Title: Internet of things in manufacturing: impact of wireless sensor networks on machine health monitoring

Authors: Victor Chang; Sasikanth Loganathan; Lewis Golightly; Qianwen Ariel Xu; Ben S.C. Liu

Addresses: Artificial Intelligence and Information Systems Research Group, School of Computing, Engineering and Digital Technologies, Teesside University, Middlesbrough TS1 3BX, UK ' Artificial Intelligence and Information Systems Research Group, School of Computing, Engineering and Digital Technologies, Teesside University, Middlesbrough TS1 3BX, UK ' Artificial Intelligence and Information Systems Research Group, School of Computing, Engineering and Digital Technologies, Teesside University, Middlesbrough TS1 3BX, UK ' Artificial Intelligence and Information Systems Research Group, School of Computing, Engineering and Digital Technologies, Teesside University, Middlesbrough TS1 3BX, UK; IBSS, Xi'an Jiaotong-Liverpool University, Suzhou 215123, China ' School of Business, Quinnipiac University, Hamden, Connecticut 06518, USA

Abstract: Digital transformation is associated with many benefits and the commonly recognised usage is machine condition monitoring. Internet of things (IoT) technologies such as radio frequency identification and wireless sensor networks (WSN) are commonly applied in different situations, but the current study primarily focuses on WSN to establish the importance of IoT in manufacturing. This study establishes the impact of IoT in manufacturing based on the impact of WSN on machine health monitoring. Both primary and secondary sources was used whereby data was obtained from the literature data in databases and existing studies. The results indicate that interconnected devices enable communication and sending alerts regarding defects and machine malfunctions. IoT helps to rectify the machine to ensure effective performance, reduce production costs, and improve safety and mass customisation. Consequently, the main benefits of IoT include faster and more informed decisions, reduced downtime, higher product quality, predictive maintenance and greater energy efficiency.

Keywords: internet of things; IoT; machine health monitoring; wireless sensor networks; WSNs; distributed processing; big data rate and throughput; mobile machine health monitoring; cloud machine health monitoring.

DOI: 10.1504/IJBIS.2023.134980

International Journal of Business Information Systems, 2023 Vol.44 No.3, pp.383 - 403

Received: 09 Sep 2020
Accepted: 02 Nov 2020
Published online: 22 Nov 2023 *

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