components in the process and different approaches or understanding about the analyzed situation. Eight types of uncertainties regarding the mine closure planning have been defined and grouped in three components: (i) natural (environmental, geological and geotechnical uncertatinty), technical (operational and technological uncertatinty), (iii) social- economical (social, regulatory, management and economic uncertainties). Enterprises associations and public agencies have been publishing guidelines to provide the companies with advice on how to plan the mine closure. However, these guidelines do not seem to be explicit in recognizing and dealing with uncertainty in the closure planning. Thus, using the content analysis technique, four best practice guidelines have been examined in order to determine whether and how they approach or produce advice to deal with uncertainty in the closure planning. The results have shown that certain types of uncertainty are addressed by the guidelines, which provide some advices to deal particularly with environmental, social, regulatory and economic uncertainties. Nevertheless, the guidelines: (i) do not present a clear concept or understanding about the uncertainty which are intrinsic to the mine closure planning, although in some situations the recognize their existence and influence; (ii) the higher emphasis on the environmental aspects used by the guidelines may induce the companies to allocate reponsibilities to deal with x questions related with the closure, the environmental department or the relations with the community and cause them not be treated in strategic level by the company and (iii) most guidelines do not provide advices on how to improve and evaluate the quality of the information/knowledge of the decision-making. An analytical scheme composed by three steps is proposed to deal with the uncertainties in the closure planning: (i) identification of the uncertainty type; (ii) definition of uncertainty causes and (iii) definitions of actions and strategies to deal with uncertainties. This proposal may contribute for the mining companies to consider in a structured way the uncertainties in their closure-related decisions and for the public agencies to evaluate the information present in closure plans and other technical studies related to licensing projects.

Este estudo teve o objetivo de prospectar as incertezas após a implantação de uma empresa produtora de biodiesel em um município produtor de soja do Rio Grande do Sul. A pesquisa é classificada como exploratória e a metodologia utilizada foi a de prospecção de cenários futuros, finalizada na quarta etapa (identificação das incertezas chave). A coleta de dados foi operacionalizada por meio de entrevistas com perguntas abertas e fechadas aos representantes dos elos de produção, beneficiamento e P&D da soja e biodiesel e visitas às empresas e instituições envolvidas nas cadeias produtivas. Dessa forma, por meio de observações, além de pesquisas bibliográficas, percebe-se uma grande necessidade de encontrar mecanismos de colaboração entre os agentes da cadeia produtiva da soja e do biodiesel, visando obter sucesso na implantação do PROBIODIESEL na região. As incertezas identificadas se referem a questões como: a disseminação da cultura administrativa no segmento de produção visando a incorporação de um sistema de gestão apropriado para a agricultura familiar; a intensificação do melhoramento genético de cultivares de soja adaptadas às condições locais, produção de biodiesel e agricultura familiar de pequeno/médio porte, com vistas ao monocultivo incentivado; a consolidação do PROBIODIESEL em termos de benefícios promovidos pelo governo federal como o Selo Combustível Social e a linha adicional do Pronaf; apoio técnico e financeiro para que o programa consiga o patamar esperado em termos de produção e realização de metas; organização da cadeia produtiva da soja em função do biodiesel e em parceria com a cadeia produtiva deste; e, a melhoria da infra-estrutura de logística para facilitar a colaboração entre os elos. As conclusões da pesquisa podem contribuir para a organização da cadeia produtiva da soja como matéria-prima do biodiesel, auxiliando-a na definição de futuros cenários agronômicos, políticos, econômicos e ambientais, somadas às informações internas disponíveis e à vontade de colaboração entre os elos para dar andamento a implantação do PROBIODIESEL na região. / The purpose of this study is to identify the uncertainties after the establishment of the biodiesel´s company in a Rio Grande do Sul s region that produce soybean. This research is classified as an exploratory survey. The methodology used Future Sets Prospection and it was finished in the fourth stage (Identification of key-uncertanties), due to the specify information that emphasize the risk perceptions to guide future plans of envolved actors. The corpus was colected by interviews with open and closed questions. The participants were representants of production, improvement and soybeans´s P&D and biodiesel. Visits to Companies and Institutions envolved in the productive chain were done to provide familiarity with the problem. Observations and the review of literature helped to understand the necessity to find out mecanisms of colaboration between agents of Productive chains of soybeans and the biodiesel, in order to have success in the PROBIODIESEL establishment in the region. The uncertanties identified refers to questions such as: the incorporation of appropriated management system to the familiar agriculture; the intensification of genetic improvement of the cultivated soybeans adapted to local condictions, production of biodiesel and the small/medium familiar agriculture, to devolop the monoculture; the program´s consolidation in terms of benefits provide by the Federal Government such as Social Fuel and the adicional Pronaf´s Line, technical and financial support to the program aiming to get in the top in terms of production and realization of goals; organization of productive chains of soybeans in relation to biodiesel and partnership of Productive chains; and the implementation of logistics infra-structure to facilitate the colaboration of links. The results can contribue to the organization of Productive Chains of soybeans as raw material to the biodiesel helping to define future sets of agronomics, politics, economics and environmental, added to internal informations available and the desire of colaboration between links in order to promote the PROBIODIESEL establishment in the region.

Orientador: Helio Fiori de Castro / Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Mecânica / Made available in DSpace on 2018-08-28T11:56:54Z (GMT). No. of bitstreams: 1 Tyminski_NataliaCezaro_M.pdf: 6550021 bytes, checksum: 3fb888c14fc5d24d29f7f155d0e4f2b0 (MD5) Previous issue date: 2015 / Resumo: As unidades geradoras de energia das usinas são formadas por turbinas e turbo-geradores, que são exemplos típicos de máquinas rotativas. Essas maquinas são componentes críticos, pois são essenciais à geração de energia. Sabendo que a análise dinâmica de máquinas rotativas é uma tarefa complexa envolvendo diversos parâmetros a serem analisados, sua realização não deve considerar apenas o rotor, pois seu comportamento dinâmico é influenciado pela interação com os demais componentes do mesmo sistema. O comportamento dinâmico de uma máquina rotativa é, geralmente, representado por um modelo determinístico. Entretanto, sistemas rotativos reais possuem características estocásticas, visto que os inúmeros parâmetros de projetos possuem incertezas inerentes à fabricação e, principalmente, às condições de operações. Desta forma, modelos estocásticos são uma opção importante para representação de sistemas rotativos na fase de projeto, onde se podem prever os efeitos da variação dos parâmetros de projeto. O tema em foco nesta dissertação de mestrado é a aplicação de Inferência Bayesiana para ajustar um modelo de sistema rotativo. Neste trabalho foram analisadas as incertezas nos parâmetros de projeto de um sistema rotativo, e a partir das incertezas obtidas foi possível obter a resposta estocástica do sistema. A primeira analise considera as incertezas dos parâmetros relacionados ao eixo; como o modulo de elasticidade, a massa especifica do material e o coeficiente de proporcionalidade a matriz de rigidez. Na segunda análise, os parâmetros escolhidos foram os parâmetros de desbalanceamento; ângulo de fase, momento de desbalanceamento e posição axial. Em uma terceira abordagem, foi analisado parâmetros dos mancais hidrodinâmicos, folga radial do mancal e temperatura do óleo lubrificante. A partir das incertezas dos referidos parâmetros, foi possível analisar a propagação de incertezas desses parâmetros no cálculo da posição do eixo no mancal e dos coeficientes dinâmicos dos mancais hidrodinâmicos / Abstract: Energy generation plants rely on units such as turbines and turbo-generators, which are common examples of rotating machines. These machines are critical components in these units, once they are essential to the energy generation. The dynamic analysis of rotating machines is a complex task including several parameters to be considered. This analysis requires taking the rotor into account but also the other components, which affect the dynamic behavior of the system. The dynamic behavior of rotating machines is usually represented by a deterministic model. Although, real rotating system have stochastic characteristics once that the parameters on project have uncertainties. In this way, stochastic models are an important option for the representation of these systems, and it's possible predict the variation's parameters. This study aims the application of Bayesian Inference for model updating on rotating systems. The uncertainties of rotating machines parameters were analyzed, and the system stochastic response was obtained. The first analyzed considers the uncertainties of the beam parameters, as the Young¿s modulus, and the proportionality coefficient to the stiffness matrix. In the second analysis, the selected parameters were the unbalance parameters; phase angle, unbalance moment and axial position. In a third approach, it was analyzed parameters of journal bearings, clearance radial and lubricating oil temperature. From the uncertainties of these parameters, it was possible to analyze the propagation of uncertainties of these parameters, to calculate the center line position in the bearing, and the dynamic coefficients of journal bearings / Mestrado / Mecanica dos Sólidos e Projeto Mecanico / Mestra em Engenharia Mecânica

This master´s thesis deals with calibration and determination of uncertainties of measurement for focus variation microscope Alicona Infinite Focus G4. Together with calibration, a measurement of chosen parameters with calculation of measurement uncertainties of a component was realised. The thesis also describes the whole calibration process and terminology used in calibration, as well as the calibrated instrument, it´s parameters and usage in practice. The measurements were realized on premises of Intemac Solutions s.r.o. Obtained data were than processed using MS Excel, Gwyddion and TalyMap software. At the end of the thesis, practical recommendations are formulated.

Transportation underlines the vehicle industry's critical role in a country's economic future.The amount of goods moved, specically by trucks, is only expected to increase inthe near future. This work attempts to tackle the problem of optimizing fuel consumptionin Volvo trucks, when there are hard constraints on the delivery time and speed limits.Knowledge of the truck such as position, state, conguration etc., along with the completeroute information of the transport mission is used for fuel optimization.Advancements in computation, storage, and communication on cloud based systems, hasmade it possible to easily incorporate such systems in assisting modern eet. In this work,an algorithm is developed in a cloud based system to compute a speed plan for the completemission for achieving fuel minimization. This computation is decoupled from thelocal control operations on the truck such as prediction control, safety, cruise control, etc.;and serves as a guide to the truck driver to reach the destination on time by consumingminimum fuel.To achieve fuel minimization under hard constraints on delivery (or arrival) time andspeed limits, a non-linear optimization problem is formulated for the high delity modelestimated from real-time drive cycles. This optimization problem is solved using a Nonlinearprogramming solver in Matlab.The optimal policy was tested on two drive cycles provided by Volvo. The policy wascompared with two dierent scenarios, where the mission demands hard constraints ontravel time and the speed limits in addition to no trac uncertainties (deterministic). with a cruise controller running at a constant set speed throughout the mission. Itis observed that there is no signicant fuel savings. with maximum possible fuel consumption; achieved without the help of optimalspeed plan (worst case). It is seen that there is a notable improvement in fuelsaving.In a real world scenario, a transport mission is interrupted by uncertainties such as trac ow, road blocks, re-routing, etc. To this end, a stochastic optimization algorithm is proposedto deal with the uncertainties modeled using historical trac ow data. Possiblesolution methodologies are suggested to tackle this stochastic optimization problem.

In this thesis, we study three periodic-review, finite-horizon inventory systems in the presence of supply and demand uncertainties. In the first part of the thesis, we study a multi-period single-station problem in which supply uncertainty is modeled by partial supply. Formulating the problem under a robust optimization (RO) framework, we show that solving the robust counterpart is equivalent to solving a nominal problem with a modified deterministic demand sequence. In particular, in the stationary case the optimal robust policy follows the quasi-(s, S) form and the corresponding s and S levels are theoretically computable. In the second part of the thesis, we extend the RO framework to a multi-period multi-echelon problem. We show that for a tree structure network, decomposition applies so that the optimal single-station robust policy remains valid for each echelon in the tree. Furthermore, if there are no setup costs in the network, then the problem can be decomposed into several uncapacitated single-station problems with new cost parameters subject to the deterministic demands. In the last part of the thesis, we consider a periodic-review Assemble-To-Order (ATO) system with multiple components and multiple products, where the inventory replenishment for each component follows an independent base-stock policy and product demands are satisfied according to a First-Come-First-Served (FCFS) rule. We jointly consider the inventory replenishment and component allocation problems in the ATO system under stochastic component replenishment lead times and stochastic product demands. The problems are formulated under the stochastic programming (SP) framework, which are difficult to solve exactly due to a large number of scenarios. We use the sample average approximation (SAA) algorithms to find near-optimal solutions, which accuracy is verified by the numerical experiment results. / Thesis / Doctor of Philosophy (PhD)

The Cloud Imaging and Particle Size (CIPS) instrument on the Aeronomy of Ice in the Mesosphere satellite images in the nadir at the UV wavelength of 265 nm. The camera array has an approximately 120° along track (2000 km) by 80° cross track (1000 km) field of view at a horizontal resolution of 1 by 2 km in the nadir. The satellite is in a sun synchronous orbit with an approximately noon local time equator crossing. The observed albedo is due to Rayleigh scattered sun light from an altitude of approximately 50 km and sunlight scattered from Polar Mesospheric Clouds (PMC) which occur in the summer mesosphere at 83 km. The goal of the CIPS instrument is to retrieve high horizontal resolution maps of PMC albedo and the mode radius of the particle size distribution. The first manuscript analyzes the uncertainties involved in the retrieval. The ability to infer mode radius from the PMC signal is made significantly harder by the presence of the Rayleigh signal. Much of the difference between PMC signals of different mode radii is also consistent with possible changes in the Rayleigh signal. The signal is decomposed into components which isolate the portion of the PMC signal's dependence on radius which is not consistent with changes in the Rayleigh signal. This isolated component is compared with the measurement noise to estimate and understand the uncertainties in the CIPS retrieval. The presence of the Rayleigh signal is a difficulty in the PMC retrieval, but it is also a valuable data product. The second manuscript highlights the initial findings of a new gravity wave data set developed by the author. The data set provides relative ozone variations at the stratopause with a horizontal resolution of 20 by 20 km. An abundance of gravity wave signatures can be seen in the data which appear to emanate from weather events like thunderstorms and hurricanes as well as orographic sources such as the Andes and the Antarctic Peninsula. The data set fills a gap that presently exists in our observational coverage of gravity waves, so the data set should help significantly in constraining Global Climate Models. / Ph. D.

Submitted by Nadir Basilio (nadirsb@uninove.br) on 2017-06-21T15:17:03Z No. of bitstreams: 1 João Luiz de Mello Tavares Feola.pdf: 5309708 bytes, checksum: d5c41cb81a5edeb9b009813c8ec264ce (MD5) / Made available in DSpace on 2017-06-21T15:17:03Z (GMT). No. of bitstreams: 1 João Luiz de Mello Tavares Feola.pdf: 5309708 bytes, checksum: d5c41cb81a5edeb9b009813c8ec264ce (MD5) Previous issue date: 2016-06-24 / Business organizations and their projects are becoming increasingly complex and demanding constants innovations, looking to comply with an increasingly demanding and knowledgeable market need. In many cases, these innovative projects do not have welldefined requirements in the initial planning and need refinement scope in the execution course, which could disrupt the final project acceptance and quickly decision making. Uncertainties are a major cause of rework, cost increases and project deadlines changes. In extreme cases, they can even generate social and financial impacts. For this, it is necessary a dynamic and iterative approach between the team and the project stakeholders, which must abandon systemic management standards and pass thought in the customer problems and needs. The Design Thinking proposes a concept of collaborative work among stakeholders and project team, developing prototypes which are refined cyclically to its final stage and have shown to be a promising approach in education and engineering areas. This study aims to identify the DT characteristics and the corporate and its projects uncertainties types, checking also how it can help reduced. For this evaluation, we carried out qualitative interviews with nine experts, mostly professionals with graduate, active on seven different organizations. The analysis indicated that the majority DT approach has as predominates characteristics the involvement and relationship with the human being, tends to develop the creative thinking and use brainstorming techniques and customer feedback to develop their projects, increasing project acceptance and contractors satisfaction. / As organizações empresariais e seus projetos vêm se tornando cada vez mais complexos e exigindo constantes inovações, visando assim atender às necessidades de um mercado cada vez mais exigente e bem informado. Em muitos casos, estes projetos inovadores não possuem requisitos bem definidos em seu planejamento inicial e necessitam de refinamento de escopo no decorrer de sua execução, devido ao grande número de incertezas presentes. Para isto, faz-se necessário uma abordagem mais dinâmica e interativa entre a equipe e os stakeholders do projeto, para focar nas necessidades e problemas do cliente final. O Design Thinking propõe um conceito de trabalho colaborativo entre as partes interessadas e o time do projeto, desenvolvendo protótipos que são refinados de forma iterativa até sua conclusão e vêm se mostrando uma abordagem promissora em áreas como educação e engenharia. O presente estudo tem como propósito identificar como o Design Thinking pode contribuir para reduzir as incertezas. Para essa identificação, realizou-se entrevistas qualitativas com nove especialistas, em sua maioria profissionais com pós graduação, atuantes de sete organizações distintas. A análise indicou que em sua maioria a abordagem DT possui características predominantes de relacionamento e envolvimento do ser humano, que tende a desenvolver o pensamento criativo e utilizar técnicas de brainstorming e feedback do cliente para o desenvolvimento de seus projetos. Observou-se que a característica do DT ser centrado no humano é utilizado em projetos com incerteza de stakeholders para mitiga-la, assim como a ideação e experimentação é usada para diminuir as incertezas tecnológicas.

Intégrée dans la chaîne décisionnelle de la Supply Chain à un niveau tactique, la Planification de Production est un process clé qui permet de répondre au mieux aux besoins selon les ressources de l’entreprise. Un des défis du domaine est la gestion des incertitudes prévisionnelles, ayant des conséquences importantes sur des indicateurs clés comme le taux de service ou les coûts. Pour y faire face, des méthodes améliorant la flexibilité des processus sont mais en place, comme le contexte de travail en Plan Glissant. Cependant, en actualisant fréquemment les données, la stabilité du système se retrouve dégradée. Ainsi, malgré les gains issus de la gestion des incertitudes, ce cadre crée une complexité dynamique à gérer. Ce travail traite de cette complexité issue de l’actualisation des prévisions pour la planification de production en plan glissant. Plus particulièrement, la question traitée ici concerne l’optimisation du plan de production, en considérant u n système mono-produit monoétage. Une modélisation mathématique générique est tout d’abord développée pour construire un modèle d’optimisation théorique du problème. Ensuite, une procédure de résolution optimale est développée en utilisant le cadre d’optimisation dynamique stochastique. Ce modèle est appliquée à des cas concrets pour lesquels l’optimalité des solutions calculées est prouvée analytiquement grâce à un raisonnement inductif basé sur des séquences de calcul d’espérances mathématiques. Des analyses numériques finalement conduites mettent en exergue les performances de la méthode développée, ses limites, et sa sensibilité vis-à-vis de l’environnement industriel. / Production Planning, as part of tactical operations integrated into the Supply Chain process, is a key procedure allowing decisioners to balance demand and production resources. One of its most challenging issues is to handle uncertainties, especially the ones coming from the Forecasted Demand. In order to manage indicators at stake, such as service level and costs, best practices increasing flexibility in the process are implemented, as Rolling-Plan Framework. However, it creates instability since the updates procedures make the data set on change constantly. Consequently, although the gain in terms of flexibility is non-negligible for the uncertainties management, it generates on the other hand dynamics complexity. We study in this work how to deal this dynamics complexity generated by updates of the Forecasted Demand made in a Rolling-Plan Framework of a Production Planning Process. In particular, the question to which it answers is how to optimize the Production Plan in such a context. This issue is tackled considering a single item single level production system. A general mathematical model in the context of our study is built to be exploitable for analytical optimization. A theoretical optimization framework is designed, and a specific solutions computation framework using stochastic dynamic programming is developed. We apply it in some precise study cases in order to compute optimal solutions and get some valuable analytical results thanks to a dynamic computation process. The optimality of the solutions is proven through an inductive reasoning based on expectations computation. Solutions are finally implemented and calculated numerically with simulations in some particular numerical examples. Analyses and sensitivity studies are performed, highlighting the performances of our optimization method.