Engenharia de Produção
URI permanente desta comunidadehttps://repositorio.fei.edu.br/handle/FEI/19
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2 resultados
Resultados da Pesquisa
- Estimation of Energy Consumption in Manufacturing Lines Using Machine Learning into Industry 4.0 Context(2022-01-05) Fabio Lima; NONOGAKI, L. K. B. Y.; CHANG, J.; Alexandre Augusto Massote© 2022 PICMET.This paper deals with the simulation of production lines focusing on opportunities of reducing the energy consumption. The simulation of systems is one of the pillars of the so-called Industry 4.0. It has been used a digital manufacturing software, which allow the creation of digital twins, to carry out the models. Once the model has been created and validated, a machine learning approach, more specifically a Neural Network was trained to estimate the energy consumption of the line. The estimation of the energy consumption allows to use this variable to take decisions of the production scheduling. Moreover, the neural network package is embedded into the digital manufacturing software which provides more flexibility to solve the problem using one single software tool. The results validate the proposal, and, for future work, the effective creation of the digital twin should be performed.
- Innovative laboratory model based on partnerships and active learning(2017-12-12) Rodrigo Maia; Alexandre Augusto Massote; Fabio Lima© 2017 IEEE.The advent of the internet of things and industry 4.0 bring new paradigms that tend to affect the way of organizing several human activities, among them the production processes that are ruled by production and human work on a large scale in the production lines. Therefore, it is inevitable to think of how to prepare students for this new, oncoming reality, since these students will have to deal with a society where usual jobs will no longer be available. This paper presents the initiative of two laboratories developed to prepare students in engineering and computer science to deal with the Internet of Things (IOT) and industry 4.0 (I4.0) subjects. These laboratories were developed in partnership with companies: the first one of Digital Manufacturing (DM) and the second one of IOT, and the integrated work of these laboratories approaches with the students the concepts of I4.0 or advanced manufacturing. The collaborative environment between academia and companies, as well as the joint work of two laboratories, allowed graduate students to develop discussions and works that integrate issues of society and companies with academic studies.