Estimation of Energy Consumption in Manufacturing Lines Using Machine Learning into Industry 4.0 Context
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2022-01-05
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Fabio Lima
NONOGAKI, L. K. B. Y.
CHANG, J.
Alexandre Augusto Massote
NONOGAKI, L. K. B. Y.
CHANG, J.
Alexandre Augusto Massote
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PICMET 2022 - Portland International Conference on Management of Engineering and Technology: Technology Management and Leadership in Digital Transformation - Looking Ahead to Post-COVID Era, Proceedings
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LIMA, F.; NONOGAKI, L. K. B. Y.; CHANG, J.; MASSOTE, A. A. Estimation of Energy Consumption in Manufacturing Lines Using Machine Learning into Industry 4.0 Context. PICMET 2022 - Portland International Conference on Management of Engineering and Technology: Technology Management and Leadership in Digital Transformation - Looking Ahead to Post-COVID Era, Proceedings, 2022.
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© 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.