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2018 | OriginalPaper | Buchkapitel

Machine Learning Predictive Model for Industry 4.0

verfasst von : Inés Sittón Candanedo, Elena Hernández Nieves, Sara Rodríguez González, M. Teresa Santos Martín, Alfonso González Briones

Erschienen in: Knowledge Management in Organizations

Verlag: Springer International Publishing

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Abstract

In an Industry 4.0 environment, the data generated by sensors networks requires machine learning and data analysis techniques. Thus, organizations face both new opportunities and challenges, one of them is predictive analysis using computer tools capable of detecting patterns in the analyzed data from the same rules that can be used to formulate predictions. The Heating, Ventilation and Air Conditioning Systems (HVAC) control in an important number of industries: indoor climate, air’s temperature, humidity and pressure, creating an optimal production environment. In accordance, a case study is presented, in it a HVAC dataset was used to test the performance of the equipment and observe whether it maintains temperatures in an optimal range. The aim of this paper is making use of machine learning algorithms for the design of predictive models in the Industry 4.0 environment, using the previously mentioned dataset.

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Titel: Machine Learning Predictive Model for Industry 4.0
verfasst von: Inés Sittón Candanedo
Elena Hernández Nieves
Sara Rodríguez González
M. Teresa Santos Martín
Alfonso González Briones
Verlag: Springer International Publishing
Buch: Knowledge Management in Organizations
Print ISBN: 978-3-319-95203-1

Electronic ISBN: 978-3-319-95204-8

Copyright-Jahr: 2018
DOI: https://doi.org/10.1007/978-3-319-95204-8_42

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