Determining the impact of 5G-technology on manufacturing performance using a modified TOPSIS method
Journal article, 2021

A digital transformation is currently taking place in society, where people and things are connected to each other and the Internet. The number of connected devices is projected to be 28 Billion in 2025, and our expectations on digitalization set new requirements of mobile communication technology. To handle the increased amount of connected devices and data generated, the next generation of mobile communication technology is under deployment: 5G-technology.
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. In Press

5G-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

More information

Latest update

9/13/2021