New helicopter rotor designs are desired that offer increased efficiency, reduced vibration, and reduced noise. This problem is multidisciplinary, requiring knowledge of structural dynamics, aerodynamics, and aeroacoustics. Rotor optimization requires achieving multiple, often conflicting objectives. There is no longer a single optimum but rather an optimal trade-off space, the Pareto Frontier. Rotor Designers in industry need methods that allow the most accurate simulation tools available to search for Pareto designs. Computer simulation and optimization of rotors have been advanced by the development of "comprehensive" rotorcraft analysis tools. These tools perform aeroelastic analysis using Computational Structural Dynamics (CSD). Though useful in optimization, these tools lack built-in high fidelity aerodynamic models. The most accurate rotor simulations utilize Computational Fluid Dynamics (CFD) coupled to the CSD of a comprehensive code, but are generally considered too time consuming where numerous simulations are required like rotor optimization. An approach is needed where high fidelity CFD/CSD simulation can be routinely used in design optimization. This thesis documents the development of physics based rotor simulation frameworks. A low fidelity model uses a comprehensive code with simplified aerodynamics. A high fidelity model uses a parallel processor capable CFD/CSD methodology. Both frameworks include an aeroacoustic simulation for prediction of noise. A synergistic process is developed that uses both frameworks together to build approximate models of important high fidelity metrics as functions of certain design variables. To test this process, a 4-bladed hingeless rotor model is used as a baseline. The design variables investigated include tip geometry and spanwise twist. Approximation models are built for high fidelity metrics related to rotor efficiency and vibration. Optimization using the approximation models found the designs having maximum rotor efficiency and minimum vibration. Various Pareto generation methods are used to find frontier designs between these two anchor designs. The Pareto anchors are tested in the high fidelity simulation and shown to be good designs, providing evidence that the process has merit. Ultimately, this process can be utilized by industry rotor designers with their existing tools to bring high fidelity analysis into the preliminary design stage of rotors.

The broad aim of this research is to contribute knowledge that enables improvements in how designers model decision alternatives at the systems level—i.e., how they model different system configurations and concepts. There are three principal complications: (1) design concepts and systems configurations are partially-defined solutions to a problem that correspond to a large set of possible design implementations, (2) each concept or configuration may operate on different physical principles, and (3) decisions typically involve tradeoffs between multiple competing objectives that can include "non-engineering" considerations such as production costs and profits. This research is an investigation of a data-driven approach to modeling partially-defined system alternatives that addresses these issues. The approach is based on compositional strategy in which designers model a system alternative using abstract models of its components. The component models are representations of the rational tradeoffs available to designers when implementing the components. Using these models, designers can predict key properties of the final implementation of each system alternative. A new construct, called a parameterized efficient set, is introduced as the decision-theoretic basis for generating the component-level tradeoff models. Appropriate efficiency criteria are defined for the cases of deterministic and uncertain data. It is shown that the model composition procedure is mathematically sound under reasonable assumptions for the case of deterministic data. This research also introduces an approach for describing the valid domain of a data-driven model based on the use of support-vector machines. Engineering examples include performing requirements allocation for a hydraulic log splitter and architecture selection for a hybrid vehicle.

Several techniques were studied to select and prioritize technologies for a complex system. Based on the findings, a method called Pareto Optimization and Selection of Technologies (POST) was formulated to efficiently explore the combinatorial technology space. A knapsack problem was selected as a benchmark problem to test-run various algorithms and techniques of POST. A Monte Carlo simulation using the surrogate models was used for uncertainty quantification. The concepts of graph theory were used to model and analyze compatibility constraints among technologies. A probabilistic Pareto optimization, based on the concepts of Strength Pareto Evolutionary Algorithm II (SPEA2), was formulated for Pareto optimization in an uncertain objective space. As a result, multiple Pareto hyper-surfaces were obtained in a multi-dimensional objective space; each hyper-surface representing a specific probability level. These Pareto layers enabled the probabilistic comparison of various non-dominated technology combinations. POST was implemented on a technology exploration problem for a 300 passenger commercial aircraft. The problem had 29 identified technologies with uncertainties in their impacts on the system. The distributions for these uncertainties were defined using beta distributions. Surrogate system models in the form of Response Surface Equations (RSE) were used to map the technology impacts on the system responses. Computational complexity of technology graph was evaluated and it was decided to use evolutionary algorithm for probabilistic Pareto optimization. The dimensionality of the objective space was reduced using a dominance structure preserving approach. Probabilistic Pareto optimization was implemented with reduced number of objectives. Most of the technologies were found to be active on the Pareto layers. These layers were exported to a dynamic visualization environment enabled by a statistical analysis and visualization software called JMP. The technology combinations on these Pareto layers are explored using various visualization tools and one combination is selected. The main outcome of this research is a method based on consistent analytical foundation to create a dynamic tradeoff environment in which decision makers can interactively explore and select technology combinations.

This thesis consists of four independent essays grouped in two parts. The first part analyzes the possibility and duration of a Pareto-improving pension reform. The second part considers some economic issues related to the tax avoidance activities. The possibility and duration of a Pareto-improving pension reform.Many countries face large problems in supporting current pay-as-you-go pension systems arising from demographic changes leading to the situation when returns on capital exceed population growth. Inefficiency arises from implicit taxation on pension contributions. In a closed economy, it is even more destructive due to its negative impact on savings and capital accumulation. Although the transition to a fully funded system is a great improvement of the economy, its implementation entails several difficulties if Pareto-efficiency is required. The first essay, “The Possibility of a Pareto Improving Pension Reform in a Heterogeneous Economy”, demonstrates that Pareto-improving transitions from pay-as-you-go to fully funded pension systems nearly always exist. To demonstrate this, I classify existing theoretical results according to the type of reformed economy, the form of pension benefits, and the policy instruments used during the transition. Then, I show that intergenerational heterogeneity should no longer be considered as an obstacle when implementing Pareto-improving pension reforms. To maintain redistributive or insurance mechanisms supported by pay-as-you-go systems, I propose to replace inefficient social security with redistributive tax and transfer payments inside one generation. This would save the economy from the inefficiency related to the implicit taxes on pension contributions imposed by pay-as-you-go systems. The second essay, “Designing Optimal Pareto Improving Pension Reforms: A More Distorted Economy Can be Reformed Faster”, investigates the optimal Pareto-improving debt-financed transition from pay-as-you-go to fully funded pension systems. In particular, I examine the relationship between key parameter values characterizing the preferences, the technology and the size of the initial system, and the necessary time for a Pareto-improving transition. My finding is that a more distorted economy can be reformed faster. This result gives an additional explanation to the success of the Chilean reform, where an initial pay-as-you-go system was the largest and, at the same time, the most distorting.An Economy with Clever Tax Avoidance Providers.In the third essay “The Importance of Income Distribution for the Price of the Tax Avoidance Service”, I design a model with a clever tax avoidance provider, who maximizes a profit by setting the price for the tax avoidance services. Therefore, the price for the tax avoidance service is endogenously defined. In that setup, the change in income distribution is not less important than changes in the tax code, which together are responsible for the tax avoidance demand. The model has a wide range of applications. In particular, I analyze the relation between inequality and the collection of tax revenue. The paper shows that tax revenue as a percentage of GDP might grow with inequality when the tax code is not significantly changed. Moreover, higher inequality implies lower marginal cost of additional revenue. This assay also considers tax base broadening, providing examples where this leads to a reduction in tax revenue.In the fourth essay, “ Tax Avoidance as a Reason for Secession”, I provide an additional explanation for the intentions to secede related to expected changes in the tax codes after the ''break down of a nation''. To demonstrate my points, I use a tax avoidance model designed in the third essay, where active tax avoidance providers make a decision about the price and quantity of their services. Secession gives the avoidance provider the option of setting different prices in separate regions.  As a consequence, the price for the tax avoidance service may fall in the poorer region and the elite of this region would be able to avoid the tax, which is impossible in union. Moreover, regional separation may lead to tremendous changes in the shape of income distribution, forcing new governments to change the tax codes. Thus, the government of the richer region may reduce tax rates in order to enlarge the tax revenue collection. To avoid a breakdown of the state, the government should reduce inefficient spending and tax duties. Promoting democracy or increasing the political influence of poor households may reduce the tendency to separate. / Diss. Stockholm : Handelshögskolan, 2002

Diss. Stockholm : Handelshögskolan, 2002.

Calif., Univ., Dep. of Economics, Diss.--Stanford, 2004. / Kopie, ersch. im Verl. UMI, Ann Arbor, Mich. - Enth. 3 Beitr.

Thesis (MScEng)--Stellenbosch University, 2011. / ENGLISH ABSTRACT: Reconfigurable Manufacturing Systems (RMSs) have the ability to reconfigure hardware and control resources at all of the functional and organizational levels. This allows for quick adjustment of production capacity and functionality in response to sudden changes in market or in regulatory requirements. This study evaluates the characteristics and operation of automated reconfigurable assembly lines using discrete event simulation. The assembly line uses a conveyor system which transports pallets to various machines to perform the assembly process. Different conveyor configurations are developed for the same assembly process using Simio simulation software. A part family consisting of five variants are assembled on the same assembly line with a large variation in the production quantities for each product. This requires the assembly system to be able to quickly adjust its functionality and capacity. Multi-objective optimization is performed on the models through the use of a Pareto exhaustive search experiment. The two contradicting objectives used are the throughput rate of the system and the average work in progress, with the aim of maximizing the former and minimizing the latter. From the Pareto exhaustive search experiment, a Pareto front is constructed showing which configuration is preferred under certain operation conditions. However it is concluded that the Pareto front can be tailored to fit the specific needs of the decision maker, depending on what the decision maker is willing to pay. An experiment that evaluates the effect of changing the conveyor speed is performed. It is established that under certain operating conditions, increasing the conveyor speed higher than the ceiling value will not improve the performance of the system. A production scenario was also developed which include different order sizes for each of the five parts of the part family. The configurations have to alter their capacities based on the order sizes to test which system performs the best under these operating conditions. For this experiment, the ramp-up time was of interest but the best system was chosen based on the combination of throughput rate and the average work in progress. From the results of the different experiments, it is recommended to first determine the maximum capacity and the operating logic before choosing one of the configurations. Once this is decided, the information gathered from the experiments can then be tailored for the decision maker to establish the best operating conditions for the chosen con guration. The developed simulation models are used as a Decision Support System for future research on the topic. It is recommended for future research to focus on using Automated Guided Vehicles (AGVs) instead of a conveyor system as transportation method. / AFRIKAANSE OPSOMMING: Herkonfigureerbare Vervaardigingstelsels (HVSs) het die vermoee om alle hardeware en beheer hulpbronne, op alle funksionele en organisatoriese vlakke te herkonfigureer. Dit maak dit moontlik vir vinnige verstellings aan produksie kapasiteit en funksionaliteit, indien daar 'n skielike verandering in die mark of wetgewing is. Hierdie studie evalueer die karakteristieke en werking van outomatiese herkon gureerbare monteerlyne met behulp van diskrete gebeurtenis simulasie. Die monteerlyne gebruik vervoerbande om pallette na verskeie masjiene te vervoer, sodat die parte aanmekaar gesit kan word. Simio simulasie sagteware is gebruik om verskillende vervoerband kon gurasies vir dieselfde monteringsproses te ontwikkel. 'n Part familie van vyf variante word op dieselfde monteerlyn aanmekaargesit. Daar is 'n groot variasie in die produksie hoeveelhede van elk van die vyf variante, dus moet die monteerlyne vinnig die kapasiteit en funksionaliteit kan aanpas. Multi-doelwitoptimering is toegepas op die modelle deur 'n Pareto alomvattende soek eksperiment uit te voer. Die twee teenstrydige doelwitte wat gebruik is, is die deurset tempo van die stelsel asook die gemiddelde werk-in-proses. Die doel is om die deurset tempo te maksimeer en terselfde tyd die gemiddelde werk-in-proses te minimeer. Die Pareto alomvattende soek eksperiment word verder gebruik om 'n Pareto front te skep wat uitwys watter vervoerband kon gurasies verkies word onder sekere bedryfstoestande. Die Pareto front kan egter aangepas word om die spesi eke behoeftes van die besluitnemer te pas. 'n Eksperiment is uitgevoer om die uitwerking van die vervoerbandspoed op die stelsel te toets. Resultate het getoon dat onder sekere bedryfstoestande die werkverrigting van die stelsel nie verbeter indien die spoed 'n maksimum grenswaarde oorskry nie. 'n Eksperiment wat 'n produksie scenario voorstel is ontwikkel waarin die vraag na die vyf part variante gevarieer word. Die vervoerband konfigurasies moet dan die kapasiteit aanpas gebaseer op die vraag na die parte. Die doel van die eksperiment is om te toets watter kon gurasie die beste vaar onder hierdie bedryfstoestande. Die tyd wat dit neem vir die stelsel om weer op dreef te kom na 'n verandering in kapasiteit is ondersoek in hierdie eksperiment, maar die beste stelsel is nog steeds gekies gebaseer op die kombinasie van deurset tempo en die gemiddelde werk-in-proses. Gegewe die resultate van die verskillende eksperimente, word dit voorgestel dat die besluitnemer eers die maksimum kapasiteit en die bedryfstoestande vasstel, voordat 'n vervoerband kon gurasie gekies word. Sodra dit besluit is, kan die inligting wat tydens die eksperimente ingesamel is, aangepas word om die beste bedryfstoestande vir die kon gurasie wat gekies is, vas te stel. Die simulasie modelle wat ontwikkel is word gebruik as 'n besluitnemingsondersteuningstelsel vir toekomstige navorsing oor die onderwerp. Dit word voorgestel dat toekomstige navorsing die moontlikheid van geoutomatiseerde begeleide voertuie (GBV), in plaas van vervoerbande as vervoermiddel, ondersoek.

This thesis is dealing with the issue of risk management during order processing in manufacturing company, which is focused on textile production. Introduction of thesis is presenting theroretical basis. Practical part of the thesis is dealing with company introduction organizational structure of the body, product range, order progressing, OSH policy and environmental policy. Tools chosen for risk assessment techniques - analysis of the causes and consequences (Ishikawa diagram), analysis of possible errors and their consequences (FMEA) and the Pareto chart. The thesis aims to analyze the risks and for the most significant risks to process proposals for their elimination.

Many concrete problems may be cast in a multi-objective optimisation framework. The redundancy of existing methods for solving multi-objective programming problems susceptible to inconsistencies, coupled with the necessity for making in- herent assumptions before using a given method, make it hard for a nonspecialist to choose a method that ¯ts the situation at hand well. Moreover, using a method blindly, as suggested by the hammer principle (when you only have a hammer, you want everything in your hand to be a nail) is an awkward approach at best and a caricatural one at worst. This brings challenges to the design, development, implementation and deployment of a Decision Support System able to choose a method that is appropriate for a given problem and to apply the chosen method to solve the problem under consideration. The choice of method should be made according to the structure of the problem and the decision maker's opinion. The aim here is to embed a sample of methods representing the main multi-objective programming techniques and to help the decision maker find the most appropriate method for his problem. / Decisions Sciences / M. Sc. (Operations Research )

The aim of the "Quality management system in the selected company" dissertation work is an analysis of the current situation of the quality management system in a company and make suggestions to improve the current system. For my dissertation work I have chosen engineering company Motorpal, a. s., which is the engineering company and the one of the leading producers of devices for diesel engines to tractors, ships and construction machine.The work consists of two parts, theoretical and practical. The first part describes terms like quality, importance of quality, factors that affect quality, management principles of quality, economy of quality, quality in pre-production stages, quality planning and quality control tools. The second part is primarily focused on the quality costs, which is the most problematic part of the quality management in the company. In this part of the dissertation work is also briefly described the company and its history, company's production program and customers and company's financial situation, processes and quality management system.