An End-to-End Big Data Analytics Platform for IoT-enabled Smart Factories: A Case Study of Battery Module Assembly System for Electric Vehicles

Journal article

Kahveci, S., Alkan, B., Ahmad, M. and Harrison, R. (2022). An End-to-End Big Data Analytics Platform for IoT-enabled Smart Factories: A Case Study of Battery Module Assembly System for Electric Vehicles. Journal of Manufacturing Systems. 63, pp. 214-223. https://doi.org/10.1016/j.jmsy.2022.03.010
AuthorsKahveci, S., Alkan, B., Ahmad, M. and Harrison, R.
Abstract

Within the concept of factories of the future, big data analytics systems play a critical role in supporting decision-making at various stages across enterprise processes. However, the design and deployment of industry-ready, lightweight, modular, flexible, and low-cost big data analytics solutions remains one of the main challenges towards the Industry 4.0 enabled digital transformation. This paper presents an end-to-end IoT-based big data analytics platform that consists of five interconnected layers and several components for data acquisition, integration, storage, analytics and visualisation purposes. The platform architecture benefits from state-of-the-art technologies and integrates them in a systematic and interoperable way with clear information flows. The developed platform has been deployed in an Electric Vehicle (EV) battery module smart assembly automation system designed by the Automation Systems Group (ASG) at the University of Warwick, UK. The developed proof-of-concept solution demonstrates how a wide variety of tools and methods can be orchestrated to work together aiming to support decision-making and to improve both process and product qualities in smart manufacturing environments.

KeywordsBig Data Analytics; Data Visualisation; IoT; Industry 4.0; Smart Manufacturing
Year2022
JournalJournal of Manufacturing Systems
Journal citation63, pp. 214-223
PublisherElsevier
ISSN0278-6125
Digital Object Identifier (DOI)https://doi.org/10.1016/j.jmsy.2022.03.010
Publication dates
Print31 Mar 2022
Publication process dates
Accepted13 Mar 2022
Deposited14 Mar 2022
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