Author(s): Santos, Maribel Yasmina ; Oliveira e Sá, Jorge ; Andrade, Carina ; Vale Lima, Francisca ; Costa, Eduarda ; Costa, Carlos ; Martinho, Bruno ; Galvão, João
Date: 2017
Persistent ID: http://hdl.handle.net/1822/46853
Origin: RepositóriUM - Universidade do Minho
Project/scholarship: info:eu-repo/grantAgreement/FCT/5876/147280/PT;
Subject(s): Big Data; Big Data Analytics; Big Data Architecture; Industry 4.0; Bosch; Science & Technology
People, devices, infrastructures and sensors can constantly communicate exchanging data and generating new data that trace many of these exchanges. This leads to vast volumes of data collected at ever increasing velocities and of different variety, a phenomenon currently known as Big Data. In particular, recent developments in Information and Communications Technologies are pushing the fourth industrial revolution, Industry 4.0, being data generated by several sources like machine controllers, sensors, manufacturing systems, among others. Joining volume, variety and velocity of data, 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. Thereby, this paper addresses this key challenge, proposing and implementing a Big Data Analytics architecture, using a multinational organisation (Bosch Car Multimedia – Braga) as a case study. In this work, all the data lifecycle, from collection to analysis, is handled, taking into consideration the different data processing speeds that can exist in the real environment of a factory (batch or stream).
This work has been supported by COMPETE: POCI-01-0145-FEDER007043 and FCT (Fundação para a Ciência e Tecnologia) within the Project Scope: UID/CEC/00319/2013, and by Portugal Incentive System for Research and Technological Development, Project in copromotion no 002814/2015 (iFACTORY 2015–2018). Some of the figures in this paper use icons made by Freepik, from www.flaticon.com.
info:eu-repo/semantics/acceptedVersion
