Ser eficiente é um requisito para a sustentabilidade das empresas concessionárias de distribuição de energia elétrica no Brasil. A busca pela eficiência deve estar em harmonia com a melhoria contínua da qualidade, da segurança e da satisfação dos consumidores e das partes envolvidas. O desafio de atender múltiplos objetivos requer que as empresas do setor desenvolvam soluções inovadoras, com a mudança de processos, tecnologia, estrutura e a capacitação das pessoas. Desenvolver um modelo operacional eficiente e uma gestão rigorosa dos custos são fatores-chave para o sucesso das empresas, considerando o contexto regulatório de revisão tarifária que incentiva a melhoria do desempenho. O modelo operacional é definido a partir da organização logística dos recursos para atendimento da demanda de serviços, que define também os custos fixos e variáveis de pessoal (salário, horas extras, refeições), infraestrutura (manutenção de prédios, ferramentas e equipamentos) e deslocamentos (manutenção de veículos, combustível), por exemplo. A melhor alocação e o melhor dimensionamento de bases operacionais possibilitam a redução dos custos com deslocamento e infraestrutura, favorecendo o aproveitamento da força de trabalho em campo, a melhoria do atendimento dos clientes e da segurança dos colaboradores. Este trabalho apresenta uma metodologia de otimização de custos através da alocação de bases e equipes operacionais, com o modelamento matemático dos objetivos e restrições do negócio e a aplicação de algoritmo evolutivo para busca das melhores soluções, sendo uma aplicação de Pesquisa Operacional, no campo da Localização de Instalações, em distribuição de energia elétrica. O modelo de otimização desenvolvido possibilita a busca pelo ponto de equilíbrio ótimo que minimiza o custo total formado pelos custos de infraestrutura, frota (veículos e deslocamentos) e pessoal. O algoritmo evolutivo aplicado no modelo oferece soluções otimizadas pelo melhoramento de conjuntos de variáveis binárias com base em conceitos da evolução genética. O modelo de otimização fornece o detalhamento de toda a estrutura operacional e de custos para uma determinada solução do problema, utilizando premissas de produtividade e deslocamentos (velocidades e distâncias) para definir as abrangências de atuação das bases operacionais, recursos (equipes, pessoas, veículos) necessários para atendimento da demanda de serviços, e projetar todos os custos fixos e variáveis associados. A metodologia desenvolvida neste trabalho considera também a projeção de demanda futura para a aplicação no estudo de caso, que evidenciou a efetividade da metodologia como ferramenta para a melhoria da eficiência operacional em empresas de distribuição de energia elétrica. / Being efficient is a requirement for the sustainability of electricity distribution companies in Brazil. The quest for efficiency must be in harmony with the continuous improvement of quality, safety and satisfaction of customers and all stakeholders involved. The challenge of attending multi-objectives requires companies in the sector to develop innovative solutions with the change of processes, technology, structure and enabling their professionals to drive this. Developing an efficient operational model and a strict cost management are keys for companies to achieve success, considering the regulatory context of tariff reviewing that encourages performance improvement. The operational model is defined from the logistics organization of resources to meet the demand of services, which also defines fixed and variable costs with people/teams (payments, overtime, meals), infrastructure (maintenance of building, tools and equipments) and fleet (maintenance of vehicles and fuel costs), for example. The best allocation and the best design of operational facilities (or operational bases) will reduce infrastructure costs and truck rolls, releasing workforce to attend customers and reducing displacements risks. This work presents a cost optimization methodology through the allocation of operational bases and teams, with the mathematical modelling of business objectives, constraints and using Evolutionary Algorithm to find the best solution, as an application of Operations Research in the field of Facility Location in electricity distribution. The optimization model enables the search for the optimal balance point that minimizes the total cost formed by infrastructure, fleet and people. The Evolutionary Algorithm applied in the model offers optimized solutions through the improvement of sets of binary variables based on genetic evolution concepts. The optimization model also gives detailed information about the operational structure and costs for a given allocation solution, using productivity and displacements (speed, distances) information to define the service regions for each operational base and resources (people, vehicles) needed to attend the demand of services, defining all fixed and variable costs for this. The methodology presented in this paper also considers the future demand of services (forecast), used in a case study that showed the effectives of this methodology as a tool for the improvement of operational efficiency in electricity distribution companies.

Cette thèse étudie des systèmes locaux de gestion de transfert de pétrole ayant une architecture de réseau de canalisation. Pour leur représentativité, deux systèmes localisés au Venezuela et appartenant à l'entreprise PDVSA (Pétroles du Venezuela) ont été retenus pour illustrer les méthodes proposées et les valider : le Terminal Maritime de Pétrole de Guaraguao et le Centre de Stockage de Punta de Palmas. Dans ces réseaux des connexions, appelées « alignements », sont établies en ouvrant/fermant des vannes à travers d'un système SCADA (Supervisory Control and Data Acquisition). Le choix d'un alignement doit tenir compte de critères d'optimisation. La minimisation des interférences avec d'autres alignements, liée à la notion de capacité opérative, a été identifiée comme le critère de choix le plus important. Les contributions de cette thèse reposent sur une modélisation sous forme de graphes, et sur des algorithmes appartenant au domaine de la recherche opérationnelle. Elles contribuent à fournir aux opérateurs de supervision des outils d'analyse permettant d'optimiser le choix des alignements. Des indicateurs permettant de quantifier l'impact des opérations d'alignement ou des défaillances, sur la capacité opérative du système, sont proposés. La minimisation de l'impact sur la capacité opérative, va correspondre à la minimisation des interférences avec des alignements potentiels. Un algorithme de calcul de ces indicateurs, est présenté, ainsi que des algorithmes de recherche de chemin, de détermination d'éléments critiques, et de recherche d'alignements utilisant des pompes. Ces algorithmes sont basés sur des algorithmes classiques s'adressant au problème du plus court chemin, du flot maximum et du nombre maximum de chemins disjoints. Cependant, ils utilisent des méthodes innovantes, comme l'ajout de contraintes considérant l'existence de sous-types d'alignements, le calcul dynamique des coûts des chemins à partir de son impact sur la capacité opérative, et la recherche de chemins via un point intermédiaire obligatoire. Les contributions sont potentiellement applicables dans des domaines autres que le transport de pétrole. Les algorithmes ont été mis en œuvre en utilisant le langage Python et ont été testés en utilisant les données réelles des réseaux étudiés. L'objectif à moyen terme de ces travaux est le développement d'un logiciel d'assistance à la prise de décision. / This thesis studies local crude oil transportation systems with a pipe network architecture. Two representative systems, belonging to PDVSA (Venezuelan oil company), have been studied: the Guaraguao Crude Oil Seaport and the Punta de Palmas Tanks Yard. In this systems, connections, called "alignments", are established by opening/closing valves using a SCADA(Supervisory Control and Data Acquisition) system. Alignment choice is made based on optimization criteria. Interferences minimization with other alignments, related to the notion of operative capacity, has been identified as the most important criterion. The contributions of this thesis are based on graph modelling and algorithms from operational research. The main goal is to provide analysis tools allowing alignment choice optimization. Indexes permitting the quantification of alignments or failures impact on the operative capacity of the system are proposed. Minimizing the impact on the operative capacity will correspond to minimizing interferences with potential alignments. An algorithm computing these indexes is presented, as well as complementary developments such as a path search algorithm, an algorithm for critical elements determination, and algorithm for alignments using pumps. These algorithms are based on classical algorithms for the shortest path problem, the maximum flow problem and the maximum disjoint paths problem. However, they use innovative methods such as adding constraints when considering alignment sub-types, the dynamic computation of path costs based on their impact on operative capacity, and path search considering an obligatory intermediate node. These contributions can potentially be applied in areas other than oil transportation. The algorithms had been implemented in Python and had been tested using real data from the studied systems. The middle term goal of these works is the development of assistance software for decision making.

Ser eficiente é um requisito para a sustentabilidade das empresas concessionárias de distribuição de energia elétrica no Brasil. A busca pela eficiência deve estar em harmonia com a melhoria contínua da qualidade, da segurança e da satisfação dos consumidores e das partes envolvidas. O desafio de atender múltiplos objetivos requer que as empresas do setor desenvolvam soluções inovadoras, com a mudança de processos, tecnologia, estrutura e a capacitação das pessoas. Desenvolver um modelo operacional eficiente e uma gestão rigorosa dos custos são fatores-chave para o sucesso das empresas, considerando o contexto regulatório de revisão tarifária que incentiva a melhoria do desempenho. O modelo operacional é definido a partir da organização logística dos recursos para atendimento da demanda de serviços, que define também os custos fixos e variáveis de pessoal (salário, horas extras, refeições), infraestrutura (manutenção de prédios, ferramentas e equipamentos) e deslocamentos (manutenção de veículos, combustível), por exemplo. A melhor alocação e o melhor dimensionamento de bases operacionais possibilitam a redução dos custos com deslocamento e infraestrutura, favorecendo o aproveitamento da força de trabalho em campo, a melhoria do atendimento dos clientes e da segurança dos colaboradores. Este trabalho apresenta uma metodologia de otimização de custos através da alocação de bases e equipes operacionais, com o modelamento matemático dos objetivos e restrições do negócio e a aplicação de algoritmo evolutivo para busca das melhores soluções, sendo uma aplicação de Pesquisa Operacional, no campo da Localização de Instalações, em distribuição de energia elétrica. O modelo de otimização desenvolvido possibilita a busca pelo ponto de equilíbrio ótimo que minimiza o custo total formado pelos custos de infraestrutura, frota (veículos e deslocamentos) e pessoal. O algoritmo evolutivo aplicado no modelo oferece soluções otimizadas pelo melhoramento de conjuntos de variáveis binárias com base em conceitos da evolução genética. O modelo de otimização fornece o detalhamento de toda a estrutura operacional e de custos para uma determinada solução do problema, utilizando premissas de produtividade e deslocamentos (velocidades e distâncias) para definir as abrangências de atuação das bases operacionais, recursos (equipes, pessoas, veículos) necessários para atendimento da demanda de serviços, e projetar todos os custos fixos e variáveis associados. A metodologia desenvolvida neste trabalho considera também a projeção de demanda futura para a aplicação no estudo de caso, que evidenciou a efetividade da metodologia como ferramenta para a melhoria da eficiência operacional em empresas de distribuição de energia elétrica. / Being efficient is a requirement for the sustainability of electricity distribution companies in Brazil. The quest for efficiency must be in harmony with the continuous improvement of quality, safety and satisfaction of customers and all stakeholders involved. The challenge of attending multi-objectives requires companies in the sector to develop innovative solutions with the change of processes, technology, structure and enabling their professionals to drive this. Developing an efficient operational model and a strict cost management are keys for companies to achieve success, considering the regulatory context of tariff reviewing that encourages performance improvement. The operational model is defined from the logistics organization of resources to meet the demand of services, which also defines fixed and variable costs with people/teams (payments, overtime, meals), infrastructure (maintenance of building, tools and equipments) and fleet (maintenance of vehicles and fuel costs), for example. The best allocation and the best design of operational facilities (or operational bases) will reduce infrastructure costs and truck rolls, releasing workforce to attend customers and reducing displacements risks. This work presents a cost optimization methodology through the allocation of operational bases and teams, with the mathematical modelling of business objectives, constraints and using Evolutionary Algorithm to find the best solution, as an application of Operations Research in the field of Facility Location in electricity distribution. The optimization model enables the search for the optimal balance point that minimizes the total cost formed by infrastructure, fleet and people. The Evolutionary Algorithm applied in the model offers optimized solutions through the improvement of sets of binary variables based on genetic evolution concepts. The optimization model also gives detailed information about the operational structure and costs for a given allocation solution, using productivity and displacements (speed, distances) information to define the service regions for each operational base and resources (people, vehicles) needed to attend the demand of services, defining all fixed and variable costs for this. The methodology presented in this paper also considers the future demand of services (forecast), used in a case study that showed the effectives of this methodology as a tool for the improvement of operational efficiency in electricity distribution companies.

A roller coaster manufacturer became aware that improperly heat treated track couplings were sent to a construction site for assembly. Concerns were that suspect couplings might not meet the engineering specifications and could be vulnerable to sudden failure. A testing company in Oak Ridge, TN that specializes in in-situ and laboratory mechanical testing was contacted by the manufacturer for help in this endeavor. The construction company elected to enlist a local testing firm to perform field tests on the components instead of the company in Oak Ridge. The test methods used are incapable of providing quantitative results that could be measured to the engineering specifications, making it unlikely to identify anything but the worst material conditions. This study is an example that the need for accurate analysis is very important. The manufacturer reported that 60 couplings were replaced, but it is presently unknown how many should have been replaced.

The purpose of this research is to implement and analyze the true lean transformation in a manufacturing start-up organization. Often, lean transformations are observed in developed manufacturing organizations having sophisticated production lines and numerous employees, where lean tools are utilized to reduce waste while increasing profit. However, this type of transformation is narrowly focused on quantifiable process results and falls short of the ultimate goal, establishing a true lean culture within the organization. As a result, it is recommended that true lean principles, philosophies, culture, operations environment and tools be applied at the very beginning stages of an organization, or during the start-up phase to embed true lean thinking and application in the entirety of the organization. In this analysis, a case study is performed on a team embarking on a start-up manufacturing enterprise. The team is trained on true lean and all the four aspects of true lean are applied for successfully implementing true lean in the start-up. In addition, a true lean implementation approach was generated and applied using PDCA (plan, do, check and act) model. The results of this case study are presented in this work.

Poor input data quality used in repairable spare parts forecasting by aerospace small and midsize enterprises (SME) suppliers results in poor inventory practices that manifest into higher costs and critical supply shortage risks. Guided by the data quality management (DQM) theory as the conceptual framework, the purpose of this exploratory multiple case study was to identify the key strategies that the aerospace SME repairable spares suppliers use to maximize their input data quality used in forecasting repairable spare parts. The multiple case study comprised of a census sample of 6 forecasting business leaders from aerospace SME repairable spares suppliers located in the states of Florida and Kansas. The sample was collected via semistructured interviews and supporting documentation from the consenting participants and organizational websites. Eight core themes emanated from the application of the content data analysis process coupled with methodological triangulation. These themes were labeled as establish data governance, identify quality forecast input data sources, develop a sustainable relationship and collaboration with customers and vendors, utilize a strategic data quality system, conduct continuous input data quality analysis, identify input data quality measures, incorporate continuous improvement initiatives, and engage in data quality training and education. Of the 8 core themes, 6 aligned to the DQM theory's conceptual constructs while 2 surfaced as outliers. The key implication of the research toward positive social change may include the increased situational awareness for SME forecasting business leaders to focus on enhancing business practices for input data quality to forecast repairable spare parts to attain sustainable profits.

Efficient management of natural resources (NRM) needs to be built on a correct understanding of the objectives of different stakeholders. Therefore, it is required to actively involve experts and stakeholders in the decision making process. However, the introduction of these knowledge claims is controversial. This is due to differences in the quality of the underlying involvement methods. The principle objective of this study was therefore to develop, apply and critically analyse improved (hybrid) methodologies to integrate expert and local knowledge in existing NRM decision making frameworks. Research is performed on 2 case studies. The SAFE case study deals with the development of a framework for evaluating sustainability levels in agricultural systems in Belgium, while the ALERT case study deals with sustainable management of water resources in semi-arid regions, applied to the Andarax catchment in Spain. The analysis of pro's and contra's of both the technocratic and the pure participatory approaches sets the blueprint for a hybrid decision making framework. Experience shows that decision support is improved when an indicator-based assessment structure is embedded in the participatory approach. This is facilitated through the use of soft operational research techniques. A sound methodology for participatory indicator selection is presented and clear-cut answers to problems with reliability of judgments are provided. The design of different typologies of membership functions is an important step to future deliberation of participatory-based norms. A computerized decision support system (DSS) is developed as it proves to be an important means to deal with increased information and complexity in decision support for NRM. In response to calls for greater collaboration with local actors, the DSS contains different functionalities that are designed to be interactive, while optimal default values ensure basic quality standards. Multi-criteria analysis allows an evaluation of alternatives and scenarios in the hybrid decision making framework. We deal with important choices that have to be made when interpreting spatio-temporal variabilities in management performances and the implications thereof on the final projections towards decision makers. The propagation of uncertainty in the hybrid decision making frameworks is critically evaluated. In order to consider uncertainty in an integrated way, a combined uncertainty/sensitivity analysis is presented. This analysis includes uncertainty related to norms, weights and indicators. Finally, guidelines for communication of the findings towards decision makers are drafted. / Pour être efficace, la gestion des ressources naturelles (GRN) doit prendre en compte correctement les objectifs de différents acteurs. Il est dès lors recommandé d’inclure activement les experts et les parties prenantes dans le processus de prise de décision. Cependant, la meilleure manière de prendre en compte différents types de savoir est sujette à controverse. L’objectif principal de cette étude est donc de développer, appliquer et évaluer des méthodes améliorées (hybrides) de prise en compte du savoir des parties prenantes et des experts dans les systèmes actuels de prise de décision pour la GRN. Cette recherche a été appliquée sur deux cas d’étude. Le premier, appelé SAFE, traite du développement d’un cadre pour évaluer la durabilité des systèmes agraires en Belgique. Le second, ALERT, traite de la gestion durable de l’eau dans des régions semi-arides, appliquée ici au bassin de l’Andarax (Espagne). L’analyse comparée des points forts et des points faibles des approches participatives et technocratiques fournit le cadre pour une approche hybride de prise de décision. Les expériences montrent que l’aide à la décision est améliorée lorsqu’une évaluation par des indicateurs est ancrée dans une approche participative. Des techniques de « recherche opérationnelle douce » permettent cette prise en compte. Nous présentons une méthode pour définir les indicateurs d’une façon participative qui permet de donner des réponses claires aux problèmes liés à la fiabilité des jugements. La définition d’une typologie de fonctions d’appartenance spécifique pour les indicateurs est une étape importante pour le choix participatif des normes. Un système informatisé d'aide à la décision (SIAD) a été développé afin de faire face à l’accroissement de la quantité d’information et de la complexité dans l'aide à la décision. En réponse à la demande d'une plus grande collaboration avec les acteurs locaux, le SIAD contient différentes fonctionnalités qui peuvent être configurées interactivement. Par default on propose des valeurs optimalisées pour assurer des standards de qualité. L'analyse multicritère permet une évaluation des alternatives de gestion et des scénarios dans le cadre de la prise de décision hybride. Nous traitons des choix importants à faire lors de l'interprétation des variations spatio-temporelles des performances de gestion et des implications de ceux-ci sur les avis finaux relayés aux décideurs. La propagation des incertitudes dans la prise de décision des cadres hybrides est aussi évaluée. Afin d'examiner l'incertitude d'une manière intégrée, une analyse mixte de sensibilité et d’incertitude est présentée. Celle-ci porte sur l’incertitude liée aux normes, aux poids et aux indicateurs. Afin de mener à une gestion efficace et durable des ressources naturelles, nous proposons des solutions techniques aux décideurs pour mieux valoriser la connaissance intrinsèque des acteurs de terrain et des gestionnaires.

Les travaux de cette thèse s’articulent autour des « problèmes d’ordonnancement multiagent avec une fonction objectif globale ». Ces modèles considèrent différents agents associés à des sous-ensembles de travaux disjoints, chacun d’eux vise à minimiser un objectif qui ne dépend que de ses propres travaux. Un critère global est aussi considéré, qui est appliqué à la totalité des travaux. La résolution de ces problèmes revient à trouver les meilleurs compromis entre les critères des agents et le critère global. Ces problèmes sont une classe particulière des problèmes d’ordonnancement « multi-agents » qui ont connu une grande expansion, reflétant leurs intérêts dans le domaine de l’ordonnancement. / This thesis addresses the multi-agent scheduling problems with a global objective function. We consider the problems featured by various agents, each of which is associated with a distinct subset of jobs. Each agent aims at minimizing a certain objective function, which only operates on its assigned jobs. A global criterion associated with a global agent is applied on the whole set of the jobs. Solving these problems involves finding the best compromises between the requirements of agents and that of the global agent. These problems belong to a particular class of multi-criteria scheduling problems. Such a class has drawn a significant interest to researchers in the area of scheduling and operational research.

Esta dissertação apresenta a aplicação de uma nova abordagem utilizando Algoritmo Genético na resolução do Problema de Corte Unidimensional na minimização de dois objetivos, geralmente conflitantes, o número de objetos processados e o setup, simultaneamente. O problema de corte consiste, basicamente, em encontrar a melhor maneira de obter peças de tamanhos distintos (itens) a partir do corte de peças maiores (objetos) com o objetivo de minimizar alguma espécie de custo ou maximizar o lucro. A disposição dos itens no objeto para a realização de cortes durante sua produção é denominada padrão de corte. E o setup é o tempo de preparação de máquina. O modelo do problema, a função objetivo e o método proposto denominado SingleGA, bem como os passos utilizados para sua resolução, também são apresentados. Os resultados obtidos pelo SingleGA são comparados com os métodos SHP, Kombi234, ANLCP300 e Symbio, encontrados na literatura, a fim de verificar a capacidade de encontrar soluções viáveis e competitivas. Os resultados computacionais mostram que o método proposto, o qual utiliza apenas um algoritmo genético para resolver esses dois objetivos inversamente relacionados, proporciona bons resultados.

Este trabalho tem como objetivo verificar se a adoção dos conceitos do BSC (Balanced Scorecard) na avaliação da gestão das unidades de negócio da Caixa Econômica Federal está contribuindo para que ocorra o alinhamento do pensamento estratégico nos diversos níveis gerenciais da organização. Com tal finalidade, foi realizada uma pesquisa junto a três grupos de profissionais com atuação na gestão das unidades de negócio da empresa na região da Superintendência Regional da Serra Gaúcha. Este trabalho apresenta o resultado da pesquisa que desenvolveu o instrumento de coleta de dados, seguindo o método de escalas multiitens. A escala foi construída a partir da realidade da organização selecionada como campo de estudo e, para tanto, fundamentou-se nos sete desafios estratégicos para o período 2005-2015. Após a revisão de literatura, a aplicação da pesquisa e a análise dos dados discutiram-se o alinhamento estratégico a partir da adoção do BSC, bem como a sua influência nos resultados da Caixa Econômica Federal. Verificou-se que, sob todos os aspectos analisados, a adoção do BSC está contribuindo para que ocorra o alinhamento do pensamento estratégico dos gestores da Caixa Econômica Federal que atuam em níveis hierárquicos e funcionais diferentes dentro da organização. Além disso, constatou-se que o resultado líquido da empresa estudada evolui acima da média dos seus maiores concorrentes. / Submitted by Marcelo Teixeira (mvteixeira@ucs.br) on 2014-05-19T18:02:14Z No. of bitstreams: 1 Dissertacao Edson Luiz Flores.pdf: 2534910 bytes, checksum: c96a1a39ab8877a4baa4c8daf56da3c1 (MD5) / Made available in DSpace on 2014-05-19T18:02:14Z (GMT). No. of bitstreams: 1 Dissertacao Edson Luiz Flores.pdf: 2534910 bytes, checksum: c96a1a39ab8877a4baa4c8daf56da3c1 (MD5) / This work has as its objective to verify if the adoption of the concepts of BSC (Balanced Scorecard) in the management evaluation of the business units of Caixa Econômica Federal is contributing to standardize the strategic thought in the several management levels of the organization. With such purpose, a research was carried out with three groups of professionals that act in the administration of the business units of the company, in the Superintendency Area of Serra Gaucha. The current work presents the research result that developed an instrument of data collection following the method of scales multiitens. The scale was built starting from the reality of the organization selected as study field and it was based in the seven strategic challenges for the period 2005-2015. After the literature revision, the application of the research and the data, the strategic standardization starting from the adoption of BSC is discussed, as well as its influence in the results of Caixa Econômica Federal. It was checked that, under all analyzed aspects, the adoption of BSC is contributing for the alignment of the bank strategic thought of the managers` of Caixa Econômica Federal that act in different hierarchical and functional levels inside the organization. Besides, it was checked that the net income of the studied company grows above the average of its largest competitors.