Towards a Digital Human Representation in an Industrial Digital Twin

8 Pages Posted: 23 Oct 2020

See all articles by Dedy Ariansyah

Dedy Ariansyah

Cranfield University

Achim Buerkle

Loughborough University

Ali Al-Yacoub

Loughborough University

Melanie Zimmer

Loughborough University

John Ahmet Erkoyuncu

Cranfield University

Niels Lohse

Loughborough University

Date Written: October 23, 2020

Abstract

Digital twins (DTs) have demonstrated their abilities to integrate sensor data, current state information, and the information about the environment in virtual models. While previous approaches have focused on creating DTs for mainly machines and workstations, a small number of studies have considered human performance when designing the DT system, which leads to a deficiency in overall system performance. The absence of the human integrated-DT framework may decelerate human integration in industrial DT, and thus, disregards the crucial role of the human in the industry of the future. This paper presents a framework for digital human representation in an industrial DT to continuously monitor and to analyse the human operational state and behaviour. Thereby, the DT enables decision-makers to allocate tasks on the shop floor taking into account the human physical and mental status. A sample case showed how a human muscle activity monitoring system could be integrated with the DT based on the developed framework to account for the operator’s muscular fatigue or physical exhaustion for decision-making. This included the use of Artificial Intelligence (AI) to interpret the human activity related data using wearable sensors, such as electromyography (EMG). Future research is proposed to harness human data from a richer variety of sensors as control parameters for production operation and improved decision-making.

Keywords: Digital Twin; Digital Human Representation; Electromyography; Machine Learning, Incremental Learning

Suggested Citation

Ariansyah, Dedy and Buerkle, Achim and Al-Yacoub, Ali and Zimmer, Melanie and Erkoyuncu, John Ahmet and Lohse, Niels, Towards a Digital Human Representation in an Industrial Digital Twin (October 23, 2020). TESConf 2020 - 9th International Conference on Through-life Engineering Services, Available at SSRN: https://ssrn.com/abstract=3717733 or http://dx.doi.org/10.2139/ssrn.3717733

Dedy Ariansyah (Contact Author)

Cranfield University ( email )

Cranfield
Bedfordshire MK43 OAL, MK43 0AL
United Kingdom

Achim Buerkle

Loughborough University

Ashby Road
Nottingham NG1 4BU
Great Britain

Ali Al-Yacoub

Loughborough University

Ashby Road
Nottingham NG1 4BU
Great Britain

Melanie Zimmer

Loughborough University

Ashby Road
Nottingham NG1 4BU
Great Britain

John Ahmet Erkoyuncu

Cranfield University ( email )

Cranfield
Bedfordshire MK43 OAL, MK43 0AL
United Kingdom

Niels Lohse

Loughborough University

Ashby Road
Nottingham NG1 4BU
Great Britain

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