Distributed Simulation in Industry

Csaba Attila Boer was born in Satu Mare, Romania, on 29 October, 1975. He completed his secondary education at Kölcsey Ferenc High School, in Satu Mare, in 1994. In the same year he started his higher education at Babeş-Bolyai University, Faculty of Mathematics and Computer Science, Cluj-Napoca, Romania, where he received his B.Sc. degree in Computer Science, in 1998, and his M.Sc. degree with major in Information Systems, specialization Designing and Implementing Complex Systems, in 1999. During these years, he obtained fellowships at the Eötvös Lóránd University, and at the Computer and Automation Research Institute of the Hungarian Academy of Sciences, Budapest, Hungary within the Central European Exchange Program for University Studies (CEEPUS). Since 1999, he has been affiliated with the Computer Science Department, Faculty of Economics at Erasmus University Rotterdam, The Netherlands. There, he worked as a researcher for one year, studying the storage and retrieval of discrete event simulation models, research that resulted in three scientific articles. Between 2000 and 2004, he was associated with the same department as a Ph.D. candidate aiming to research the area of distributed simulation and its application in industry. His topic being close to the research carried out at the Faculty of Technology, Policy and Management, Delft University of Technology, and the BETADE research program, he started to collaborate with researchers from these groups, getting involved in two joint practical case study projects. This collaboration resulted in seven joint scientific articles, presented at various international conferences. Furthermore, Csaba has maintained international contacts with researchers from the distributed simulation area. He has been invited twice to Brunel University, London to give a presentation concerning the application of distributed simulation in industry. Currently, he is working as a simulation consultant atGedistribueerde simulatie wordt binnen de defensie in brede kring geaccepteerd en toegepast, maar het heeft in de industrie geen voet aan de grond gekregen. In dit proefschrift onderzoeken we de redenen voor dit fenomeen door te bestuderen wat de industrie verwacht op het terrein van de gedistribueerde simulatie. In het algemeen worden in de industrie simulatiemodellen ontworpen en ontwikkeld met COTS (“commercial-off-the-shelf”) simulatiepakketten. Echter, de bestaande architecturen voor gedistribueerde simulatie binnen defensie zijn niet gericht op het koppelen van modellen gebouwd met COTS simulatiepakketten. Om de industrie te motiveren gedistribueerde simulatie te accepteren en te gebruiken moet men derhalve ernaar streven het mogelijk te maken om modellen, die gebouwd zijn met deze pakketten, aan elkaar te koppelen zonder dat dat al te veel inspanning vereist van de modelbouwers. Uitgaande van een onderzoek onder experts in dit domein, stellen we in dit proefschrift een pakket van eisen voor voor het ontwerp en ontwikkelen van gedistribueerde simulatiearchitecturen dat de industriegemeenschap zal motiveren om gedistribueerde simulatie te accepteren en toe te passen. Daarnaast presenteren we een lichtgewicht architectuur voor gedistribueerde simulatie die met succes toegepast is in twee industriële projecten, en die in grote mate voldoet aan het voorgestelde pakket van eisen.While distributed simulation is widely accepted and applied in defence, it has not gathered ground yet in industry. In this thesis we investigate the reasons behind this phenomenon by surveying the expectation of industry with respect to distributed simulation solutions. Simulation models in industry are mainly designed and developed in commercial-off-the-shelf (COTS) simulation packages. The existing distributed simulation architectures in defence, however, do not focus on coupling models created in COTS simulation packages. Therefore, in order to motivate the industrial community to easily accept and use distributed simulation, one should strive to couple models built in these packages. Further, coupling these models should be possible without needing too much extra effort from modellers. In this thesis, based on a survey with experts in domain, we propose a list of requirements for designing and developing distributed simulation architectures that would encourage the industrial community to accept and apply distributed simulation. Furthermore, we present a lightweight distributed simulation architecture which has been successfully applied in two industrial projects, and satisfies to a large extent the proposed requirements

Reusing simulation experiments for model composition and extension

This thesis aims to reuse simulation experiments to support developing models via model reuse, with a focus on validating the resulting model. Individual models are annotated with their simulation experiments. Upon reuse of those models for building new ones, the associated simulation experiments are also reused and executed with the new model, to inspect whether the key behavior exhibited by the original models is preserved or not in the new model. Hence, the changes of model behavior resulting from the model reuse are revealed, and insights into validity of the new model are provided

Simulação computacional: análise de um sistema de manufatura em fase de desenvolvimento.

O presente trabalho aborda um estudo de simulação para avaliar o desempenho de um novo sistema de manufatura que está em fase de desenvolvimento, ou seja, ainda não implantado. O estudo se desenvolve na seção de engenharia de desenvolvimento de uma empresa do setor de autopeças. O sistema de manufatura foco deste estudo, foi inicialmente idealizado numa fase de elaboração de orçamentos, fase em que, engenheiros orçamentistas pré conceberam o sistema a partir de desenhos e especificações técnicas fornecidas pelo cliente. É comum que na fase de desenvolvimento os engenheiros responsáveis discordem de idéias e decisões tomadas na fase de orçamento, ocorrendo então, as cobranças do tipo “tinha que se ter pensado nisso antes!”. Pensando nos futuros usuários do sistema, e preocupados com este mesmo tipo de cobrança, os responsáveis pelo desenvolvimento optaram pelo uso da simulação como uma técnica de análise e auxílio à decisão, visando obter informações preventivas e preditivas do funcionamento e desempenho futuro do sistema. Primeiramente foi realizada uma revisão da literatura verificando as pesquisas desenvolvidas sobre os conceitos e as ferramentas utilizadas neste trabalho: sistemas de produção; mapeamento de processo; arranjos físicos; tempo padrão; modelagem para a tomada de decisão; modelo de simulação; simulação computacional; ciclo da simulação; etapas do estudo da simulação etc. Na etapa de aplicação da simulação o estudo teve duas fases distintas: 1) foram descritos os principais conceitos e considerações do produto a ser fabricado; foram realizados diagrama, fluxograma e mapofluxograma dos processos; foram definidos os arranjos físicos e construídos os modelo conceituais dos processos. 2) construção dos modelos de simulação utilizando-se o pacote de simulação ProModel®; execução e análise dos experimentos. Como conclusões finais foram apresentados comentários sobre observações realizadas durante a construção dos modelos, realização dos experimentos, modificações e ajustes nos modelos. Também foi apresentado um quadro de resultados de redução de custos obtidos a partir da análise dos resultados do estudo da simulação. O trabalho também vislumbrou a importância do uso do recurso de animação apresentado pelo software como uma ferramenta para facilitar a comunicação entre a supervisão e a mão de obra direta, possibilitando transmitir facilmente, de maneira clara e objetiva, como se deseja que uma tarefa seja executada e qual o desempenho esperado, buscando o comprometimento e a participação do funcionário. Outra oportunidade vislumbrada é quanto à utilização da simulação na fase de realização de orçamentos, visando informações antecipadas que possibilitam maior competitividade em relação ao que se estiver sendo orçado

Comparing model reuse with model building : an empirical study of learning from simulation

What are the benefits of involving decision makers in simulation model development? Do decision makers learn more about their problem if they are involved in model development than if they had been excluded? This thesis presents an experiment which compares decision maker learning outcomes and process in two different types of discrete-event simulation (DES) study. The first is a traditional simulation project where decision makers take the role of domain experts and are involved in the building of a simulation model through to its use. The second is where a model is reused rather than built. Sixty four undergraduate participants were individually involved in one of three experimental conditions: development of an A&E simulation model and its subsequent use; development of the same model, but with less time for model use; or were presented with the model already developed and asked to reuse it. Participants of each condition were then allowed to run the model, change variables and review results in an attempt to improve the performance of the system. Learning was measured at two levels: attitude change, to infer learning about a business problem, and transfer of learning, to infer a deeper learning. Results indicated that, firstly, model building aided participant's discovery of aspects of the problem that were previously unconsidered. However, attitudes about these novel aspects of the problem were only converted to transferable knowledge when experimentation was not limited. Secondly, participants that reused the model learnt about the model through quick cycles of experimentation followed by validation, although these tended to be focused on factors with which participants were most familiar. In fact, model reuse participants learnt more following this approach than by scrutinizing the results of each scenario in detail. Little empirical evidence exists to support the discussions and the view that involvement in model building aids learning. This thesis contributes to this debate by providing insight into the mechanisms that in uence learning. Moreover, results suggest that learning from experimentation when reusing a model is also valid, although the process followed may be different. Of course, there are limitations to the approach used to perform the comparison. For instance, the experiment uses novice decision makers and measures attitude immediately after the experiment. Refl ection on such points is used to aid the generation of testable hypotheses that can be explored in future research

Simulação computacional: análise de uma célula de manufatura em lotes do setor de auto-peças

Computer Simulation (Discrete Event Simulation) is becoming one of the most popular tools for the modeling and analysis of complex manufacturing systems. In a manufacturing project the simulation can be used in two different phases: the phase of justification of the project and the phase of drawing the production processes. In the implementation phase, the simulation shows its main collaboration by helping to foresee possible problems, consequently generating savings of company’s financial resources. Besides the benefits during the phase of designing the process and subsequent its implementation, simulation has another focus, which is as a support tool for the company’s strategic planning. This strategic focus lies in the possibility of using the model to simulate several scenarios, such as the increase in the demand, impact of a new maintenance policy, the impact of changing the working shifts, the impact in relation to the sequencing programming or the change of the product mix along time without causing ruptures in the production in order to carry out real experiments. This work describes the application of the computacional simulation in a lot-manufacturing cell of a company that belongs to the sector of automotive parts, a manufacturer of rings for engine pistons. The discussion and the application of the simulation in this manufacturing cell generated the development of a necessary approach for the application of the simulation work in an industrial environment. This approach is not described in details in the literature, which usually presents methodologies focused on the execution of the working method of the simulation process. The execution of the work demanded the organization of a team and the careful description of each member’s role. Another point that must be highlighted is that the simulation itself doesn't solve all the problems, it is necessary previously to carry out and analyze the possible solutions that will be considered for modeling.A simulação computacional está se tornando uma das mais populares ferramentas de modelagem e análise de complexos sistemas de manufatura . Em um projeto de manufatura a simulação poderá ser usada em duas fases distintas: a fase de justificativa do projeto e na fase do desenho dos processos de fabricação. Na fase de implantação a simulação também colabora ajudando a prever possíveis problemas em campo e com isto gerando economia dos recursos financeiros da empresa. Além dos benefícios destacados durante a fase de projeto do processo e sua posterior implantação, a simulação tem outro enfoque como uma ferramenta de apoio ao planejamento estratégico da empresa. Este enfoque estratégico está na possibilidade de usar o modelo criado para simular diversos cenários, como o aumento da demanda, impacto de uma nova política de manutenção, o impacto da alteração dos turnos de trabalho, o impacto do seqüenciamento da programação ou a mudança do mix de produtos ao longo do tempo sem provocar rupturas na produção pela necessidade de realizar experimentos reais. Este trabalho descreve a aplicação da simulação computacional em uma célula de manufatura em lotes de uma empresa do setor de auto peças, fabricante de anéis para pistão de motor. A discussão e a aplicação da simulação nesta célula de manufatura gerou o desenvolvimento de uma abordagem necessária a execução do trabalho de simulação em um ambiente fabril. Esta abordagem não é descrita em detalhes na literatura, que normalmente traz metodologias focadas na execução do método de trabalho do processo de simulação. A execução do trabalho exigiu a organização de uma equipe e o detalhamento do papel de cada membro. Outro ponto a destacar é o de que a simulação em si não resolve todos os problemas, é necessária a criação e análise prévia das possíveis soluções que serão modeladas