In this thesis, capacity-constrained aspects of multi-level, multi-stage productionplanning are investigated. The aim has been to extend Material Requirements Planning Theory (MRP Theory) to cover more general problems dealing with capacity constraints, in particular when non-zero lead times are present and the processes take place in continuous time. MRP Theory deals with multi-level production systems with multiple items taking place either within a discrete or continuous time framework. External demand is considered either deterministic or stochastic. Lead times are assumed to be given constants, and the Net Present Value Principle has been applied as the objective function. The Bill-of-Materials, capturing component as well as capacity requirements, in volume as well as in advanced timing due to lead times, has been described using a generalised input matrix involving Laplace transforms or z transforms. In order to be able to apply Dynamic Programming as a solution method, the system state has been defined and designed in terms of a matrix, in which historical values of cumulative production and cumulative demand are given state variables. A high power computer has been used to calculate solutions to numerical examples. Moreover, this thesis examines the fundamental equations of MRP Theory in order to analyse the possibility to obtain closed-form expressions for the time development of the system, when standard ordering rules of MRP are applied. In addition, capacity-constrained production planning problems and procedures in a paper mill have been surveyed and are presented in the form of a case study.

A generic conflict model is developed to analyze international toxic waste disposal issues, and then, to provide feasible strategic resolutions for this serious environmental dispute. With the rapid growth of the global economy, toxic waste traffic from the advanced to developing nations has become a serious side effect of this globalization. The illegal transboundary movement of toxic wastes not only aggravates the burden on the poorer nations, but also negatively impacts the worldwide environment. In this thesis, the ongoing toxic waste disputes are divided into two stages consisting of the dumping prevention and dispute resolution stages. The analyses based on the methodology of Graph Model for Conflict Resolution are used in both stages in order to grasp the structure and implications of the conflict from a strategic viewpoint. The in-depth modeling of the toxic waste dumping disputes, which consist of historical and generic situations, specifies the involved parties and their options. By synthesizing the economic, political and legal factors, the relative preferences for each party can be determined. The Graphical User Interface (GUI) of the Decision Support System (DSS) GMCR II simplifies the processing of calculations. The analytical research furnishes investigators or other interested parties with possible resolutions for the disputes arising from an international waste dumping event. Sensitivity analyses are also conducted to provide a comprehensive understanding of the different situations that may occur in real-world cases. The case study of the Ivory Coast waste dumping controversy is used to demonstrate how to practically implement the generic multi-stage graph model.

A generic conflict model is developed to analyze international toxic waste disposal issues, and then, to provide feasible strategic resolutions for this serious environmental dispute. With the rapid growth of the global economy, toxic waste traffic from the advanced to developing nations has become a serious side effect of this globalization. The illegal transboundary movement of toxic wastes not only aggravates the burden on the poorer nations, but also negatively impacts the worldwide environment. In this thesis, the ongoing toxic waste disputes are divided into two stages consisting of the dumping prevention and dispute resolution stages. The analyses based on the methodology of Graph Model for Conflict Resolution are used in both stages in order to grasp the structure and implications of the conflict from a strategic viewpoint. The in-depth modeling of the toxic waste dumping disputes, which consist of historical and generic situations, specifies the involved parties and their options. By synthesizing the economic, political and legal factors, the relative preferences for each party can be determined. The Graphical User Interface (GUI) of the Decision Support System (DSS) GMCR II simplifies the processing of calculations. The analytical research furnishes investigators or other interested parties with possible resolutions for the disputes arising from an international waste dumping event. Sensitivity analyses are also conducted to provide a comprehensive understanding of the different situations that may occur in real-world cases. The case study of the Ivory Coast waste dumping controversy is used to demonstrate how to practically implement the generic multi-stage graph model.

In a fiber spinning process molten polymer is extruded into a fiber. The resulting fiber known as as-spun fiber is relatively weak and shows a large plastic central zone in its constitutive behavior. As a result the fiber deforms substantially without a significant change in load thus making it unsuitable for stress bearing applications. The range of plastic deformation is related to the natural draw ratio. In order to improve the mechanical properties of as spun fibers, fiber spinning is followed by a fiber draw process. With multi stage draw the as-spun fiber is drawn beyond the plastic region in various drawing zones which produces greater orientation of the polymer chains in the axial direction of the fiber thus enhancing mechanical strength characteristics of the fiber. The multistage draw process consists of several rollers each rotating at a speed greater than the one prior to it. The objective of this work is to develop a first approximation to model fiber draw in the multistage drawing process, with and without a draw pin. As the first step the slippage of fibers on rollers was analysed by including centrifugal acceleration and acceleration due to stretching. The draw in a free span is also modelled. Several representative draw processes were examined. It was found draw pin localizes the draw significantly although the resulting mechanical unloading complicates the analysis. Draw in the free span is impossible for isothermal draw processes, and anisothermal draw induces thermal unloading in the system. A comprehensive analysis of various draw processes will be examined.

The ability to produce potable water economically is the primary focus of seawater desalination research. There are numerous methods to desalinate water, including reverse osmosis, multi-stage flash distillation, and multi-effect evaporation. These methods cost more than potable water produced from natural resources; hence an attempt is made in this research project to produce potable water using a modified high-efficiency jet ejector in vapor-compression distillation. The greater efficiency of the jet ejector is achieved by properly mixing propelled and motive streams. From experiments conducted using air, the pressure rise across the jet ejector is better in case of one or two mixing vanes and the highest back pressure (pinch valve closed 83.33%). At other pinch valve closings, the air velocity through the jet ejector was high, so the extra surface area from the mixing vanes caused excessive friction and lowered the efficiency.

Vacuum technology is ubiquitous in the high tech industries and scientific endeavors. Since vacuum pumps are critical to operation, semiconductor manufacturers desire reliable operations, ability to schedule downtime, and less costly maintenance services. To better cope with difficult maintenance issues, interests in novel fault diagnosis techniques are growing. This study concerns model based fault diagnosis and isolation (MB-FDI) of dry vacuum pumps in the semiconductor industry. Faults alter normal operation of a vacuum pump resulting in performance deviations, discovered by measurements. Simulations using an appropriate mathematical model with suitably chosen parameters can mimic faulty behavior. This research focuses on the construction of a detailed multi-stage dry vacuum pump model for MB-FDI, and the development of a simple and efficient FDI method to analyze common incipient faults such as particulate deposition and gas leak inside the pump. The pump model features 0-D thermo-fluid dynamics, scalable geometric representations of Roots blower, claw pumps and inter-stage port interfaces, a unified pipe model seamlessly connecting from free molecular to turbulent regimes, sophisticated internal leakage model considering true pump geometry and tribological aspects, and systematic assembly of a multi-stage configuration using single stage pump models. Design of a simple FDI technique for the dry vacuum pump includes staged fault simulations using faulty pump models, parametric study of faulty pump behaviors, and design of a health indicator based on classification. The main research contributions include the developments of an accurate multi-stage dry pump model with many features not found in existing pump models, and the design of a simple MB-FDI technique to detect and isolate the common faults found in dry vacuum pumps. The proposed dry pump model can pave the way for the future development of advanced MB-FDI methods, also performance improvement of existing dry vacuum pumps. The proposed fault classification charts can serve as a quick guideline for vacuum pump manufactures to isolate roots causes from faulty symptoms. / text

L'incertitude a été toujours présente dans les problèmes d'optimisation. Dans ce travail, nous nous intéressons aux problèmes d'optimisation multi-niveaux où l'incertitude apparaît très naturellement. Les problèmes d'optimisation multi-niveaux avec incertitude ont suscité un intérêt à la fois théorique et pratique. L'optimisation robuste fait partie des méthodes les plus étudiées pour traiter ces problèmes. En optimisation robuste, nous cherchons une solution qui optimise la fonction objective pour le pire scénario appartenant à un ensemble d'incertitude donné. Les problèmes d'optimisation robuste multi-niveaux sont difficiles à résoudre, même de façon heuristique. Dans cette thèse, nous abordons les problèmes d'optimisation robuste à travers le prisme des méthodes de décomposition. Ces méthodes décomposent le problème en un problème maître (MP) et plusieurs problèmes satellites de séparation (AP). Dans ce contexte, les solutions et les relaxations heuristiques ont une importance particulière. Même pour les problèmes d'optimisation combinatoires, les relaxations sont importantes pour analyser l'écart de l'optimalité des solutions heuristiques. Un autre aspect important est l'utilisation des heuristiques comme integrés dans une méthode exacte. Les principales contributions de ce travail sont les suivantes. Premièrement, nous proposons une nouvelle relaxation pour les problèmes multi-niveaux basée sur l’approche dite d’information parfaite dans le domaine de l’optimisation stochastique. L'idée principale derrière cette méthode est d'éliminer les contraintes de non anticipativité du modèle pour obtenir un problème plus simple. Nous pouvons ensuite fournir des algorithmes combinatoires ad-hoc et des formulations de programmation mixte en nombres entiers compactes pour ce problème. Deuxièmement, nous proposons de nouveaux algorithmes de programmation dynamique pour résoudre les problèmes satellites apparaissant dans une classe spécifique de problèmes robustes pour un ensemble d'incertitude de type budget. Ce type d'incertitude est basé sur le nombre maximum d'écarts autorisés et leur taille. Ces algorithmes peuvent être appliqués à des problèmes de lot-sizing et à des problèmes de tournées de véhicules. Enfin, nous proposons un modèle robuste pour un problème lié à l’installation équitable de capteurs. Ce modèle fait le lien entre l'optimisation robuste et l'optimisation stochastique avec contraintes probabilistes ambigües. / Uncertainty has always been present in optimization problems, and it arises even more severely in multistage optimization problems. Multistage optimization problems underuncertainty have attracted interest from both the theoretical and the practical level.Robust optimization stands among the most established methodologies for dealing with such problems. In robust optimization, we look for a solution that optimizes the objective function for the worst possible scenario, in a given uncertainty set. Robust multi-stage optimization problems are hard to solve even heuristically. In this thesis, we address robust optimization problems through the lens of decompositions methods. These methods are based on the decomposition of the robust problem into a master problem (MP) and several adversarial separation problems (APs). The master problem contains the original robust constraints, however, written only for finite numbers of scenarios. Additional scenarios are generated on the y by solving the APs. In this context, heuristic solutions and relaxations have a particular importance. Similarly to combinatorial optimization problems, relaxations are important to analyze the optimality gap of heuristic solutions. Heuristic solutions represent a substantial gain from the computational viewpoint, especially when used to solve the separation problem. Because the adversarial problems must be solved several times, good heuristic solution may avoid the exact solution of the APs. The main contributions of this work are three-fold. First, we propose a new relaxation for multi-stage problems based on the approach named perfect information in the field of stochastic optimization. The main idea behind this method is to remove nonanticipativity constraints from the model to obtain a simpler problem for which we can provide ad-hoc combinatorial algorithms and compact mixed integer programming formulations. Second, we propose new dynamic programming algorithms to solve the APs for robust problems involving budgeted uncertainty, which are based on the maximum number of deviations allowed and on the size of the deviations. These algorithms can be applied to lot-sizing problems and vehicle routing problems among others. Finally, we study the robust equitable sensor location problem. We make the connection between the robust optimization and the stochastic programming with ambiguous probabilistic constraints. We propose linear models for several variants of the problem together withnumerical results.

Made available in DSpace on 2014-07-29T15:01:52Z (GMT). No. of bitstreams: 1 dissertacao daniela camplesi.pdf: 1230668 bytes, checksum: 56ed1f54e5e43d735ad2b69bff069adc (MD5) Previous issue date: 2009-12-18 / The present work has evaluated the efficiency of an MSF system for treating supplying water on a pilot scale. A MSF pilot plant was located in the Water Treatment Station (WTS) area in Goianápolis- GO and fed by Sozinha stream. The plant was comprised of a dynamic prefilter (DPF) and a vertical upflowing pre-filter (VUF) in layers, both of them with different granular compositions; a slow sand filter (SSF); and a slow sand filter with activated carbon (SSFAC), which was called SEQ. 1. The second sequence of the trial, SEQ. 2, was comprised of a dynamic pre-filter (DPF) and a slow sand filter (SSF-2). The filtration rates in use were 24 and 48 m3/m2 a day for DPF, 12 e 24 m3/m2. day for APF; 3 e 6 m3/m2. day for SSF and SSFAC. The efficiency was evaluated by analyzing turbidity, apparent color, total suspended solids (TSS), as well as total thermo tolerant coliforms. The following items were evaluated: the filtration rates ranging effect onto the MSF unit trial system efficiencies; the MSF system efficiency comparison to the WTS complete cycling treatment; and the correlations between turbidity, color, and coliforms removals and the TSS removals. The results obtained from the trials have shown that DPF and VUF are important units for microorganisms and solid particles retaining, for it prepares the effluent in order to submit it into slow filtration. They have also shown that they make it possible for the roughing filtration to last longer. Generally put, it presents that the slow filters are significantly and above 90% efficient in removing TSS, color and turbidity, and 99% efficient in removing total coliforms and thermotolerant coliforms in all roughing filtration. After comparing the quality of both the water produced by MSF and the one by the complete cycling WTS, it was noticed that MSF produces water with quality similar to the complete cycling WTS. The range for the filtration rates has had significant influence only in the removal efficiencies of color and turbidity. There isn t correlation among the removals of the parameters color, turbidity, TSS and coliforms but for the correlation among apparent color and true color. The experiment results suggest that MSF technology, when suitably operated, it is a viable system for the treatment of supplying water and produced water with low levels of color, turbidity, TSS and coliforms is that 40% of the samples, provided drinking water under conditions compatible to those established by Decree 518/2004 of the Ministry of Health (BRAZIL, 2004) for human consumption / O presente trabalho avaliou a eficiência de um sistema de FiME no tratamento de águas de abastecimento em escala piloto. A instalação piloto FiME, localizada na área da Estação de Tratamento de Água (ETA) de Goianápolis, GO e alimentada pelo Ribeirão Sozinha, era composta de um pré-filtro dinâmico (PFD), um pré-filtro com escoamento vertical ascendente (PFA) em camadas, ambos com composições granulométricas diferenciadas, um filtro lento de areia (FLA) e um filtro lento de areia com carvão ativado (FLAC) e foi denominada SEQ 1. A SEQ 2 do experimento era constituída de um pré-filtro dinâmico (PFD) e um filtro lento de areia (FLA-2). As taxas de filtração utilizadas foram 24 e 48 m3/m2. dia para PFD, 12 e 24 m3/m2. dia para PFA, 3 e 6 m3/m2. dia para FLA e FLAC. A eficiência foi avaliada por meio das análises de turbidez, cor aparente, sólidos suspensos totais (SST) e coliformes totais e termotolerantes. Foi avaliado também o efeito da variação das taxas de filtração nas eficiências das unidades do sistema FiME, a comparação da eficiência do sistema FiME com o tratamento de ciclo completo da ETA e as correlações entre as remoções de turbidez, cor, coliformes e a remoção de SST. Os resultados obtidos nos experimentos demonstraram que o PFD e PFA são unidades importantes para a retenção de partículas sólidas e microorganismos, preparando o afluente para ser submetido à filtração lenta e possibilitam maior duração das carreiras de filtração. De maneira geral, os filtros lentos apresentaram eficiências significativas e superiores a 90% para remoção de cor, turbidez, SST e 99,9% de eficiência para remoção de coliformes totais e termotolerantes em praticamente todas as carreiras de filtração. Quando comparada a qualidade da água produzida pelo sistema FiME com a ETA de ciclo completo, verificou-se que a FiME produz água com qualidade similar à ETA de ciclo completo. As variações das taxas de filtração influenciaram significativamente nas eficiências de remoção de cor e turbidez. Não há correlação entre as remoções dos parâmetros cor, turbidez, SST e coliformes mas há correlação para cor aparente e cor verdadeira. Os resultados obtidos nos experimentos sugerem que a tecnologia de FiME, quando operada adequadamente, é um sistema viável para o tratamento de águas de abastecimento e produziu água com baixos teores de cor, turbidez, SST e coliformes sendo que em 40% das amostras analisadas, proveu água potável em condições compatíveis às estabelecidas pela Portaria 518/2004 do Ministério da Saúde (BRASIL, 2004) para consumo humano

The main objective of this thesis is to build a multi-stage stochastic pro- gram within an asset-liability management problem of a leasing company. At the beginning, the business model of such a company is introduced and the stochastic programming formulation is derived. Thereafter, three various risk constraints, namely the chance constraint, the Value-at-Risk constraint and the conditional Value-at-Risk constraint along with the second-order stochastic dominance constraint are applied to the model to control for riski- ness of the optimal strategy. Their properties and their effects on the optimal decisions are thoroughly investigated, while various risk limits are considered. In order to obtain solutions of the problems, random elements in the model formulation had to be approximated by scenarios. The Hull - White model calibrated by a newly proposed method based on maximum likelihood esti- mation has been used to generate scenarios of future interest rates. In the end, the performances of the optimal solutions of the problems for unconsid- ered and unfavourable crisis scenarios were inspected. The used methodology of such a stress test has not yet been implemented in stochastic programming problems within an asset-liability management. 1

By means of car2x communication technologies (car2x) driver warnings can be presented to drivers quite early. However, due to their early timing they could be misunderstood by drivers, distract or even disturb them. These problems arise if, at the moment of the warning, the safety–critical situation is not yet perceivable or critical. In order to examine, when drivers want to receive early warnings as a function of the situation criticality, a driving simulator study was conducted using the two early warning stages of a multi stage collision warning system (first stage: informing the driver; second stage: prewarning the driver). The optimum timing to activate these two early warning stages was derived by examining the drivers’ evaluation of these timings concerning their appropriateness and usefulness. As situational variation, drivers traveling at about 100 km/h were confronted with slow moving traffic either driving at 25 km/h or 50 km/h at the end of a rural road. In total, 24 participants were tested in a within-subjects design (12 female, 12 male; M = 26.6 years, SD = 7.2 years). For both stages, drivers preferred an earlier timing when approaching slow moving traffic traveling at 25 km/h (first stage: 447 m, second stage: 249 m ahead of the lead vehicle) compared to 50 km/h (first stage: 338 m, second stage: 186 m ahead of the lead vehicle). The drivers’ usefulness rating also varied with the timing, spanning a range of 8 s for driver-accepted timing variations and showed correspondence to the drivers’ appropriateness ratings. Based on these results and those of a previous study, a timing function for each of the two early warning stages depending on the speed difference between the safety–critical object and the host vehicle is presented. Indirectly, similar adaptations are already implemented in current collision warning systems, which use the time-to-collision to give drivers acute warnings in a later stage, when an immediate reaction of the driver may still prevent a collision. However, this study showed that drivers also favor this kind of adaptation for earlier warning stages (information and prewarning). Thus, adapting the timing according to the drivers’ preferences will contribute to a better acceptance of these collision warning systems.