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Human-centered cyber-physical systems in manufacturing industry: a systematic search and review

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Anuradha Colombathanthri
Anuradha Colombathanthri
Anuradha Colombathanthri
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Walid Jomaa at Polytechnique Montréal
Walid Jomaa
Yuvin Adnarain Chinniah
Yuvin Adnarain Chinniah
Yuvin Adnarain Chinniah
  • This person is not on ResearchGate, or hasn't claimed this research yet.
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Abstract and Figures

Industry 4.0 brings smartness to manufacturing systems through Cyber-Physical Systems (CPS), Digital Twins (DT), and the Internet of Things. Going a step further, Industry 5.0 seeks to achieve these modern manufacturing industry goals by integrating the precision of robots/cobots with human creativity by establishing human-centered CPS. Hence, it is crucial to have a good understanding of key technological adjustments and how they are being incorporated for sustaining human-centricity, resilience, and reconfigurability in CPS-based workcells. This systematic search and review addresses this central research question. The review was based on carefully established systematic search and elimination/inclusion criteria. After a gradual filtering process as elaborated in this paper, 88 related articles were deeply analyzed to arrive at the conclusions. The significance of this review is that it analyzes research works based on CPS platforms to identify how the technicalities at each level of the CPS establishment can support sustaining human-centered applications. It was identified that novel approaches are obtained by adjusting the decision-making algorithms of the CPS. An overuse of virtual reality methods was noticed. There is a requirement for improved and reliable biosensing applications. Parallel improvements in other industries such as interoperability and cyber-security can provide better support for the changes in the focused industry. These findings will be useful for future research trends in the manufacturing industry.
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Vol.:(0123456789)
https://doi.org/10.1007/s00170-024-14959-w
CRITICAL REVIEW
Human‑centered cyber‑physical systems inmanufacturing industry:
asystematic search andreview
AnuradhaColombathanthri1 · WalidJomaa1· YuvinAdnarainChinniah1
Received: 2 September 2024 / Accepted: 19 December 2024
© The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2025
Abstract
Industry 4.0 brings smartness to manufacturing systems through Cyber-Physical Systems (CPS), Digital Twins (DT), and
the Internet of Things. Going a step further, Industry 5.0 seeks to achieve these modern manufacturing industry goals by
integrating the precision of robots/cobots with human creativity by establishing human-centered CPS. Hence, it is crucial
to have a good understanding of key technological adjustments and how they are being incorporated for sustaining human-
centricity, resilience, and reconfigurability in CPS-based workcells. This systematic search and review addresses this central
research question. The review was based on carefully established systematic search and elimination/inclusion criteria. After
a gradual filtering process as elaborated in this paper, 88 related articles were deeply analyzed to arrive at the conclusions.
The significance of this review is that it analyzes research works based on CPS platforms to identify how the technicalities
at each level of the CPS establishment can support sustaining human-centered applications. It was identified that novel
approaches are obtained by adjusting the decision-making algorithms of the CPS. An overuse of virtual reality methods was
noticed. There is a requirement for improved and reliable biosensing applications. Parallel improvements in other industries
such as interoperability and cyber-security can provide better support for the changes in the focused industry. These findings
will be useful for future research trends in the manufacturing industry.
Keywords Digital Twins· Cyber-Physical Systems· Biofeedback controlling· Human safety· Manufacturing industry
1 Introduction
To tackle the manufacturing industry-specific challenges
such as productivity improvement, dynamic reconfigura-
tion, standardization, and use of information technology,
Industry 4.0 (I 4.0) has been introduced into the manufac-
turing industry since 2011 [1]. The I 4.0 is a consolidation of
nine technologies namely, big data analytics, cybersecurity,
Industrial Internet of Things (IIoT), simulation, augmented
reality, additive manufacturing, advanced robotics, cloud
services, and horizontal and vertical system integration [2].
Cyber-Physical Systems (CPS) and Digital Twins (DT) are
considered to be the prominent concepts that can be used for
this consolidation of technologies [3, 4].
CPS integrates the system in physical space with its digital
counterpart in cyberspace to monitor real-time data and to pre-
dict the operation accordingly, which can provide reconfigur-
ability to the system [1]. As [5] described, CPS is a 5C-level
architecture (connection, conversion, configuration, cognition,
and cyber). Digital Twin is positioned at the third C level of
this architecture as a tool for real-time control of the machine.
Highlights
• A systematic search and review targeting the manufacturing
industry
• Identification of state-of-the-art concepts in workcells based on
Cyber-Physical Systems (CPS) and Digital Twins (DT)
• Technical approaches to include human-centricity, resilience,
and reconfigurability in all layers of a CPS
• Future research applications to advance the field of human-
centric CPS
• Analysis of biofeedback controlling in the CPS-based
manufacturing workcells
* Anuradha Colombathanthri
anuradha.colombathanthri@polymtl.ca
Walid Jomaa
walid.jomaa@polymtl.ca
Yuvin Adnarain Chinniah
yuvin.chinniah@polymtl.ca
1 Department ofMathematics & Industrial Engineering,
Polytechnique Montréal, Montréal, Canada
The International Journal of Advanced Manufacturing Technology (2025) 136:2107–2141
/ Published online: 15 January 2025
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
ResearchGate has not been able to resolve any citations for this publication.
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