Título:
Machine learning for predictive model for Industry 4.0 environment.
Machine learning for predictive model for Industry 4.0 environment.
Autores:
Sittón Candanedo, Inés; Hernández Nieves, Elena; Rodríguez González, Sara; Santos Martín, María T.; González Briones, Alfonso
Libro:
Knowledge Management in Organizations. KMO 2018.. Communications in Computer and Information Science. Volumen 877, pp. 501-510.
Fecha de Publicación:
July 2018
ISBN:
978-3-319-95204-8
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.