Abstract
Markets and consequently manufacturing companies are facing an unprecedented challenge. The constant markets demand of more and more customized and personalized products combined with the recent evolution of information technologies, brought to the manufacturing world the integration of new solutions previously unimaginable in a production environment. Hence, in the last years manufacturing systems were changing and nowadays each component present in the shop floor generates a huge amount of data that is usually not used. In this paper the authors present a framework capable to deal with all this data generated from a production cell in the automotive industry and reduce the energy consumption. Firstly, it is described how the information is extracted and how the data clustering is done, then the data mining process and management are presented, together with the obtained results.
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Rocha, A.D., Tapadinhas, J.A., Flores, L., Barata Oliveira, J. (2017). Data Mining of Energy Consumption in Manufacturing Environment. In: Borangiu, T., Trentesaux, D., Thomas, A., Leitão, P., Oliveira, J. (eds) Service Orientation in Holonic and Multi-Agent Manufacturing . SOHOMA 2016. Studies in Computational Intelligence, vol 694. Springer, Cham. https://doi.org/10.1007/978-3-319-51100-9_14
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DOI: https://doi.org/10.1007/978-3-319-51100-9_14
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