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Cited by 47Digital Transformation in IndustryApplied Advanced TechnologiesImpact of AI and Big Data on Business and Society

Sustainability Requirements of Digital Twin-Based Systems: A Meta Systematic Literature Review

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Carvalho, Rui, da Silva, Alberto Rodrigues·2021·Applied Sciences
DOI 10.3390/app11125519
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Abstract

Sustainable development was defined by the UN in 1987 as development that meets the needs of the present without compromising the ability of future generations to meet their own needs, and this is a core concept in this paper. This work acknowledges the three dimensions of sustainability, i.e., economic, social, and environmental, but its focus is on this last one. A digital twin (DT) is frequently described as a physical entity with a virtual counterpart, and the data, connections between the two, implying the existence of connectors and blocks for efficient and effective data communication. This paper provides a meta systematic literature review (SLR) (i.e., an SLR of SLRs) regarding the sustainability requirements of DT-based systems. Numerous papers on the subject of DT were also selected because they cited the analyzed SLRs and were considered relevant to the purposes of this research. From the selection and analysis of 29 papers, several limitations and challenges were identified: the perceived benefits of DTs are not clearly understood; DTs across the product life cycle or the DT life cycle are not sufficiently studied; it is not clear how DTs can contribute to reducing costs or supporting decision-making; technical implementation of DTs must be improved and better integrated in the context of the IoT; the level of fidelity of DTs is not entirely evaluated in terms of their parameters, accuracy, and level of abstraction; and the ownership of data stored within DTs should be better understood. Furthermore, from our research, it was not possible to find a paper discussing DTs only in regard to environmental sustainability.

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  • It is difficult for designers to mimic or model behaviors that cannot be explained by numbers, such as social conflicts, sociopolitical issues, social inequality and environmental sustainability.

    “It is difficult for designers to mimic or model behaviors that cannot be explained by numbers.Such is the case of social conflicts, sociopolitical issues, social inequality [79] and environmental sustainability [80].”

    From Digital Twin Technology Challenges and Applications: A Comprehensive Review (2022) · cites this paper as [80]

    Citation [80] is attached to environmental sustainability, not the social issues cited to [79]. The Discussion says there is no integrated approach to understanding how digital twins can create environmental sustainability and that evaluating environmental costs adds work and complexity. It does not say environmental sustainability cannot be explained by numbers or that designers therefore cannot model it. (LLM, conf=0.78)

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Cited by

Sorted by citations

Authors
Carvalho, R., & da Silva, A. R.
Affiliations
  • University of Lisbon (PT)
  • INESC-ID, Instituto Superior Técnico, Universidade de Lisboa, 1000-029 Lisboa, Portugal
Corresponding author
Carvalho, Rui
ORCID
da Silva, Alberto Rodrigues
Venue
Applied Sciences
Publisher
MDPI AG
Published
2021-06-15
Volume
11
Issue
12
Pages
5519
ISSN
2076-3417 (ISSN-L)
DOI
10.3390/app11125519
OpenAlex
W3171674920
Cited by
47
References
1
Citations by year
2026: 4 · 2025: 6 · 2024: 13 · 2023: 10 · 2022: 12 · 2021: 2
FWCI
0.86
Type
journal article
Language
en
Open access
Licence
Locations
  • Applied Sciences (publishedVersion, cc-by)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
Fundação para a Ciência e a Tecnologia (UIDB/50021/2020)
Topics
  • Physical Sciences › Engineering › Industrial and Manufacturing Engineering › Digital Transformation in Industry
  • Physical Sciences › Engineering › Industrial and Manufacturing Engineering › Applied Advanced Technologies
  • Social Sciences › Decision Sciences › Management Science and Operations Research › Impact of AI and Big Data on Business and Society
Keywords
digital twin, sustainability requirements, environmental sustainability, sustainable development, product life cycle, Internet of Things, data fidelity, data ownership, decision support, cost reduction

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