Determining the impact of 5G-technology on manufacturing performance using a modified TOPSIS method
Journal article, 2022
The manufacturing industry follows the digital transformation, aiming for digitalized manufacturing with competitive and sustainable production systems.
5G-technology meets the connectivity requirements in digitalized manufacturing, with low latency, high data rates, and high reliability. Despite these technological benefits, the question remains: Why should the manufacturing industry invest in 5G-technology?
This study aims to determine the impact of 5G-technology on manufacturing performance; based on a mixed-methods approach including a modified TOPSIS method to ensure robustness of the results. The results show that 5 G-technology will mainly impact productivity, maintenance performance, and flexibility. By linking 5G-technology to the performance of the manufacturing system, instead of focusing on network performance, the benefits of using 5G-technology in manufacturing become clear, and can thus facilitate investment and deployment of 5G-technology in the manufacturing industry.
quantitative methods
performance analysis
information technology
manufacturing information systems
New technology management
Author
Camilla Lundgren
Chalmers, Industrial and Materials Science, Production Systems
Ebru Turanoglu Bekar
Chalmers, Industrial and Materials Science, Production Systems
Maja Bärring
Chalmers, Industrial and Materials Science, Production Systems
Johan Stahre
Chalmers, Industrial and Materials Science, Production Systems
Anders Skoogh
Chalmers, Industrial and Materials Science, Production Systems
Björn Johansson
Chalmers, Industrial and Materials Science, Production Systems
R. Hedman
Volvo Group
International Journal of Computer Integrated Manufacturing
0951-192X (ISSN) 1362-3052 (eISSN)
Vol. 35 1 69-905G-Enabled Manufacturing II (5GEMII)
VINNOVA (2018-02820), 2018-06-21 -- 2019-09-01.
Subject Categories
Production Engineering, Human Work Science and Ergonomics
Other Mechanical Engineering
Computer Science
Areas of Advance
Production
DOI
10.1080/0951192X.2021.1972465