Definition, Analysis, And An Approach For Discrete-Event Simulation Model Interoperability

Even though simulation technology provides great benefits to industry, it is largely underutilized. One of the biggest barriers to utilizing simulation is the lack of interoperability between simulation models. This is especially true when simulation models that need to interact with each other span an enterprise or supply chain. These models are likely to be distributed and developed in disparate simulation application software. In order to analyze the dynamic behavior of the systems they represent, the models must interoperate. However, currently this interoperability is nearly impossible. The interaction of models also refers to the understanding of them among stakeholders in the different stages of models¡Š lifecycles. The lack of interoperability also makes it difficult to share the knowledge within disparate models. This research first investigates this problem by identifying, defining, and analyzing the types of simulation model interactions. It then identifies and defines possible approaches to allow models to interact. Finally, a framework that adopts the strength of Structured Modeling (SM) and the Object-Oriented (OO) concept is proposed for representing discrete event simulation models. The framework captures the most common simulation elements and will serve as an intermediate language between disparate simulation models. Because of the structured nature of the framework, the resulting model representation is concise and easily understandable. Tools are developed to implement the framework. A Common User Interface (CUI) with software specified controllers is developed for using the proposed framework with various commercial simulation software packages. The CUI is also used to edit simulation models in a neutral environment. A graphical modeling tool is also developed to facilitate conceptual modeling. The resulting graphic can be translated into the common model representation automatically. This not only increases the understanding of models for all stakeholders, but also shifts model interactions to the ¡§formulating¡š stage, which can prevent problems later in the model¡Šs lifecycle. Illustration of the proposed framework and the tools will be given, as well as future work needs

CAPACITY IMPROVEMENT AND CYCLE TIME REDUCTION USING VALUE STREAM MAPPING AND SIMULATION FOR A PRODUCTION PLANT IN QATAR, A CASE STUDY

This Project deals with a real life problem of a construction company, and is about capacity mismatches between different manufacturing modules. This mismatch badly influences the production and results in increased cycle time. Thus the objective of this project is to attempt capacity equalization (reducing mismatch) which if taken care off will improve the capacity and will lead to cycle time reduction. The company owns a stabilizing plant. This company operates in Qatar and specialized in infrastructure projects mainly in road construction and road development. This company is anticipating an increase in demand due to booming road construction activities mainly due to 2022 FIFA World Cup and development of infrastructure in line with Qatar National Vision 2030. The company executives were interested for a detailed investigation to analyze the problem of capacity mismatch between the different workstations of their plant and wanted to address the higher cycle time as well. This project was undertaken to investigate the above mentioned problem using scientific and proven process improvement management tools which are in use for such types of problems. For this investigation the student attempted lean based value stream mapping as a major investigation approach. Value stream mapping (VSM) has been in use for the last 20 years to get more from the existing processes without any significant investment. Besides this, it has been in use for capacity improvement and capacity mismatch analysis based situations also. The data were collected from the plant during operation, indicating the cycle time and capacity of each workstation and based on these details current state was prepared. This was an eye opening exercise, and this process management based tool proved as a trigger for improvement and the mismatch related problem was pin pointed. Based on this current state, after exposing various pockets of inefficiency several improvement measures were suggested. Based on these suggested improvements the future state is attempted. As the implementation could not be achieved, so to validate the changes simulation was used as tool to demonstrate the impact of these changes on the cycle time. Simulated future state results after incorporating improvements demonstrated the capacity balance problem and resulted in improvement in cycle time and finally a comparison was made between the two states and future scope of work was reported

Modeling Multilevel Supply Chain Systems to Optimize Order Quantities and Order Points Through Mathematical Models, Discrete Event simulation and Physical Simulations

Managing supply chains in today\u27s distributed manufacturing environment has become more complex. To remain competitive in today\u27s global marketplace, organizations must streamline their supply chains. The practice of coordinating the design, procurement, flow of goods, services, information and finances, from raw material flows to parts supplier to manufacturer to distributor to retailer and finally to consumer requires synchronized planning and execution. Efficient and effective supply chain management assists an organization in getting the right goods and services to the place needed at the right time, in the proper quantity and at acceptable cost. Managing this process involves developing and overseeing relationships with suppliers and customers, controlling inventory, and forecasting demand, all requiring constant feedback from every link in the chain. Base Stock Model and (Q, r) models are applied to three tier single-product supply chain to calculate order quantities and reorder point at various locations within the supply chain. Two physical simulations are designed to study the above supply chain. One of these simulations is specifically designed to validate the results from Base Stock model. A computer based discrete event simulation model is created to study the three tier supply chain and to validate the results of the Base Stock model. Results from these mathematical models, physical simulation models and computer based simulation model are compared. In addition, the physical simulation model studies the impact of lean implementation through various performance metrics and the results demonstrate the power of physical simulations as a pedagogical tool for training. Contribution of present work in understanding the supply chain integration is discussed and future research topics are presented

Documentação da lógica de modelos de simulação por meio do uso da técnica de modelagem IDEF-SIM.

A gestão do conhecimento aplicada em projetos de simulação é de grande importância, uma vez que ela possibilita a retenção do conhecimento, podendo este ser repassado para outras pessoas e até mesmo utilizado em projetos futuros. Dessa forma, é necessário registrar as lógicas de programação utilizadas em modelos computacionais. Assim, o objetivo desse trabalho é verificar a aplicabilidade da técnica de modelagem IDEF-SIM no registro de lógicas de programação de modelos de Simulação a Eventos Discretos. Essa aplicabilidade será analisada, incluindo, se for necessário, alterações na técnica para aperfeiçoá-la. Para isso, primeiramente foi realizada uma revisão sistemática da literatura com a finalidade de verificar como a técnica IDEF-SIM está sendo utilizada, identificando as principais lacunas. Também foram definindos os parâmetros para a pesquisa, como a técnica utilizada e os softwares para a construção dos modelos computacionais. Logo em seguida, através do método de pesquisa-ação, foram selecionados três modelos simulados no software ProModel®. A cada ciclo da pesquisa-ação, um modelo foi reproduzido, sendo cada um deles convertidos para o IDEF-SIM com as suas lógicas de programação e depois reproduzido no software FlexSim®. Os softwares ProModel® e FlexSim® foram escolhidos devido à diferença existente em relação à programação dos mesmos. O grau de dificuldade e inserção de elementos foram aumentando em cada ciclo da pesquisa-ação. As análises e conclusões de cada ciclo foram feitas por testes estatísticos, uma vez que os modelos foram programados por dois diferentes especialistas. Ao final de cada seção, melhorias propostas no IDEF-SIM foram identificadas para o próximo ciclo. Para a confirmação da pesquisa, um processo hipotético foi construído e aplicado em uma sala de aula, onde os alunos estavam aprendendo Simulação a Eventos Discretos. Após a programação, um questionário foi aplicado para medir a aplicabilidade da técnica. Depois dos testes, uma alteração no método de modelagem e simulação de Montevechi et al. (2010) foi proposta. Através dos ciclos de pesquisa-ação e do questionário respondido, pode-se afirmar que a técnica de fato consegue reproduzir a programação da lógica do modelo computacional, de forma clara e sem gerar confusões, contribuindo para a gestão do conhecimento em projetos de simulação

Discrete event simulation and lean production: quantification of waste in a pharmaceutical industry

Nowadays it is imperative that companies seek constant improvements in their operational performance so as not to become obsolete in relation to the new cutting edge trends of smart manufacturing or industry 4.0. In this context, it is noteworthy that manufacturing must occur in the presence of variability and uncertainty, and manufacturing systems must be complex, efficient and lean. Therefore, a conduct aimed at interventions focused on reducing waste in manufacturing and service operations are essential actions. A tool that can help in this purpose is the discrete event simulation (DES). In this context, the objective of this research is to apply DES and quantify the financial waste arising from non-value-adding activities. The object of study was a production line of a pharmaceutical industry and as a research method an approach was used combining modeling and simulation (quantitative) and case study (qualitative) methods. The software chosen was Flexsim®, a powerful simulation and process analysis tool that helps professionals in decision making. Finally, the results obtained through this research show the great financial waste in the analyzed assembly line. This impactful result on losses in the operation serves as a warning so that intervention measures are planned and executed to eliminate or mitigate the consequences of this waste

Modelagem e Simulação de uma proposta de implantação de leiaute em uma Empresa do Setor Automotivo.

A simulação a eventos discretos tem sido utilizada na manufatura e na área de serviço para determinar por exemplo: o gargalo, o lead time e o tempo médio de fila de um sistema. A presente dissertação visa mostrar o trabalho realizado em uma empresa do setor automotivo que se utilizou da simulação a eventos discretos e a teoria de leiaute na manufatura para mensurar a quantidade de máquinas necessárias para criar um leiaute especifico a uma família de produto. No entanto, outros pontos foram avaliados como a aceitação da simulação a eventos discretos na empresa e a comparação dos ganhos estimados pelo mapeamento de fluxo de valor (Value Stream Mapping) com os ganhos reais obtidos na criação do novo leiaute. Para tal, precisou-se obter dados referentes ao tempo padrão, amostra com os tamanhos de lotes, frequência de produção dos itens da empresa, tempo de setup, frequência média de quebra das máquinas e tempo médio para o seu reparo. Dessa forma foi possível criar e validar o modelo computacional e assim quantificar o número de máquinas necessárias para produzir o demandado pelo cliente. Essa quantidade serviu como matéria prima para criar uma proposta de leiaute que fosse mais adequada para a fabricação do produto estudado. O novo leiaute obteve os resultados esperados, reduzindo o refugo médio para a família de produto estudada, o estoque em processo, seu lead time de fabricação e aumentou sua produtividade. Além disso o projeto auxiliou na compreensão da aceitação da simulação na empresa e na comparação entre os ganhos estimados pelo Value Stream Mapping e os ganhos reais obtidos

Integração da simulação a Eventos Discretos e mapeamento do fluxo de valor para melhoria do sistema de distribuição de medicamentos em um hospital.

Este trabalho utilizou a Simulação a Eventos Discretos e o Mapeamento do Fluxo de Valor (MFV) para avaliar o sistema de distribuição de medicamentos de um hospital, devido a constantes atrasos na entrega de medicamentos aos pacientes. Desta forma, o trabalho tem como objetivo integrar simulação a eventos discretos e o mapeamento do fluxo de valor para melhoria de processos em uma farmácia hospitalar. A presente pesquisa aplicou a metodologia modelagem e simulação para analisar o sistema, em que foi divida em fase de concepção, fase de implementação, e fase de análise, na qual foi realizado um diagnóstico por meio do Mapa do Estado Atual para identificar os erros e desperdícios do processo e posteriormente, foram discutidas alterações através do Mapa do Estado Futuro. O Mapa do Estado futuro elaborado foi utilizado como projeto experimental da simulação. As alterações propostas foram o balanceamento da chegada das prescrições, a abertura de um novo posto de trabalho e a eliminação das paradas não planejadas dos funcionários. Analisando os relatórios obtidos com as replicações foi possível compreender e quantificar o impacto dessas alterações sobre o processo. Por fim, com utilização Delineamento de Experimentos, notou-se que com todos os fatores no estado de melhoria é possível atender todos os pacientes de acordo com a prescrição médica

Development of a standard framework for manufacturing simulators

Discrete event simulation is now a well established modelling and experimental technique for the analysis of manufacturing systems. Since it was first employed as a technique, much of the research and commercial developments in the field have been concerned with improving the considerable task of model specification in order to improve productivity and reduce the level of modelling and programming expertise required. The main areas of research have been the development of modelling structures to bring modularity in program development, incorporating such structures in simulation software systems which would alleviate some of the programming burden, and the use of automatic programming systems to develop interfaces that would raise the model specification to a higher level of abstraction. A more recent development in the field has been the advent of a new generation of software, often referred to as manufacturing simulators, which have incorporated extensive manufacturing system domain knowledge in the model specification interface. Many manufacturing simulators are now commercially available, but their development has not been based on any common standard. This is evident in the differences that exist between their interfaces, internal data representation methods and modelling capabilities. The lack of a standard makes it impossible to reuse any part of a model when a user finds it necessary to move from one simulator to another. In such cases, not only a new modelling language has to be learnt but also the complete model has to be developed again requiring considerable time and effort. The motivation for the research was the need for the development of a standard that is necessary to improve reusability of models and is the first step towards interchangability of such models. A standard framework for manufacturing simulators has been developed. It consists of a data model that is independent of any simulator, and a translation module for converting model specification data into the internal data representation of manufacturing simulators; the translators are application specific, but the methodology is common and illustrated for three popular simulators. The data model provides for a minimum common model data specification which is based on an extensive analysis of existing simulators. It uses dialogues for interface and the frame knowledge representation method for modular storage of data. The translation methodology uses production rules for data mapping

Economic evaluation of scenarios for manufacturing systems using discrete event simulation based experiments

This paper aims to perform economic evaluation of scenarios for manufacturing systems via discrete event simulation based experiments. First, three simulation models were built to mimic three manufacturing cells from two companies. In these simulation models, there are eight, thirty two and sixty four scenarios to be economically analyzed. Then, the decision makers can choose the best scenario by selecting the highest net present value, according to a future predicted demand. The research´s results allowed the identification of an activity that should not exist inside the production process (an analyzed scenario). So, the simulation model gained credibility among the decision makers after it pointed out a 35% of increase in the current monthly output. Finally, this work is concluded by highlighting the role of the design of experiments to select the most relevant scenarios to be economically analyzed. This saves time, when there are a large number of scenarios

Proposta de uso integrado entre o Mapeamento do Fluxo de Valor e a Simulação a Eventos Discretos em uma fábrica de laticínios.

O objetivo deste trabalho consiste em analisar a integração entre as técnicas Mapeamento do Fluxo de Valor (MFV) e Simulação a Eventos Discretos (SED), elaborar uma proposta de integração entre as duas técnicas e aplicar essa proposta em um caso real. A aplicação da proposta de integração ocorreu em uma fábrica de laticínios marcado pela presença de eventos discretos, contínuos e em batelada. A partir do MFV do estado atual foi possível identificar e registrar os desperdícios do processo de fabricação de queijos. Um modelo computacional do estado atual foi desenvolvido para monitorar esses desperdícios e tornar os critérios de avaliação como lead time e tempo de agregação de valor (TAV), inicialmente determinístico, em valores estocásticos. Em seguida, um MFV do estado futuro foi desenvolvido com base nos conceitos do lean, propondo melhorias para o processo produtivo. Essas melhorias foram implementadas a partir da modificação do modelo computacional do estado atual, gerando um modelo computacional para o estado futuro. Ao final do modelo de simulação, experimentos foram gerados através da técnica DOE (design of experiments) e simulados, gerando assim um cenário futuro ideal. As melhorias observadas no processo de laticínios foram: diminuição do lead time, do TAV e aumento da flexibilidade na produção dos diversos itens. A análise e aplicação da proposta de integração gerou um guia estruturado que auxiliará a prática integrada entre o MFV e a SED