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A cloud-based framework for shop floor big data management and elastic computing analytics
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DOI：10.1016/j.compind.2019.03.005.png)
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Abstract
En 中文
Advanced digitalization together with the rise of disruptive Internet technologies are key enablers of a fundamental paradigm shift observed in industrial production. This is known as the fourth industrial revolution (Industry 4.0) which proposes the integration of the new generation of ICT solutions for the monitoring, adaptation, simulation, and optimisation of factories. With the democratization of sensors and actuators, factories and machine tools can now be sensorized and the data generated by these devices can be exploited, for instance, to optimise the utilization of the machines as well as their operation and maintenance. However, analyzing the vast amount of generated data is resource demanding both in terms of computing power and network bandwidth, thus requiring highly scalable solutions. This paper presents a novel big data approach and analytics framework for the management and analysis of machine generated data in the cloud. It brings together standard open source technologies and the exploitation of elastic computing, which, as a whole, can be adapted to and deployed on different cloud computing platforms. This enables reducing infrastructure costs, minimizing deployment difficulty and providing on-demand access to a virtually infinite set of computing power, storage and network resources. (C) 2019 Elsevier B.V. All rights reserved.
Keywords:
Industry 4.0
Cyber physical systems
Big data
Cloud-based data collection
Cloud-based analytics
Elastic computing
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