A Big Data Analytics Architecture for Industry 4.0

• Published in: Advances in intelligent systems and computing Vol. 570; pp. 175 - 184
• Main Authors: Santos, Maribel Yasmina, Sá, Jorge Oliveira e, Costa, Carlos, Galvão, João, Andrade, Carina, Martinho, Bruno, Lima, Francisca Vale, Costa, Eduarda
• Format: Book Chapter Conference Proceeding
• Language: English
• Published: Switzerland Springer International Publishing AG 2017; Springer Verlag; Springer International Publishing
• Series: Advances in Intelligent Systems and Computing
• Subjects: Artificial intelligence; Big Data; Big Data Analytics; Big Data Architecture; Industry 4.0
• ISBN: 9783319565378; 3319565370
• ISSN: 2194-5357; 2194-5365; 2194-5365
• DOI: 10.1007/978-3-319-56538-5_19

In an era in which people, devices, infrastructures and sensors can constantly communicate exchanging data and, also, generating new data that traces many of these exchanges, vast volumes of data is generated giving the context for the emergence of the Big Data concept. In particular, recent devel‐ opments in Information and Communications Technology (ICT) are pushing the fourth industrial revolution, Industry 4.0, being data generated by several sources like machine controllers, sensors, manufacturing systems, among others. Joining the volume and variety of data, arriving at high velocity, with Industry 4.0, makes the opportunity to enhance sustainable innovation in the Factories of the future. In this, the collection, integration, storage, processing and analysis of data is a key challenge, being Big Data systems needed to link all the entities and data needs of the factory. In this context, this paper proposes a Big Data Analytics architecture that includes layers dedicated to deal with all data needs, from collec‐ tion to analysis and distribution.