Zugl.: Leipzig, Univ., Diss., 2008

Published also as Thesis (Ph. D.)--Columbia University, 1922. / "Columbia university contributions to philosophy and psychology." Bibliography: p. 92-93.

Thesis (Ph.D.) - University of Queensland, 2004. / Includes bibliography.

Thesis (M.S.)--Rochester Institute of Technology, 2007. / Typescript. Includes bibliographical references (p. 47-50).

Thesis (MScEng)--University of Stellenbosch, 2002. / ENGLISH ABSTRACT: Metallurgical processes are often high dimensional and non-linear making them difficult to understand, model and control. Whereas the human eye has extensively been used in discerning temporal patterns in historical process data from these processes, the systematic study of such data has only recently come to the forefront. This resulted predominantly from the inadequacy of previously used linear techniques and the computational power required when analysing the non-linear dynamics underlying these systems. Furthermore, owing to the recent progress made with regard to the identification of non-linear systems and the increased availability of computational power, the application of non-linear modelling techniques for the development of neural network models to be used in advanced control systems has become a potential alternative to operator experience. The objective of this study was the development ofa non-linear, dynamic model of an autogenous mill for use in an advanced control system. This was accomplished through system identification, modelling and prediction, and application to control. For system identification, the attractor was reconstructed based on Taken's theorem making use of both the Method Of Delays and singular spectrum analysis. Modelling consisted of the development of multi-layer perceptron neural network, radial basis function neural network, and support vector machine models for the prediction of the power drawn by an autogenous mill. The best model was subsequently selected and validated through its application to control. This was accomplished by means of developing a neurocontroller, which was tested under simulation. Initial inspection of the process data to be modelled indicated that it contained a considerable amount noise. However, using the method of surrogate data, it was found that the time series representing the power drawn by the autogenous mill clearly exhibited deterministic character, making it suitable for predictive modelling. It was subsequently found that, when using the data for attractor reconstruction, a connection existed between the embedding strategy used, the quality of the reconstructed attractor, and the quality of the resulting model. Owing to the high degree of noise in the data it was found that the singular spectrum analysis embeddings resulted in better quality reconstructed attractors that covered a larger part of the state space when compared to the method of delays embeddings; the data embedded using singular spectrum analysis also resulting in the development of better quality models. From a modelling perspective it was found that the multi-layer perceptron neural network models generally performed the best; a multi-layer perceptron neural network model having an appropriately embedded multi-dimensional input space outperforming all the other developed models with regard to free-run prediction success. However, none of the non-linear models performed significantly better than the ARX model with regard to one-step prediction results (based on the R2 statistic); the one-step predictions having a prediction interval of 30 seconds. In general the best model was a multi-layer perceptron neural network model having an input space consisting of the FAG mill power (XI), the FAG mill load (X2), the FAG mill coarse ore feed rate (X3), the FAG mill fine ore feed rate (X4), the FAG mill inlet water flow rate (X7) and the FAG mill discharge flow rates (X9, XIO). Since the accuracy of any neural network model is highly dependent on its training data, a process model diagnostic system was developed to accompany the process model. Linear principal component analysis was used for this purposes and the resulting diagnostic system was successfully used for data validation. One of the models developed during this research was also successfully used for the development of a neurocontroller, proving its possible use in an advanced control system. / AFRIKAANSE OPSOMMING: Metallurgiese prosesse is gewoonlik hoogs dimensioneel en nie-lineêr, wat dit moeilik maak om te verstaan, modelleer, en te beheer. Alhoewel die menslike oog alreeds wyd gebruik word om temporale patrone in historiese proses data te onderskei, het die sistematiese studie van hierdie tipe data eers onlangs na vore gekom. Dit is hoofsaaklik na aanleiding van die onvoldoende resultate wat verkry is deur van voorafgaande lineêre tegnieke gebruik te maak, asook die beperkende berekenings vermoë wat beskikbaar was vir analise van onderliggend nie-lineêre dinamiese stelsels. 'n Verder bydraende faktor is die onlangse vordering wat gemaak is met betrekking tot die identifikasie van nie-lineêre stelsels en die toename in beskikbaarheid van rekenaar-vermoë. Die toepassing van nie-lineêre modellerings tegnieke vir die ontwikkeling van neurale netwerke om gebruik te word in gevorderde beheerstelsels, het 'n potensiële alternatief geword tot operateur ondervinding. Die doelwit van hierdie studie was die ontwikkeling van 'n gevorderde beheerstelsel vir 'n outogene meul gebaseer op 'n nie-lineêre, dinamiese model. Dit is bereik deur middel van stelsel-identifikasie, modellering en voorspelling, en laastens implementering van die beheerstelsel. Vir stelsel-identifikasie is die attraktor van die stelsel bepaal soos gebaseer op Taken se teorema deur gebruik te maak van beide die metode van vertraging en enkelvoudige spektrum analise. Modellering van die stelsel vir die voorspelling van krag-verbruik deur die outogene meul het bestaan uit die ontwikkeling van multilaag-perseptron-neurale netwerke, radiaalbasisfunksie-neurale netwerke, en steunvektor-masjien-modelle. Die beste model is daarna gekies vir validasie deur middel van toepassing vir beheer. Dit is bereik deur 'n neurobeheerder te ontwikkel en te toets deur middel van simulasie. Die aanvanklike inspeksie van proses data wat gebruik sou word vir modellering het egter getoon dat die data 'n aansienlike hoeveelheid geraas bevat. Nietemin, deur die gebruik van 'n surrogaat-data-metode, is dit bevind dat die tyd-reeks wat die krag verbruik van die outogene meul beskryf, duidelik deterministiese karakter toon en dat dit dus wenslik is om 'n nie-lineêre voorspellings-model, soos 'n neurale netwerk te gruik. Gevolglik is gevind dat, wanneer die data vir attraktor hersamestelling gebruik word, 'n verband bestaan tussen die ontvouing-strategie wat gebruik word, die kwaliteit van die gerekonstrueerde attraktor, en die kwaliteit van die daaropvolgende model. As gevolg van die geraas in die data is gevind dat die ontvouing gebaseer op enkelvoudige spektrum analise 'n beter kwaliteit attraktor hersamestelling lewer. So ook is gevind dat 'n groter deel van die toestandruimte gedek word in vergelyking met die metode van vertraging-ontvouing. Deur gebruik te maak van enkelvoudige spektrum-analise, het die dataontvouing ook beter kwaliteit modelle opgelewer. Vanuit 'n modellerings-perspektief is gevind dat die multilaag-perseptron-neurale netwerk-modelle in die algemeen die beste gevaar het. 'n Multilaag-perseptronneurale netwerk met 'n gepaste ontvoude multidimensionele invoer-spasie het die beste gevaar van al die ontwikkelde modelle met betrekking tot vryloopvoorspellings. Geen van die nie-lineêre modelle het egter beduidend (op 'n R2 basis) beter gevaar as die ARX model wanneer daar na die eenstap-voorspellings (oor 'n 30 sekonde interval) gekyk word nie. Die multilaag-perseptron-neurale netwerk met 'n invoer-spasie bestaande uit die meul krag-verbruik (XI), die meullading (X2), die meul growwe-erts voertempo (X3), die meul fyn-erts voertemp ('4), die meul inlaat-water vloeitempo (X7) en die meul uitlaat vloeitempo's (X9, XIO) het in die algemeen die beste gevaar. Aangesien die akkuraatheid van emge neurale netwerk afhanklik is van die data waarmee dit aanvanklik opgestel is, is 'n diagnostiese proses modelontwikkel om die proses-model te vergesel. Lineêre hoofkomponent analise is vir hierdie doel aangewend en die gevolglike diagnostiese stelsel is suksesvol aangewend vir datavalidasie. Een van die modelle ontwikkel gedurende hierdie navorsing is ook suksesvol gebruik vir die ontwikkeling van 'n neurobeheerder wat dien as bewys dat die model goed gebruik kan word in 'n gevorderde beheerstelsel.

The basis of lean manufacturing is to minimize the inventories to reveal the disfunctions of the production system and to optimize process to avoid every kind of wastes. Lean systems are characteristic with smooth pull production system with one piece flow and just in time supplements of inventories. The layout of the line is transformed to the U work cell and the material is ordered by using kanban tickets. To receive the potential of implementation of the lean manufacturing principles we can use indicators IE - industrial efficiency and PLT - pruduction lead time.

Orientador: Ademir Jose Petenate / Dissertação (mestrado profissional) - Universidade Estadual de Campinas, Faculdade de Engenharia Mecanica / Made available in DSpace on 2018-08-05T21:53:14Z (GMT). No. of bitstreams: 1 Krahembuhl_CarlosEduardoZoppi_M.pdf: 9607428 bytes, checksum: dd179dbe75dda87476281150130dda7d (MD5) Previous issue date: 2005 / Resumo: As organizações necessitam constantemente se aprimorar e reduzir custos devido a percepção do cliente quanto ao valor que ele realmente está disposto a pagar por um produto. Dentre os diversos métodos de melhoria contínua, o DMAIC (sigla em inglês de Define, Measure, Analyse, Improve e Control) vem ganhando adeptos devido aos casos de sucesso apresentados por empresas como General Eletric e ABB. Este trabalho tem por objetivo avaliar as dificuldades e facilidades na aplicação do DMAIC sendo proposto um método de avaliação para implantação de cada uma de suas fases. O estudo de caso apresenta o bom resultado na redução de inventário em uma empresa de autopeças que desconhecia o método. O nível de inventário é um bom indicador de eficiência das empresas por estar relacionado com o desempenho da produção (programação, fluxo de processo, rejeição), manutenção de máquinas e qualidade de fornecedores. Os resultados financeiros obtidos foram considerados satisfatórios pela empresa apesar do tempo gasto na conclusão do trabalho. A estruturação lógica das fases do DMAIC compensa a dificuldade da aplicação de algumas de suas ferramentas, mas os fatores liderança e motivação da equipe, além da participação do patrocinador foram considerados essenciais para o sucesso de um proj eto de melhoria / Abstract: Now a days companies need to improve your process and reduce costs because the customers know how much they want to pay for a product. Among some improvement methods, DMAIC (Define, Measure, Analyse, Improve and Control) has wide recognition because good results shown by General Eletric and Motorola. The objective of this work is to evaluate the difficulty and facility for each phase of DMAIC. This case study shows the inventory reduction in a automaker parts that didn't know DMAIC method. The inventory leveI is a good metric because it's related with production performance (schedule, process flow, scrap), machine maintenance and quality suppliers. The financial results were good to the company although project time expended. The logic phases structure of DMAIC is balance the difficulty to apply some tools, but, team leadership, team motivation and champion participation are to critical to improvement project success / Mestrado / Gestão da Qualidade Total / Mestre em Engenharia Mecânica

Orientadores: Geraldo Nonato Telles, Oduvaldo Vendrameto / Dissertação (mestrado) - Universidade Estadual de Campinas. Faculdade de Engenharia Mecanica / Made available in DSpace on 2018-07-23T15:22:19Z (GMT). No. of bitstreams: 1 Monteiro_Rogerio_M.pdf: 7869079 bytes, checksum: 8e6bc72c41b2bb890b0e774a01f368e7 (MD5) Previous issue date: 1998 / Resumo: O crescente avanço tecnológico condicionou as empresas utilizarem recursos cada vez mais elaborados e as fábricas foram integradas em redes de computadores, aumentando em muito a velocidade do fluxo de informações sobre o sistema produtivo. A fábrica ganhou, portanto, um perfil orgânico, integrado e bastante flexível,com capacidade de produzir elevada variedade de produtos mesmo em pequenas quantidades, ou seja, a fábrica tomou-se um exemplo de agilidade e versatilidade. No entanto, observa-se também um rápido e acentuado aumento da concorrência, com a empresa passando a competir em um mercado globalizado em que pequenas vantagens competitivas são fundamentais para garantir seu futuro no mercado em que atua. Esta concorrência acirrada juntamente com o ambiente em constantes mudanças forçam os empresários a buscarem o máximo de informações a respeito do processo e da organização como um todo. É neste sentido que aumenta o interesse, tanto na indústria quanto na área acadêmica, por indicadores capazes de refletir o nível de organização das empresas, o grau de automação das atividades, bem como os níveis de flexibilidade dos sistemas de manufatura. O presente estudo apresenta dez diferentes métodos de indicadores de desempenho e flexibilidade e compara suas características e aplicabilidade no ambiente real, como por exemplo, na análise do fluxo de materiais em uma célula de manufatura, no gerenciamento do chão de fábrica ou na administração geral de empresas, segundo a concepção específica para a qual foi criado. Serão abordados itens como fator característico do processo e teoria da medição da flexibilidade,contando com suporte bibliográfico, além de um estudo de caso em empresas da região de Campinas / Abstract: The growing technological progressoconditioned the companies to use resources more and more elaborated. The factories have been integrated in nets of computers, increasing drastically the speed of the flow of information on the productive system. Therefore, factories has delivered an organic, integrated and quite flexible profile, with capacity of producing high variety of products even in small quantities, that is to say, factory became example of agility and versatility. However, it is also observed a fast and accentuated increase of the in a global market environrnent. Small competitive advantages are now fundamental to guarantee companies' future in the market place. This fiery competition together with constant changes have forced the managers to seek for obtaining maximum information of the process and the organization as a whole. In this sense, there is a growly interest, either industrial or academic in developing indicators capable of reflecting the stage of company organization, the degree of automation as well as the leveI of flexibilityof the manufacturing systems. The present study presents ten methods of automation indicators and compare their ability and application in case studies tfee the real environrnent,in the analysisof the flow of materials in a manufacturing cell, in the management of the shop floor or in the general administration of companies, according to the specific conception for which was created. Furthense, characteristic factor of the process and the theory of the flexibility assessment will be approached, supported by references in addition to a case study / Mestrado / Materiais e Processos de Fabricação / Mestre em Engenharia Mecânica

This research addresses the application of Value Stream Mapping in the automotive component industry. The goal of this research is to investigate how Value Stream Mapping can identify waste, and to evaluate its benefits on a specific application instance. Value Stream Mapping is used to first map the current state and then used to identify sources of waste and to identify lean tools to try eliminate this waste. The future state map is then developed with lean tools applied to it. A South African company, Federal Mogul South Africa (FMSA), has experienced the impact of globalisation and the need to become globally competitive first hand. FMSA will be used as a case study to illustrate the impact of using Value Stream Mapping as a tool for identify waste and the need for improving the performance of a company’s value stream in achieving the international goals set for the company and its supply chain.

M.Comm. / Please refer to full text to view abstract