A digital twin model for enhancing performance measurement in assembly lines

Papanagnou, C ORCID: https://orcid.org/0000-0002-5889-4209 2019, 'A digital twin model for enhancing performance measurement in assembly lines' , in: Digital Twin Technologies and Smart Cities , Internet of Things , Springer, pp. 53-66.

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Dynamic manufacturing processes are characterized by a lack of coordination, complexity and sheer volumes of data. Digital transformation technologies offer the manufacturers the capability to better monitor and control both assets and production. This provides also an ever-improving ability to investigate new products and production concepts in the virtual world while optimizing future production with IoT-captured data from different devices and shop floor machine centres. In this study, a digital twin is presented for an assembly line, where IoT-captured data is fed back into the digital twin enabling manufacturers to interface, analyse and measure the performance in real-time of a manufacturing process. The digital twin concept is then applied to an assembly production plan found in the automotive industry, where actual data is considered to analyse how the digital duplicate can be used to review activities and improve productivity within all production shifts.

Item Type: Book Section
Editors: Farsi, M, Daneshkhah, A, Hosseinian-Far, A and Jahankhani, H
Schools: Schools > Salford Business School > Salford Business School Research Centre
Journal or Publication Title: Digital Twin Technologies and Smart Cities
Publisher: Springer
Series Name: Internet of Things
ISBN: 9783030187316 (print); 9783030187323 (ebk.)
Related URLs:
Depositing User: Dr Christos Papanagnou
Date Deposited: 24 Feb 2020 09:34
Last Modified: 16 Feb 2022 04:05
URI: https://usir.salford.ac.uk/id/eprint/56484

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