Submitted by Bruna Rodrigues (bruna92rodrigues@yahoo.com.br) on 2016-10-05T13:21:28Z No. of bitstreams: 1 TeseRFF.pdf: 11255323 bytes, checksum: 6490de6218937c15e5bbdc6d9672a300 (MD5) / Approved for entry into archive by Marina Freitas (marinapf@ufscar.br) on 2016-10-20T18:15:52Z (GMT) No. of bitstreams: 1 TeseRFF.pdf: 11255323 bytes, checksum: 6490de6218937c15e5bbdc6d9672a300 (MD5) / Approved for entry into archive by Marina Freitas (marinapf@ufscar.br) on 2016-10-20T18:15:59Z (GMT) No. of bitstreams: 1 TeseRFF.pdf: 11255323 bytes, checksum: 6490de6218937c15e5bbdc6d9672a300 (MD5) / Made available in DSpace on 2016-10-20T18:16:05Z (GMT). No. of bitstreams: 1 TeseRFF.pdf: 11255323 bytes, checksum: 6490de6218937c15e5bbdc6d9672a300 (MD5) Previous issue date: 2016-05-04 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) / Solid-state fermentation is characterized by the growth of microorganisms in absence of free water. In one hand, it is advantageous because simulates their natural environment, enabling the use of agro industrial residues in natura. On the other hand, it limits heat transfer between elements, restricting control over the temperature of the medium. In fact, the microbial growth and the product formation dynamics are directly affected by the environmental conditions and variations can be harmful to the process productivity. As a consequence, the temperature increase caused by metabolic heat needs to be avoided. Studies concerning the microbial dynamics dealing with these variations are scarce. Moreover, it was not found any control laws, with guarantee of stability, which was designed for a reference tracking and to minimize the disturbances effects. Thus, two fronts need to be addressed for the solid-state fermentation viability: the development of a mathematical model able to estimate the effects of environmental changes in the process; and a temperature control system able to handle the heat from microbial metabolism. The model was used in a computational algorithm in order to determine if there was a temperature profile that would be more favorable to the products formation. In this work two control laws were studied, a proportional integrative, because it is the most widespread in the industry, and a model base predictive controller, because of its multivariable control versatility. Both control laws were simulated and then implemented in an eleven liters agitated drum bioreactor. Some of the various methods for PI controller parameters settings had their performance and relative stability requirement evaluated. The one that was proved stable was implemented in the bioreactor. Due to the uncertainties of the fermentation process, a self-adjustment mechanism was added to the predictive controller, in spite of the developed mathematical model, in order to avoid some estimation mistakes caused by some non-estimated states of the real process. The controller achieved an adequate performance with this approach. The results showed that the microorganisms were more efficient at a constant 32°C temperature. In addition, both developed controllers presented appropriate results facing the fermentation process requirement, with mean deviances from the referential temperature below 0,6°C and a maximum error of 2,8°C. / Uma das características da fermentação em estado sólido é que ela ocorre na ausência de água livre. Isso a torna vantajosa por simular o ambiente natural dos microrganismos com possibilidade de uso de resíduos agroindustriais in natura. Por outro lado, dificulta a transferência de calor entre os elementos do processo e, com isso, a capacidade de controlar a temperatura do meio fica debilitada. Por sua vez, a dinâmica do crescimento microbiano e a formação de produtos de interesse estão diretamente relacionadas às condições ambientais, cujas variações podem ser prejudiciais à produtividade do processo. Ao mesmo tempo, o calor gerado pelo metabolismo microbiano aumenta a temperatura do processo, que necessita ser regulada. Estudos que revelam como os microrganismos se comportam frente essas variações são escassos. Além disso, não foram encontradas leis de controle para a FES, com garantia de estabilidade, a fim de se minimizar os efeitos dos distúrbios. Duas frentes se destacam para a viabilização da FES: o desenvolvimento de um modelo matemático capaz de estimar os efeitos das variações das condições ambientais na dinâmica do processo e um sistema de controle da temperatura apropriado para lidar com os distúrbios gerados pelo crescimento celular. Em conjunto com a modelagem matemática, foram empregados mecanismos computacionais para averiguar qual seria o perfil de temperaturas que mais favorece à formação dos produtos. Por sua vez, foram estudados dois tipos de controladores: os proporcionais integrativos, pela ampla aplicação industrial, e os preditivos baseados em modelo, pela versatilidade no controle multivariável. Os sistemas de controle foram testados em um biorreator de 11 litros de volume nominal. Dentre várias, algumas metodologias para ajuste dos controladores proporcionais integrativos foram avaliadas nos quesitos desempenho e estabilidade relativa durante a fase de simulações. A metodologia que se provou estável nos testes realizados foi implementada no biorreator. Já para o controlador preditivo, frente às incertezas do processo fermentativo, foi necessário desenvolver um mecanismo de auto ajuste do modelo desenvolvido, a fim de que os erros dos estados não estimados do processo real fossem compensados e o controlador tivesse um desempenho adequado. Os resultados mostraram que o microrganismo, Aspergilus niger 3T5B8, produz uma quantidade maior de metabólitos de interesse a uma temperatura constante de 32°C. Além disso, ambos controladores utilizados apresentaram resultados apropriados aos requisitos do processo fermentativo, ou seja, com desvio médio da temperatura de referência menor do que 0,6°C.

Este trabalho descreve a aplicação de redes neurais \"feed-forward\" com três camadas em diferentes áreas da Engenharia Química. O objetivo principal do projeto é a modelagem, simulação e posterior otimização do processo de produção de isopreno empregando técnicas de redes neurais em substituição as equações de modelagem fenomenológica. A planta industrial testada é a unidade de produção de isopreno da BRASKEM (antiga COPENE). O sistema consiste essencialmente de um reator de dimerização e uma série de colunas de destilação. Uma vez que redes neurais são capazes de aprender eficientemente o processo a partir de informações extraídas diretamente de dados da planta, para este trabalho o modelo de rede neural gerado foi construído a partir de dados históricos operacionais coletados a cada 15 minutos durante o período de 1 ano. Em uma primeira etapa é realizada a análise dos dados operacionais de modo a detectar e eliminar erros grosseiros e sistemáticos. Em seguida, a modelagem e simulação do processo são realizadas. O modelo de redes neurais gerado é, então, empregado na otimização qualitativa/quantitativa do processo, construindo um \"grid\" de busca detalhado da região de interesse, através um mapeamento completo da função objetivo no espaço das variáveis de decisão. A segunda etapa diz respeito à predição de azeótropos, visando um melhor entendimento do comportamento do sistema da seção de extração de isopreno. Nas duas etapas, a grande vantagem em utilizar modelos de redes neurais, além de ajustar dados, é a capacidade que estes apresentam em representar eficientemente sistemas multivariáveis, complexos e não lineares, aprendendo o sistema, sem o conhecimento das leis físicas e químicas que o regem. Comparações entre a predição dos modelos propostos e os dados experimentais foram executadas e resultados muito bons foram conseguidos do ponto de vista industrial. ) Esta metodologia fornece informações interessantes e de maior compreensão para a análise dos engenheiros de processo do que os procedimentos convencionais correspondentes. Além disso, este trabalho mostra que a metodologia de redes neurais é promissora para varias aplicações indústrias, tais como análise de dados, modelagem, simulação e otimização de processos, bem como predição de propriedades termodinâmicas. / This work describes the application of a three-layer feed-forward neural network (NN) in different areas of chemical engineering. The main objective of this study is to model, simulate and optimize a real industrial plant, using NN by replacing phenomenological models. The industrial process studied is the isoprene production unit from BRASKEM. The chemical process consists basically of a dimerization reactor and a separation column train. Since NNs are able to extract information from plant data in an efficient manner, for this work, the neural network model was built directly from historical plant data, which were collected every 15 minutes during a period of one year. These data were carefully analyzed in order to identify and eliminate gross error data and non-steady state operation data. The modeling using NN was carried out by parts in order to get information on intermediate streams. Then, the global model was built, by interconnecting each individual model, and used to simulate and optimize the process. The optimization procedure carries on a detailed grid search of the region of interest, by a full mapping of the objective function on the space of decision variables. The second stage of this work deals with the azeotropic prediction using also the neural network approach. The objective of this step was to obtain a better understanding of the system behavior in the isoprene extraction section. Since all the cases studied are non-linear, complex andmultivariable systems, NN approach appears as a technique of interest due to its capability of learning the system without knowledge of the physical and chemical laws that govern it. Comparisons between the model\'s prediction and the experimental data were performed and reasonable results were achieved from an industrial point of view. ) Using neural network approach provides more comprehensive information for an engineer\'s analysis than the conventional procedure. This work shows that the use of NN methodology is promising for several industrial applications, such as data analysis, modeling, simulation and optimization process, as well as thermodynamics properties prediction. However, success in obtaining a reliable and robust NN depends strongly on the choice of the variables involved, as well as the quality of available data set and the domain used for training purposes.

This thesis deals with questions regarding quality assurance and software testing. The subject of its theoretical part is the specification of the general concept of quality, description of standards used in the field of software product quality evaluation and finally the evaluation of software development process itself. The thesis intends to introduce the theoretical framework of software quality assurance, especially the detailed analysis of the whole software testing branch. An added value to the theoretical part constitutes the characterization of procedural approach and selected methods used towards the improvement of processes. The practical part of the thesis comprises of the exemplification -- it shows the procedural approach at software quality management, applied to a selected IT company. The main aim of the practical part is to create a purposeful project for optimization of quality assurance and software testing processes. The core of the matter is to accomplish the process analysis of the present condition of software testing methodology. For the purpose of process analysis and optimization project, the models of key processes will be created; these processes will then be depicted based on defined pattern. The description of the state-of-the-art of software product quality assurance processes is further supplemented by the evaluation of such processes maturity. The project for optimization of software testing and quality assurance processes comes from the process analysis of the present condition of software testing methodology, as well as from the evaluation of procedural models maturity. The essence of processes optimization is the incorporation of change requests and innovative intentions of individual processes into the resulting state of methodology draft. For the measurement of selected quality assurance and software testing processes, the configuration of efficiency indicators and their application on particular processes is implemented. The research on the of the state-of-the-art, as well as the elaboration of this whole project for optimization of software testing and quality assurance processes runs in conformity with the principles of DMAIC model of Six Sigma method.

The master thesis deals with business process optimization which has to be in a place due to a global implementation of a new logistic information system. The aim is to ensure a process analysis of a current status of selected processes of a company part which is going to be influenced by this implementation. Then to highlight and to stress on the biggest risks and disadvantages of a current status. Final result will be a proposal of new optimized process flows on a higher level of maturity which will meet all requirements set by a new information system, by an information need of a local management and will be helpful to customer service improvement. The first part of the thesis covers theoretical base of a business process management, process modeling and business process optimization approaches which prepare a base for their application in the second practical part of this thesis.

The master thesis deals with optimization of business processes in a telecommunication company views of knowledge management. For this purpose, attention is paid to the following areas, namely knowledge management, implementation methodologies of knowledge management, process analysis and process optimization. The theoretical part deals mainly with the link between knowledge management and ways of managing organizations, it presents a theoretical framework necessary for the practical part of the work, which is based on implementation of monitoring system using selected methodology in an environment of selected organization.

This Diploma thesis focuses on the alignment of regulatory processes to support corporate performance management in the selected retail company. The main objective is the preparation of process maps that serve as a basis for the implementation of a global standard for automatic exchange of financial account information, developed by the OECD, also called as Common Reporting Standard. Additionally, the partial objectives include analysis of existing forms of content-related processes, creating a methodological support to the created processes and the theoretical concepts of regulatory requirements. The theoretical part focuses on the introduction of concepts related to the corporate management performance and also on theory about specific regulatory regulation used. In the practical part is an analysis of the company through the Balanced Scorecard (BSC), followed by the actual design and process description. The main contribution of the Diploma thesis was to perform process optimization, along with some improvements during the creation of these processes. The company will use the outcomes in practice.

The thesis is concerned with application of Decision Support Systems and Business Intelligence as a tool for decision-making support into processes of operational risk management in insurance company to improve them and reach a higher corporate performance.The goal of the thesis is to analyze a theory for a support of a process improvement design with the mentioned reach and to develop a design of improved operational risk management processes in a particular insurance company. The mean to reach goals is through-out a literature and articles research regarding a process improvement, decision-making, models and technologies of DSS and BI, and risk management. The theoretical framework is then used as back-bone for implementation of a practical part of innovated processes design. The thesis offers the analysis of an area of risk management processes improvement via DSS and BI in an insurance company that has been researched relatively little, but whose principles can be used for improvement projects in different areas too. A department of operational risk management in a certain insurance company obtains a complete design of innovated processes including DSS / BI application support specification which respects modern techniques of process improvements involving specific methods of decision-making quality. For the same department a part of the design was implemented -- Knowledge management system, that can be fully used. Introductory part of the thesis is concerned with techniques of business process improvement and its alignment with corporate performance. The next chapter describes specifics of operational risk management processes. In the third one models, techniques, information technologies of Decision Support Systems and Business Intelligence disciplines are analyzed. The practical part of the text starts with strategic analysis of the insurance company, proceeds with operational risk management processes analysis and reaches the design of innovated processes involving DSS and BI application support. Benefits of designed processes' changes are verified. In the conclusion a certain process change is accepted for the implementation and its results are described.

The master thesis deals with optimization of business processes in a food company. For this purpose the attention is paid to the three areas, namely process analysis, implementation of activity based costing model and business process optimization. The theoretical part describes the linkage between process analysis and activity based costing and acts as theoretical framework for practical part of the thesis. Presented cost model is implemented in existing company and information provided by model is used for business process optimization.

The aim of the thesis is to design and implement a simulator of image reconstruction during x-ray computed tomography fluoroscopy. Apart from quantitative evaluation of particular imaging process parameters influence, the intended program application will lie in optimization of these parameter values. Introductory part is focused on brief theoretical description of x-ray computed tomography imaging process. Emphasis is placed on fluoroscopy-specific approaches, particularly the division of scanned projections into chosen amount of sectors as well as fluoroscopic imaging process evaluation methods. The subsequent part deals with program implementation and its limitations and sketches the possible working framework. Moreover, one of the chapters is devoted to optimization of imaging process parameters measurement. The final part aims at impact analysis of particular process parameters as well as fluoroscopic imaging process optimization approaches. The thesis consists also of a didactic simulator enabling real-time intervention simulation with manual instrument manipulation. Since both simulators are intended for teaching purposes, the thesis is supplemented with a laboratory exercise draft.

The diploma thesis is devoted to the process analysis of realization educational programs and their optimization. The theoretical section is focused on educational programs, educational policy EU concept, process questions and connected notions. The analytical part researches implementation processes of educational programs, international activities analysis of Faculty of business, bilateral contracts and questionnaire survey. Knowledge of the analytical part is used in the proposal part, where results of the research are evaluated and drawn up procedures to improve processes. Proposals and disposals leading to increasing student´s participation and process optimization were compiled on the basis of gained information about Faculty of business and they respect educational concept of European Union.