Essa dissertação tem como objetivo utilizar a simulação de eventos discretos na análise dos estoques seletivos em processo de cabinas, em uma montadora de veículos comerciais de grande porte instalada no Brasil. A análise e a redução desses estoques seletivos são desejadas, pois o armazenamento de cabinas de caminhões, além de representar um alto custo para a produção, é de difícil controle e de alto risco. O desenvolvimento deste trabalho contribuirá para o conhecimento das dificuldades e benefícios da aplicação da simulação de sistemas discretos em sistemas produtivos de alta complexidade, como são os sistemas de manufatura da indústria automobilística. A análise desse sistema é de significativa dificuldade, devido ao tamanho dos produtos, ao mix de produção, à variabilidade do fluxo das etapas de produção e às diversas variáveis que influem no sistema simultaneamente. A técnica de simulação de eventos discretos foi escolhida por ser a mais indicada para analisar todo o sistema e auxiliar na tomada de decisão. Todo o estudo do sistema, modelagem, verificação, validação, simulação e resultados foram feitos de acordo com procedimentos já sedimentados para o uso da simulação de eventos discretos, de acordo com a bibliografia apresentada. Os resultados mostram a eficiência do método utilizado e propõem um cenário otimizado para o sistema estudado. O estudo foi realizado com a utilização do software de simulação de eventos discretos, Arena® 5.0. / This work has the main objective to use the discrete event simulation to analyze the in process cabins selective banks of a commercial vehicle assembler. The analysis and reduction of the selective banks are useful because the storage of cabins represents some production risks, is hard to control and implies in high costs. The developing of this work will contribute to the knowledge of the difficulties and benefits of the use of discrete event simulation applied to high complexity production systems like the automotive industry. The size of the products, the production mix, the throughput variability and the other simultaneous variables turn the storage analysis to a hard level. In this way, the discrete event simulation is the most indicated technique to help the analysis and the decision making. The whole study of the system, the modeling, the validation, the simulation runs and the results were done according to known procedures of using the discrete event simulation, which are mentioned in the references. The presented results show the efficiency of the utilized method and proposed optimized scenery of the studied system. The simulation software Arena 5.0 was used in this study.

Modelos de simulação usados para representar uma malha ferroviária com a circulação de trens percorrendo nela um ciclo fechado, estão sujeitos a diversas interferências. Essas interferências são representadas pela circulação de outros trens, bem como pelas filas que são formadas junto aos terminas de carga e descarga, que alteram a programação inicialmente idealizada. A validação desses modelos de simulação é prejudicada por essas interferências, e a busca por um correto procedimento de validação deve ter como base o adequado direcionamento e alocação dos trens. A carência de estudos sobre a validação de simulações aplicadas a sistemas ferroviários, que considerem a característica especifica de trens de ciclo e as interferências citadas, possibilitou a elaboração desta tese, a qual sinaliza que o desenvolvimento de algoritmos que representam o processo de movimentação dos trens em nível de detalhe suficiente, e a adoção de um método de direcionamento adequado, permitem a validação do modelo para esse tipo de sistema. Das três alternativas avaliadas para representar o direcionamento: escolha aleatória entre diversos pontos de carregamento para atender um destino final ou realizado por rotina com a mesma finalidade inserida no próprio simulador, e por modelo otimizador acessado externamente pelo simulador, foi selecionada a segunda opção por permitir uma validação do modelo mais próxima da realidade e realizar experimentos com menor tempo computacional. Uma vez programado o modelo de simulação com o direcionamento de trens escolhido, foi possível conduzir experimentos para medir a sensibilidade com relação as principais variáveis que permitem o dimensionamento de sistemas ferroviários brasileiros. / The rail network simulation models considering trains on closed loop may have many disturbances. These disturbances are caused by the railnet traffic, or queues at the load/unload stations, that changes the movement previously planned. The validation of these simulation models can be problematic because of these disturbances, and the search for the right validation procedure must count with a good train destination choosing process. The lack of studies about the validation of simulations applied to rail networks, considering the specific features of the closed loop trains and the disturbances, have leaded this thesis development, which proves that the development of algorithms that represent the movement process of the trains under sufficient detailing level, and the adoption of a correct destination choosing process, reaches the model validation. From the three options evaluated to represent this destination choosing procedure: random choosing between many loading points to one unloading point, or an internal model routine to do this same task, or an external optimization model called from the simulation model, was choosen the second option, because it validates the model and runs the simulation experiment faster. Once prepared the model with the destination choosing process selected, was possible to conduct experiments to measure the model sensitivity to the main parameters at the design of brazilian rail networks.

Submitted by Mariana Dornelles Vargas (marianadv) on 2015-03-17T19:40:51Z No. of bitstreams: 1 metodo_quantificar.pdf: 1038017 bytes, checksum: 54f78fa2753a1dfe9d797dc88d1ed31e (MD5) / Made available in DSpace on 2015-03-17T19:40:51Z (GMT). No. of bitstreams: 1 metodo_quantificar.pdf: 1038017 bytes, checksum: 54f78fa2753a1dfe9d797dc88d1ed31e (MD5) Previous issue date: 2011-03-16 / CAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / PROSUP - Programa de Suporte à Pós-Gradução de Instituições de Ensino Particulares / Em ambientes produtivos intermitentes que operam na condição ?produzir para estoque?, com fluxo convergente, a possibilidade de constituir estoques em processo (WIP), de produtos prontos, ou matérias-primas pode aumentar o grau de complexidade da gestão das operações e a necessidade de utilizar procedimentos de controle distintos para cada tipo de estoque. Ao focar no alinhamento da gestão dos estoques aos planos de demanda e capacidade, considerando um ambiente produtivo que emprega a abordagem Conwip, a presente pesquisa tem por finalidade propor um método estruturado que possibilite quantificar o nível de WIP do sistema produtivo, a partir da Simulação por Eventos Discretos e da técnica de Apoio Multicritério ELECTRE TRI. Esta pesquisa tem o intuito de contribuir com a geração de informações que subsidiem a tomada de decisão concernente à escolha de uma configuração de cenário que aluda a um nível de estoque em processo e de produtos prontos considerando o mix de produção sob estudo. Fundamentado na proposta desenvolvida nesta dissertação, o Método de Pesquisa pode ser caracterizado quanto aos procedimentos técnicos, pelo uso da Simulação Computacional e relativo à natureza dos dados, destaca-se o da abordagem essencialmente quantitativa, ou Pesquisa Quantitativa. O método proposto foi avaliado, quanto a sua estrutura e proposta, por especialistas das disciplinas de Simulação, Gestão de Sistemas Produtivos e Métodos Multicritério à Decisão. Uma aplicação do método em um sistema produtivo real também é apresentada / In intermittent productive systems that operate in the condition 'make to stock' with convergent flow, the possibility of generate work in process (WIP), finish good products or raw materials inventories can increase the degree of complexity of the management in the operations and the need of using procedures of different control for each stock type. Focusing in the alignment of the stocks to the demand and capacity plans, considering a productive system which uses the Conwip approach, this research describes a structured method that aims to quantify the level of WIP in the productive system, applying the Events Discrete Simulation and the technique nominated ELECTRE TRI. This research intends to contribute with the generation of information for decision support regarding the choice of work in process and finished goods stock levels, considering the production mix studied. Based in the proposal developed in this work, the Method of Research can be characterized, regarding the technical procedures, as Computational Simulation, and regarding the nature of the data, as Quantitative Research. The method proposed in this research was evaluated for specialists in the disciplines of Simulation, Administration of Production Systems and Multicriteria Decision Analysis. An application of the method in a real productive system is also presented.

Current industrial companies are highly pressured by growing competitiveness and globalization, while striving for increased production effectiveness. Meanwhile, flustered markets and amplified customer demands are causing manufacturers to shift strategy. Hence, international companies are challenged to pursue changes, in order to continue being competitive on global markets. Consequently, a new industrial revolution has taken place, introduced as Industry 4.0. This new concept incorporates organizational improvement and digitalization of current information and data flows. Accomplished by data from embedded systems through connected machines, devices and humans into a combined interface. Thus, companies are given possibilities to improve current production systems, simultaneously saving operational costs and minimizing insufficient production development. Smart Factories, being the foundation of Industry 4.0 results in making more accurate and precise operational decisions from abilities to test industrial changes in a virtual world before real-life implementation. However, in order to assure these functions as intended, enormous amount of data must be collected, analysed and evaluated. The indicated data will aid companies to make more self-aware and automated decisions, resulting in increased effectiveness in production. Thus, the concept will clearly change how operational decisions are made today. Nowadays, Discrete Event Simulation is a commonly applied tool founded on specific data requirements as operational changes can be tested in virtual settings. Accordingly, it is believed that simulation can aid companies that are striving for implementing Industry 4.0. As a result, data requirements between Discrete Event Simulation and Industry 4.0 needs to be established, while detecting the current data gap in operational context. Hence, the purpose of this thesis is to analyse the data requirements of Discrete Event Simulation and Industry 4.0 for improving operational decisions of production systems. In order to justify the purpose, the following research questions has been stated:   RQ1: What are the data challenges in existing production systems? RQ2: What data is required for implementing Industry 4.0 in production systems? RQ3: How can data requirements from Discrete Event Simulation benefit operational decisions when implementing Industry 4.0?   The research questions were answered by conducting a case study, in collaboration with Scania CV AB. The case study performed observations, interviews and other relevant data collection to accomplish the purpose. In parallel, a literature review focusing on data requirements for operational decisions was compared to the empirical findings. The analysis identified the current data gap in existing production systems, in correlation to Industry 4.0, affecting the accuracy of operational decisions. In addition, it was shown that simulation can undoubtedly give positive outcome for adaptation of Industry 4.0, and a clear insight on data requirements.

This thesis participates to the effort launched after the Fukushima-Daiichi disaster to improve the robustness of national institutions involved in nuclear safety because of the role that the failing nuclear regulator had in the accident. The driving idea is to investigate how engineering techniques used in high-risk industries can be applied to institutions involved in nuclear safety to improve their robustness. The thesis focuses specifically on the Office for Nuclear Regulation (ONR), the British nuclear regulator, and its process for structured inspections. The first part of the thesis demonstrates that the hazard and operability (HAZOP) technique, used in the nuclear industry to identify hazards associated with an activity, can be adapted to qualitatively assess the robustness of organisational processes. The HAZOP method was applied to the ONR inspection process and led to the identification of five significant failures or errors. These are: failure to focus on an area/topic deserving regulatory attention; failure to evaluate an area/topic of interest; failure to identify a non-compliance; failure to identify the underlying issue, its full extent and/or safety significance and failure to adequately share inspection findings. In addition, the study identified the main causal chains leading to each failure. The safeguards of the process, i.e. the mechanisms in place to prevent, detect, resolve and mitigate possible failures, were then analysed to assess the robustness of the inspection process. The principal safeguard found is the superintending inspector who performs reviews of inspection reports and debriefs inspectors after inspections. It was concluded that the inspection process is robust provided recruitment and training excellence. However, given the predominant role of the superintending inspector, the robustness of the process could be improved by increasing the diversity of safeguards. Finally, suggestions for improvement were made such as establishing a formal handover procedure between former and new site inspectors, formalising and generalising the shadowing scheme between inspectors and setting minimum standards for inspection debriefs. These results were shared with ONR, which had reached the same conclusions independently, thus validating the new application for the HAZOP method. The second part of the thesis demonstrates that computational modelling techniques can be used to build digital twins of institutions involved in safety which can then be used to assess their effectiveness. The knowledge learned thanks to the HAZOP study was used in association with computational modelling techniques to build a digital twin of the ONR and its structural inspection process along with a simple model of a nuclear plant. The model was validated using the face-validity and predictive validation processes. They respectively involved an experienced ONR inspector checking the validity of the model’s procedures and decision-making processes and comparing the model’s output for oversight work done to data provided by the ONR. The effectiveness of the ONR was then evaluated using a scenario where a hypothetical, newly discovered phenomenon threatens the integrity of the plant, with ONR inspectors gradually learning and sharing new information about it. Monte-Carlo simulation was used to estimate the cost of regulatory oversight and the probability that the ONR model detects and resolves the issue introduced before it causes an accident. Different arrangements were tested and in particular with a superintending inspector reviewing inspection reports and a formal information sharing process. For this scenario, these two improvements were found to have a similar impact on the success probability. However, the former achieves it for only half the cost.

Submitted by Lucio Flore Maciel (floremaciel@gmail.com) on 2017-02-15T08:26:10Z No. of bitstreams: 1 Dissertação Lucio Flore Maciel APLICAÇÃO DA SIMULAÇÃO A EVENTOS DISCRETOS NO BALANCEAMENTO DE LINHA DE MONTAGEM.pdf: 1899747 bytes, checksum: ce39bd6323b1cd070d845c8ce1d9a680 (MD5) / Approved for entry into archive by Juliano Benedito Ferreira (julianoferreira@reitoria.unesp.br) on 2017-02-21T17:37:52Z (GMT) No. of bitstreams: 1 maciel_lf_me_guara.pdf: 1899747 bytes, checksum: ce39bd6323b1cd070d845c8ce1d9a680 (MD5) / Made available in DSpace on 2017-02-21T17:37:52Z (GMT). No. of bitstreams: 1 maciel_lf_me_guara.pdf: 1899747 bytes, checksum: ce39bd6323b1cd070d845c8ce1d9a680 (MD5) Previous issue date: 2016-04-01 / O objetivo geral da pesquisa foi desenvolver um modelo de simulação a eventos discretos para ser aplicado ao balanceamento de uma linha de montagem de componentes numa empresa do setor automotivo, buscando aumentar a produtividade da linha e utilizando menores quantidades de insumos. Na situação estudada há muitos elementos com comportamento estocástico, que podem influenciar na produtividade da linha, além da diversidade de insumos que abastecem a montagem, o que torna o balanceamento da linha uma tarefa complexa e favorece o uso da Simulação como procedimento de solução. Na modelagem conceitual do problema estudado adotou-se o método IDEF-SIM e para a simulação foi utilizado o software ProModel®. Como resultados tem-se um modelo conceitual e implementado para uma linha de montagem que possibilitou informações interessantes sobre o problema, tais como: juntar funções de dois postos de trabalhos, eliminar excesso de movimentação e eliminar gargalos. / The overall objective of the research was to develop a simulation model discrete event to be applied to balancing an assembly line components in automotive company, seeking to increase line productivity and using lower amounts of inputs. In the situation studied for many elements with stochastic behavior, which may influence the productivity of the line beyond the range of products that supply assembly, which makes the balancing line a complex task and promotes the use of the simulation procedure as a solution. In conceptual modeling of the studied problem adopted the IDEF-SIM method and for the simulation we used the ProModel® software. As results has a conceptual model and implemented for an assembly line that has enabled interesting information about the problem, such as joining functions of two posts jobs, eliminate excess movement and eliminate bottlenecks.

In direct reference to the saying “time is money”, nowadays scenario simulations play a key role in the tasks people perform. Optimizing the time length of tasks and synchronizing them properly is essential to increased profits in any line of business. In this thesis the Bergkvist-Insjön sawmill yard process will be computer simulated. As the number of trucks arriving at the sawmill is unknown, the unexpected arrival of trucks would produce a high pressure on internal resources and handling operations. The aim of this paper is to optimize the usage of the resources in the Bergkvist-Insjön sawmill, by running three different scenarios built based on the real system simulation. Scenario number three, in which a log stacker only has the tasks to unload the trucks and supply the measurement station, has been found most efficient. In the simulation of this scenario, the number of logs processed by the sawmill is the highest one. Also, the time spent by the log stackers between their tasks is the shortest one from all scenarios. The results of this thesis revealed that the most efficient improvement of the sawmill yard would be gained by a different tasks’ priority for the operating log stackers.

This thesis proposes a multidirectional methodological framework for a comprehensive ergonomic analysis and modelling of workflow for multi-modal vascular image-guided procedures (IGPs). Two approaches are employed to analyse the workflow: Discrete Event Simulation (DES) and purpose-oriented physical models. In contrast to previous studies, the proposed methodology looks in detail the actions carried out within the intervention rooms and the clinical experience during the procedures with three main objectives: to provide a deeper understanding of vascular procedures, to predict the impact of protocol modifications and to offer a framework to develop new image-guided protocols for the alternative use of Magnetic Resonance (MR) imaging in comparison with X-Ray Digital Subtraction Angiography (DSA). The methodological framework includes an assessment of commercial simulation software packages to evaluate their fitness to the specific requirements of this research. The novel methodology is applied to several cases studies of common vascular IGPs. In addition, a case of MR – guided focused ultrasound intervention demonstrates how it is possible to extend the framework to study non-vascular IGPs. The multi-disciplinary methodological framework described opens a new way to understand IGPs that could be used in prospective applications such as medical education and medical devices regulations.

The high complexity existent in businesses has required managers to rely on accurate and up to date information. Over the years, many tools have been created to give support to decision makers, such as discrete event simulation and artificial neural networks. Both tools have been applied to improve business performance; however, most of the time they are used separately. This research aims to interpret artificial neural network models that are applied to the data generated by a simulation model and determine which inputs have the most impact on the output of a business. This would allow prioritization of the variables for maximized system performance. A connection weight approach will be used to interpret the artificial neural network models. The research methodology consisted of three main steps: 1) creation of an accurate simulation model, 2) application of artificial neural network models to the output data of the simulation model, and 3) interpretation of the artificial neural network models using the connection weight approach. In order to test this methodology, a study was performed in the raw material receiving process of a manufacturing facility aiming to determine which variables impact the most the total time a truck stays in the system waiting to unload its materials. Through the research it was possible to observe that artificial neural network models can be useful in making good prediction about the system they model. Moreover, through the connection weight approach, artificial neural network models were interpreted and helped determine the variables that have the greatest impact on the modeled system. As future research, it would be interesting to use this methodology with other data mining algorithms and understand which techniques have the greatest capabilities of determining the most meaningful variables of a model. It would also be relevant to use this methodology as a resource to not only prioritize, but optimize a simulation model.

Discrete-event simulation can be a useful tool in analyzing complex system dynamics in various industries. However, it is difficult for entry-level users of discrete-event simulation software to both collect the appropriate data to create a model and to actually generate the base-case simulation model. These difficulties decrease the usefulness of simulation software and limit its application in areas in which it could be potentially useful. This research proposes and evaluates a data collection and analysis methodology that would allow for the programmatic generation of simulation models using production tracking data. It uses data collected from a GPS device that follows products as they move through a system. The data is then analyzed by identifying accelerations in movement as the products travel and then using those accelerations to determine discrete events of the system. The data is also used to identify flow paths, pseudo-capacities, and to characterize the discrete events. Using the results of this analysis, it is possible to then generate a base-case discrete event simulation. The research finds that discrete event simulations can be programmatically generated within certain limitations. It was found that, within these limitations, the data collection and analysis method could be used to build and characterize a representative simulation model. A test scenario found that a model could be generated with 2.1% error on the average total throughput time of a product in the system, and less than 8% error on the average throughput time of a product through any particular process in the system. The research also found that the time to build a model under the proposed method is likely significantly less, as it took an experienced simulation modeler .4% of the time to build a simple model based off a real-world scenario programmatically than it did to build the model manually.