Presented PhD thesis aims at development of new methodologies and approaches to reduce lead times in production systems. Therefore the thesis examines in detail the design of new, more comprehensive approaches to shortening lead times. The dissertation describes the methodology of using these approaches in production systems, it is suggested their inclusion in the control structure of production and adequate managerial support for the successful application of these new approaches in the industry is developed. The first part summarizes current knowledge in the field of reducing lead times. The various methods that can be used for reducing lead times are defined and described, from which is selected discrete simulation of manufacturing systems as a suitable method for the purposes of issue development. The next part of this work is therefore devoted to simulation approach to reducing lead times and the factors that affect them, such as processing time, size of the batch, queue lengths, etc. In this part is also discussed the use of information technologies (programming languages, libraries, and software tools) that enable efficient creation of simulation models. The second part is focused on industrial applications implemented to reduce production lead times. Specific simulation analysis deal with, for example, reduction of the lead time for manufacture of surgical instruments, screws, slats, but also transport systems, optimization of production orders input to the production system, the issue of supply, etc. The second part also describes a practical approach to data transfer to / from the simulation model, simulation software connection to the ERP database of enterprise and energy intensity of production. The conclusion summarizes the findings that were detected on the issue of reducing lead times, and within the chosen methodology, simulation of manufacturing processes indicates possible further progress in the research and practical applications.

Industry 4.0 has caused exceptional changes in the industrial world. A relevant breakthrough is the concept of Cyber-Physical Production System (CPPS) which involves a system of interconnected entities with the main objective of achieving flexibility, which is essential for the manufacturing industries to remain competitive due to the actual demand for customization. The project suggests the use of a robot cell distribution called robot island as a solution to address this problem. In the implementation, a virtual model and program will be presented with flexible mobile robots, AGVs and a PLC. All are designed following the three principles of the CPS using RobotStudio and CODESYS to simulate and evaluate the results. The research demonstrates how autonomous, modular, flexible and adaptable to changes in product or production process system is, for example with the integration of the concept of the resource pool and variations in the product characteristics. The resulting executable is made with standardised modules so it can be extrapolated to other manufacturing processes, opening a wide range of possibilities for this island of robots. / <p>Utbytesstudenter</p>

Актуальность темы исследования. Эффективная организация производственной системы является инструментом повышения конкурентоспособности предприятия на рынке. В период активного роста конкуренции и снижения спроса на продукцию наиболее успешными становятся компании способные проявлять гибкость в управлении и нацеленные на снижение себестоимости и оптимизации цикла производства. Для поддержания производственной системы на конкурентоспособном уровне необходимо не только соблюдать качество исполнения производственных регламентов и процессов, но и следовать новым трендам в области организации. Актуальность проблемы повышения эффективности функционирования производственной системы методами бережливого производства подтверждается недостаточной конкурентоспособностью российских предприятий на внешних рынках. В ходе работы рассмотрена эксплуатационная, техническая и экономическая документация. В результате проанализирован процесс производства медных катодов, произведены сметные расчеты расходов на внедрение инструментов бережливого производства, произведена оценка экономической эффективности внедряемых инструментов бережливого производства, рассмотрена текущая производственная ситуация при производстве медных катодов АО «Уралэлектромедь» в ключе применения алгоритма развития производственной системы, основанного на анализе результатов деятельности предприятия с применением «колеса бережливого производства» и позволяющий принимать оперативные управленческое решения и управлять развитием производственной системы. / Relevance of the research topic. Efficient organization of the production system is a tool to improve the competitiveness of enterprises in the market. In the period of active growth of competition and reduction in demand for products, companies that are most capable of flexibility in management and aimed at cost reduction and optimization of the production cycle become the most successful. To maintain the production system at a competitive level, it is necessary not only to comply with the quality of performance of production regulations and processes, but also to follow new trends in the organization. The urgency of the problem of increasing the efficiency of the production system functioning by methods of lean production is confirmed by the lack of competitiveness of Russian enterprises in foreign markets. During the work considered operational, technical and economic documentation. As a result, the copper cathode production process was analyzed, cost estimates for the introduction of lean manufacturing tools were estimated, the economic efficiency of the lean manufacturing tools introduced was evaluated, the current production situation in the production of copper cathodes by Uralelectromed JSC was considered in the key to the application of the development system algorithm based on the analysis results of the enterprise with the use of "lean wheel" and poses olyayuschy take operational decisions and manage the development of the production system.

No description available.

No description available.

La révolution la plus récente dans l'industrie (révolution industrielle 4.0) nécessite une plus grande flexibilité, agilité et efficacité dans l'utilisation des équipements de production. Le système manufacturier cellulaire dynamique (DCMS) est l'un des meilleurs systèmes de production qui répondent à ces exigences. En outre, l'importance croissante du développement durable force les fabricants et les gestionnaires à prendre en compte les enjeux environnementaux et sociaux dans la conception et la configuration des systèmes de fabrication. Cette thèse porte sur la configuration durable des DCMS en proposant trois modèles mathématiques. Le plus grand challenge de cette étude est (i) de choisir des critères sociaux et environnementaux appropriés, (ii) de les intégrer dans des modèles mathématiques et (iii) d'étudier l'impact de ces critères sur des DCMS. Le premier modèle est bi-objectif afin de faire un compromis entre certains critères sociaux (offres d'emplois, risques de la machine, etc.) et économiques (divers coûts liés à la formation de cellules). Pour être plus proche de situations de la vie réelle, certains paramètres tels que la demande, les coûts liés aux machines et la capacité en temps des machines sont considérés comme incertains. Pour résoudre ce problème, une méthode d'optimisation robuste est appliquée pour faire face à cette incertitude. Dans le deuxième modèle, toutes les dimensions du développement durable sont prises en compte dans le modèle mathématique bi-objectif proposé. La première fonction objectif modélise des critères économiques (coûts) et la seconde des aspects environnementaux (déchets de production), tandis que certaines contraintes représentent des questions sociales (principalement le « Daily Noise » à cause de la complexité de calcul). En raison de la NP-difficulté du problème, une nouvelle approche novatrice appelée NSGA II-MOSA est proposée. Le troisième modèle proposé a trois fonctions objectif, une pour chaque type d’enjeux : environnemental, social et économique. Afin d'être proche de la vie réelle, certains paramètres du modèle sont exprimés en termes de valeur floue. Nous proposons une méthode possibiliste hybride pour faire face à l'incertitude et une approche floue interactive est considérée pour résoudre un modèle multi-objectif déterministe pour des solutions de compromis. Enfin, la dernière partie de la thèse étudie la possibilité d'appliquer les trois modèles proposés à l’industrie grâce à une méthode plus facile. Une approche d'optimisation-simulation innovante est introduite pour faire face à la configuration de DCMS : (i) La phase d'optimisation fonctionne comme méthode de fractionnement de scénarii pour réduire le nombre de configurations alternatives en se concentrant sur les niveaux stratégique et tactique. (ii) Ensuite, un outil de simulation détaille le niveau opérationnel en étudiant la performance de chaque alternative et l'interaction entre plusieurs composants de cellules. / The most recent revolution in industry (Industrial Revolution 4.0) requires increased flexibility, agility and efficiency in the use of production equipment. Dynamic Cellular Manufacturing System (DCMS) is one of the best production systems to meet such requirements. In addition, the increasing importance of sustainable development forces manufacturers and managers to take account of the environmental and social issues in the design and configuration of manufacturing systems. This thesis focuses on the sustainable configuration of DCMS by proposing three mathematical models. The main challenge of this study is to (i) choose appropriate social and environmental criteria, (ii) integrate them in mathematical models, and (iii) study the impact of these criteria on DCMS. The first model is bi-objective in order to make a trade-off between some social (job opportunity, potential machine hazards, etc.) and economic (various costs related to cell formation) criteria. To get closer to real-life situations, some parameters such as demand, machine-related costs and time capacity of the machines are considered as uncertain. To solve this problem, a robust optimization method is applied to cope with this uncertainty. In the second model, all dimensions of sustainable development are taken into account in a new bi-objective mathematical model. The first objective function models economic criteria (costs) and the second one environmental aspects (production waste), while social issues (mainly Daily Noise Dosage because of computational complexity) are modeled as constraints. Due to the NP-hardness of the problem, a new innovative approach called NSGA II-MOSA is proposed. The last model has three objective functions, one for each dimension of the sustainable development: environmental, social and economic. In order to be close to real life, some parameters of the model are expressed in terms of fuzzy value. We propose a hybridized possibilistic method to deal with uncertainty and an interactive fuzzy approach is considered to solve an auxiliary crisp multi-objective model in order to find trade-off solutions. Finally, the last part of the thesis studies the possibility to apply the three proposed models to the industry thanks to an easier method. A novel optimization-simulation approach is introduced to deal with the configuration of DCMS: (i) the optimization phase operates as scenario fraction method in order to reduce the number of alternative configurations by focusing on strategic and tactical levels; (ii) next, a simulation tool investigates the operational level by studying the performance of each alternative and the interaction between several components of the cells.

Dans cette thèse nous analysons dans quelle mesure le concept de mobilité peut être pris en compte dans la démarche d'analyse et de conception de systèmes de production. Notre apport vise à formaliser la démarche d'analyse et de conception de ce dernier, explicitant les décisions à prendre, les informations nécessaires et les critères de décision à mettre en place. Dans cet objectif, deux niveaux d'analyse ont été distingués : un niveau local concernant un site de production et un niveau global comprenant un ensemble de sites.Le premier niveau local considère un seul site de production. A ce niveau nous avons proposé une approche prenant en compte les caractéristiques du site de production. Dans notre contexte, le choix de la localisation géographique de production est imposé par le client. De ce fait, la conception du système de production doit s'adapter à cette contrainte. D'un point de vue conception, quatre questions sont abordées : (1) dans quelle mesure le concept de mobilité peut être intégré dans une démarche de conception de système de production mobile ? (2) quelles caractéristiques de l'environnement de production doivent être prises en compte ? (3) comment déterminer ce qu'il faut produire sur site ou ce qu'il serait opportun d'externaliser ? et (4) compte tenu des informations obtenues quelle est la meilleure configuration du SPM à envisager et selon quels critères de choix ? La réponse à ces questions conduit à la proposition d'une configuration du SPM adaptée pour un seul site de production.Le deuxième niveau global traite la problématique de mobilité successive multi sites. En effet, pour être rentabilisé le système de production doit être mobilisé sur plusieurs sites de production. A chaque changement de site de production, une reconfiguration du système de production s'impose en se basant sur la configuration existante (version i-1). LaThèse de Youssef BENAMAreconfigurabilité concerne d'une part l'architecture interne du système (choix des machines, recrutement de nouvelles équipes locales, etc) et d'autre part l'organisation de la chaîne d'approvisionnement du SPM (faire en interne ou externaliser, fournisseur local, etc.). A ce niveau global d'analyse, nous proposons deux modèles d'analyse : (1) un premier modèle pour l'analyse de la reconfigurabilité interne. Ce modèle d'analyse permet d'adapter le nombre de lignes de production et le nombre d'équipes en fonction d'un scénario de demande (localisations géographiques, capacité nécessaire par site). L'originalité de notre proposition consiste d'une part en l'évaluation des coûts de reconfiguration nécessaires et d'autre part l'appréciation du niveau d'adéquation de la configuration proposée avec le contexte du site de production via l'utilisation de l'indicateur de mobilité. (2) Le deuxième modèle d'analyse concerne la reconfigurabilité de la chaîne d'approvisionnement amont du SPM. Il consiste en une adaptation du modèle d'aide à la décision "faire ou faire faire" par l'intégration d'un côté de l'importance du site de production et d'un autre côté des spécificités de chaque site de production.La démarche d'analyse proposée est illustrée sur le cas industriel concernant la conception d'une usine mobile pour la fabrication et l'installation sur site de composants de centrales solaires thermodynamiques. / In this thesis we analyse how the concept of mobility can be taken into account in the analysis and design of production systems. Our contribution aims to formalize the analysis and design process, explaining the decisions, the necessary information and decision criteria to be taken into account. For this purpose, two levels of analysis were distinguished: a local level concerning one production site and a global level including a set of sites.The first level considers one production site. At this level we have proposed an approach that takes into account the characteristics of the production site. In our context, the choice of the geographical location of production is imposed by the final client. Therefore, the design of the production system should be adapted to this constraint. From a design perspective, four questions are addressed: (1) To what extent the concept of mobility can be integrated into a mobile production system design approach? (2) What characteristics of the production environment must be taken into account? (3) How to determine what to produce on site or that it would be appropriate to outsource? And (4) taking into account all obtained information what is the best configuration of the mobile production system to consider and according towhich criteria? The answer to these questions led to the proposal of a configuration of SPM suitable for a single production site.The second Level of analysis addresses the problem of global mobility. In order to be profitable, the production system must be used on several production locations. every change of production location led to a need of reconfiguration of the Production System. Reconfigurability Concerns the internal architecture of the system (machine selection, recruitment News local teams, etc.) as well as the organization of the SPM supply chain. Fot this global level, we propose two analytical models: (1) the first model for the analysis of internal reconfigurability. This analysis model is used to adapt the number of production lines and the number of teams according to a production scenario (Geographical locations, necessary capacity per site). The originality of our proposal consists on the assessment of costs to support reconfiguration and the appreciation the convenience level with the context of the production site by using the mobility indicator. (2) Second model to analyse Concerns reconfigurability of the upstream supply chain of PMS. It Consists in June adaptation of the model using the decision "to do ou do" by integrating A side of the importance of the production site and another side Specifics Each of the production site.The proposed approach is illustrated on an industrial case concerning the design of a mobile manufacturing plant used to produce in-site and Install components of solar plant

Submitted by Alison Vanceto (alison-vanceto@hotmail.com) on 2017-08-30T12:26:40Z No. of bitstreams: 1 DissMSV.pdf: 2771156 bytes, checksum: add74067c9db203edececa7202e83a52 (MD5) / Approved for entry into archive by Ronildo Prado (ronisp@ufscar.br) on 2017-09-20T14:06:15Z (GMT) No. of bitstreams: 1 DissMSV.pdf: 2771156 bytes, checksum: add74067c9db203edececa7202e83a52 (MD5) / Approved for entry into archive by Ronildo Prado (ronisp@ufscar.br) on 2017-09-20T14:06:22Z (GMT) No. of bitstreams: 1 DissMSV.pdf: 2771156 bytes, checksum: add74067c9db203edececa7202e83a52 (MD5) / Made available in DSpace on 2017-09-20T14:11:11Z (GMT). No. of bitstreams: 1 DissMSV.pdf: 2771156 bytes, checksum: add74067c9db203edececa7202e83a52 (MD5) Previous issue date: 2016-08-29 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) / In recent years, several studies have been carried out to minimize the production time (makespan) in a production schedule of a scenario that represents a manufacturing system. The problem of production scheduling is classified as a combinatorial problem belongs to the NP-hard class of computational problems. Furthermore, in a real world production system, there are many unexpected events (eg, review of production, entry of new products, breaking machines, etc.). To deal with the interruptions of the initial programming, we need to change any settings, which is called reactive production schedule or, simply, reactive scheduling. As a problem of combinatorial features, meta-heuristics is widely used in its resolution. This paper proposes a method that uses an evolutionary meta-heuristic Genetic Algorithm in conjunction with an operator called “Transgenics”, which allows to manipulate the genetic material of individuals adding features which are believed to be important, with the proposal to direct some population of individuals to a more favorable solution to the problem without removing the diversity of the population with a lower cost of time. The objective of this study is to use the Genetic Algorithm with transgenics operator obtain a reactive programming acceptable response time to minimize the makespan value. The objective of this study is to use the Genetic Algorithm with transgenics Operator obtain a reactive programming acceptable response time to minimize the makespan value. Experimental results show the proposed algorithm is able to bring better results than the makespan algorithm and compared in a shorter processing time due to the search direction which provides transgenic operator. / Nos últimos anos, várias pesquisas vêm sendo realizadas a fim de minimizar o tempo total de produção (makespan) em uma programação da produção de algum cenário que representa um sistema de manufatura. O problema da programação da produção é classificado como sendo um problema combinatório pertencente à classe NP-Hard dos problemas computacionais. Além disso, em um sistema de produção real, há muitos eventos inesperados (por exemplo, a revisão da produção, chegada de novos produtos, quebra máquinas, etc.). Para lidar com as interrupções da programação inicial, é preciso realizar outra programação, a qual é denominada de programação reativa da produção. Sendo um problema de recursos combinatórios, é amplamente utilizado metaheurísticas em sua resolução. Neste trabalho é proposto um método que faz uso de uma metaheurística evolutiva Algoritmo Genético em conjunto com um operador intitulado Operador de Transgenia, no qual possibilita manipular o material genético dos indivíduos acrescentando características das quais se acredita serem importantes, com a proposta de direcionar alguns indivíduos da população para uma solução mais favorável para o problema sem tirar a diversidade da população com um custo menor de tempo. O Objetivo deste trabalho é utilizando o Algoritmo Genético com Operador de Transgenia obter uma programação reativa em tempo de resposta aceitável, visando minimizar o valor de makespan. Resultados experimentais mostraram que algoritmo proposto foi capaz de trazer resultados de makespan melhores que os algoritmos comparados e em um menor tempo de processamento, devido ao direcionamento na busca que operador de transgenia proporciona.

Made available in DSpace on 2016-06-02T19:06:27Z (GMT). No. of bitstreams: 1 DissARS.pdf: 1479466 bytes, checksum: b0e4db694de6cc642354b502d3f9187f (MD5) Previous issue date: 2005-05-31 / Universidade Federal de Sao Carlos / Production planning in automated manufacturing environments is a complex task which comprehends, among other activities, the production sequencing. One of the techniques used to determine the best production sequencing is the simulation. All possible sequences can be simulated and, right after that, the sequences with the best performance are verified, according to some criteria. However, due to the combinatory nature of the sequencing, the simulation of all possible combinations takes long time, becoming quite impracticable in many cases. Besides, events that were not programmed occur frequently in automated manufacturing environments and the decision maker must be fast choosing alternatives. Aiming to contour this problem, this work proposes a fuzzy analyser of sceneries for the production sequencing (ANCSP). The goal is to reduce the quantity of sequences to be simulated by the decision maker when non programmed events occur in the productive system, according to a defined performance criteria. The maximum quantity of generated sequences is calculated based on the time avaliable to realize the simulation. The proposed model intends to support the usage of the simulation technique by the decision makers. The ANCSP was implemented and various tests were performed. A specific model of flexible manufacturing system was considered to perform the tests. The performance of the ANCSP was analyzed comparing its results with those presented by a simulation software, for the same test sets and in accordance to the performance measures established. / O planejamento da produção em ambientes automatizados de manufatura é uma tarefa complexa que compreende, dentre outras atividades, o sequenciamento da produção. Uma das técnicas usadas para determinar qual a melhor sequência de produção é a simulação. Todas as sequências possíveis são simuladas e, logo após, verifica-se qual a sequência que obteve o melhor desempenho, de acordo com algum critério. Entretanto, devido à natureza combinatória do sequenciamento, a simulação de todas as sequências possíveis consome muito tempo, tornando-se inviável em muitos casos. Além disso, eventos não programados ocorrem com frequência nos ambientes automatizados de manufatura e o tomador de decisão precisa ter escolhas rápidas. Visando contornar esses problemas, esse trabalho propõe um analisador nebuloso de cen´arios para o sequenciamento da produção (ANCSP). O objetivo é reduzir a quantidade de sequências a serem simuladas pelo tomador de decis ao no momento da ocorrência de eventos não programados no sistema produtivo, de acordo com alguma medida de desempenho. A quantidade máxima de sequências geradas é calculada com base no tempo que o tomador de decisão possui para realizar a simulação. Dessa maneira, o modelo proposto pretende apoiar o uso da técnica de simulação pelos tomadores de decisão. O ANCSP foi implementado e diversos testes foram realizados. Para a realização dos testes, considerou-se um modelo específico de sistema flexível de manufatura. O desempenho do ANCSP foi analisado mediante comparação dos seus resultados com aqueles apresentados por um software de simulação, para o mesmo conjunto de testes e de acordo com as medidas de desempenho estabelecidas.

Submitted by Alison Vanceto (alison-vanceto@hotmail.com) on 2017-01-03T12:57:22Z No. of bitstreams: 1 DissMRS.pdf: 7075641 bytes, checksum: 8e6f815544b7f6f2ce4a1a5a47b25482 (MD5) / Approved for entry into archive by Marina Freitas (marinapf@ufscar.br) on 2017-01-16T16:33:09Z (GMT) No. of bitstreams: 1 DissMRS.pdf: 7075641 bytes, checksum: 8e6f815544b7f6f2ce4a1a5a47b25482 (MD5) / Approved for entry into archive by Marina Freitas (marinapf@ufscar.br) on 2017-01-16T16:33:38Z (GMT) No. of bitstreams: 1 DissMRS.pdf: 7075641 bytes, checksum: 8e6f815544b7f6f2ce4a1a5a47b25482 (MD5) / Made available in DSpace on 2017-01-16T16:33:48Z (GMT). No. of bitstreams: 1 DissMRS.pdf: 7075641 bytes, checksum: 8e6f815544b7f6f2ce4a1a5a47b25482 (MD5) Previous issue date: 2016-12-14 / Não recebi financiamento / In recent years, companies have used Artificial Intelligence (AI) techniques to facilitate the decisionmaking process in manufacturing systems. The use of these techniques allows increased performance of Flexible Manufacturing System (FMS). The automation of the process using computational resources allows a deeper analysis of the system conditions, which sometimes result in a better decision taking. In this sense, the Fuzzy Logic has been engaged to carry out this task, because it has the characteristic of dealing easily with inaccurate information and encoding knowledge specialist in Fuzzy rules. However, as soon as the system complexity increases, the task of generating a Fuzzy Rule Base (FRB) appropriate to the proposed system becomes increasingly difficult. To assist this process of generation of the FRB, several techniques can be used and among them stand out the search technique called Evolutionary Algorithm (EA). The EA is used, for example, for tuning the FRB of the FMS through the reduction of the optimization variables values as Makespan or Tardiness. In the case of variable called Makespan, the tuning occurs when the EA generates an FRB that reduces the makespan values of a FMS. However, the construction of the EA that effectively generates a tuning FRB is not trivial. It is required to be in the process, the construction of various EA with different selection methods and different mutation rates among other settings until an appropriate EA for a given situation appears. Therefore, in this study we aim to build an environment configuration and performance analysis of EAs in order to define the tuning FRB of the Fuzzy Control System of an FMS, i.e., it is intended to investigate how the EA ideal parameter scenario used for tuning the FRB of the said control system. In this study, the used EA was an extension of Genetic Algorithm (GA). For implementing the proposal, an evolutionary system for configuration and analysis of this variant of the GA was created. In this system, entitled "EvolSys - Evolutionary System" parameters of the system as Number of Input Variables of FRB, Number of Output Variables of FRB, Population Size, Mutation Rate and the EA Crossover Rate, among others are configured and then, one FRB is generated. Using this, there is an EA analysis of the possibility for choosing a FRB that will provide the reduction of makespan in FMS. Consequently, through this study, we may conclude that the use of EAs in collaboration with Fuzzy system may become an important tool for turning the system responsibility to the sequences of an FMS operation. Accordingly, the environment created meets the configuration step and analysis of EAs. / Nos últimos anos, empresas tem usado técnicas de Inteligência Artificial (AI) para auxiliar o processo de tomada de decisão em sistemas de manufatura. O uso dessas técnicas possibilita o aumento do desempenho dos Sistemas Flexíveis de Manufatura (FMS), uma vez que a automatização do processo com o uso de recursos computacionais permite uma análise mais profunda das condições do sistema o que, por vezes, resulta em uma melhor tomada de decisão. Neste sentido, a Lógica Fuzzy vem sendo usada para realizar essa tarefa, pois ela tem a característica de lidar facilmente com informações imprecisas, codificando o conhecimento do especialista nas chamadas Regras Fuzzy. Entretanto, à medida que a complexidade do sistema aumenta, a tarefa de gerar uma Base de Regras Fuzzy (FRB) adequada ao sistema proposto se torna cada vez mais difícil. Para auxiliar esse processo de geração da FRB, várias técnicas podem ser usadas e dentre elas destaca-se a técnica de busca denominada Algoritmo Evolutivo (EA). O EA pode ser usado, por exemplo, para a sintonia da Base de Regras Fuzzy do Sistema de Controle de um FMS por intermédio da redução de valores de variáveis de otimização como Makespan ou Tardiness. No caso da variável denominada Makespan, a sintonia ocorre quando o EA gera uma FRB que reduz os valores do makespan do FMS em questão. Entretanto, a construção do EA que efetivamente gera uma FRB sintonizada para um FMS não é trivial, pois é necessário que haja, nesse processo, a construção de vários tipos de EA com métodos de seleção diferentes, taxas de cruzamento e mutação diferentes dentre outras configurações, até que se encontre o EA adequado à uma dada situação. Sendo assim, no presente trabalho, o objetivo é a construção de um ambiente de configuração e análise de desempenho de EAs para sintonia da FRB do Sistema de Controle de um FMS, ou seja, pretende-se investigar qual o cenário de parâmetros ideal do EA usado na sintonia da FRB do referido sistema de controle. No presente trabalho, o EA usado foi uma extensão do Algoritmo Genético (GA). Para implementação da proposta, um Sistema Evolutivo para configuração e análise dessa variante do GA foi criado. Nesse sistema, intitulado “EvolSys - Evolutionary System”, parâmetros dos sistema como Número de Varáveis de Entrada da FRB, Número de Variáveis de Saída da FRB, Tamanho da População, Taxa de Mutação e Taxa de Cruzamento do EA, dentre outros são configurados e, por consequência, uma FRB é gerada. Com isso, há a possiblidade da análise do EA para a escolha de uma FRB que venha propiciar a redução do makespan em FMSs. Portanto, é possível concluir, a partir desse trabalho, que o uso de EAs em colaboração com os sistemas Fuzzy pode vir a se tornar uma importante ferramenta para sintonia da Base de Regras do sistema responsável pelo sequenciamento das operações de um FMS e, nesse sentido, o ambiente criado cumpre a etapa de configuração e análise do desempenho de EAs.