Um simulador para análise de redes de produção da indústria 4.0

• Autor(a) principal: Pereira, Adriano
• Data de Publicação: 2019
• Tipo de documento: Tese
• Idioma: por
• Título da fonte: Manancial - Repositório Digital da UFSM
• dARK ID: ark:/26339/0013000003qnv
• Texto Completo: http://repositorio.ufsm.br/handle/1/20541
• topic: Simulador; Produção; Rede; Indústria 4.0; Simulation; Production; Network; Industry 4.0; CNPQ::CIENCIAS SOCIAIS APLICADAS::ADMINISTRACAO

The evolution of technology and production methods has led to revolutions in industry fields. The first three Industrial Revolution were marks of these advances, and they keep being studied after their occurrence. In 2011, at Germany, the term Industry 4.0 was created. It refers to the Fourth Industrial Revolution, which has been studied before it happens, or while it is happening, differently of the previous three. Industry 4.0 uses technologies such as Internet of Things and Cyber-Physical Systems to build smart-factories, where machines and human interact and make decision based on real time information. The interaction of these actors makes huge and complex production networks, which study is important to the advance of Industry 4.0; nevertheless, this study is too expensive in the real environment. In this context, modeling and simulation techniques can be used to allow analysis and evaluation of different production scenarios. This work had as goal the development of a software simulator for the analysis of Industry 4.0 production networks. Therefore, Design Science Research method was used. This method is used when the research aims to build constructs to solve relevant problems, based on scientific rigor and the extension of the solution to a class of problems. The simulator development began with literature review and requirements definition. After that, an Industry 4.0 production network model was created and, then, three algorithms were proposed to define nodes and paths to execute production tasks in the network. The algorithms were based on depth-first search, breadth-first search and genetic algorithm metaheuristic. Both production model and the algorithms were validated. The simulator was implemented as a software, and tests were performed to check different algorithms and network structures behaviors, as well as networks behaviors with failures. Among the three proposed algorithms, genetic algorithm obtained better results regarding to tasks execution. Besides, it was proved that the simulator can be used to evaluate different scenarios, base on production analysis in different networks configurations, as well as in the presence of failures. Then, the work achieved its goal, and it can be used in different areas of Industry 4.0 production networks study, being a theoretical framework to these networks analysis.