Role of Artificial Intelligence in Circular Manufacturing: A Systematic Literature Review
Open accessAbstract
Circular Economy (CE) empowers firms (micro-level), network of firms (meso-level), cities, regions and nations (macro-level) sustainability. CE potentialities in making regenerate resources are even greater if supported by technologies, and Artificial Intelligence (AI) is gaining momentum in this regard. The extant literature presents a limited investigation of the exploitable synergies among CE and AI at the different scales of CE adoption in manufacturing, also named Circular Manufacturing (CM). Indeed, this paper entails a systematic literature review to investigate the state-of-the-art in this domain proposing future research opportunities. Among the findings, AI exploitation is advanced at micro-level, whilst the meso-level, macro-level, and the synergies among the three levels require further exploration.
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AI can support designers by suggesting initial designs for eco-friendly products or adjusting designs based on environmental parameters and/or considerations of other actors in the circular value chain.
“AI can support designers by suggesting initial designs for eco-friendly products or adjusting designs based on environmental parameters and/or considerations of other actors in the circular value chain (Acerbi et al. 2021;Gailhofer et al. 2021).”
From Artificial intelligence in support of the circular economy: ethical considerations and a path forward (2024) · cites this paper as Acerbi et al. 2021
To date, considerations of the ethical implications of using AI to achieve a transition to CE have been limited, and the potential harms from using AI for CE have not been comprehensively analysed.
“However, to date, considerations of the ethical implications of using AI to achieve a transition to CE have been limited.”
From Artificial intelligence in support of the circular economy: ethical considerations and a path forward (2024) · cites this paper as Acerbi et al. 2021
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Roberts, H., Zhang, J., Bariach, B., Cowls, J., Gilburt, B., Juneja, P., Tsamados, A., Ziosi, M., Taddeo, M., & Floridi, L. (2024) · AI & SOCIETY · doi:10.1007/s00146-022-01596-8 · Cited by 123 · see citing works
- Authors
- Acerbi, F., Forterre, D. A., & Taisch, M.
- Affiliations
- Politecnico di Milano (IT)
- Corresponding author
- Acerbi, Federica
- Forterre, Dai Andrew
- Taisch, Marco
- Venue
- IFAC-PapersOnLine
- Publisher
- Elsevier BV
- Published
- 2021
- Volume
- 54
- Issue
- 1
- Pages
- 367-372
- ISSN
- 2405-8963 (ISSN-L)
- OpenAlex
- W3214597440
- Cited by
- 57
- References
- 25
- Citations by year
- 2026: 17 · 2025: 20 · 2024: 7 · 2023: 9 · 2022: 4
- FWCI
- 0.85
- Type
- journal article
- Language
- en
- Open access
- diamond
- doi.org
- Locations
- IFAC-PapersOnLine (publishedVersion)
- Virtual Community of Pathological Anatomy (University of Castilla La Mancha) (submittedVersion, other-oa)
- Topics
- Social Sciences › Business, Management and Accounting › Strategy and Management › Sustainable Supply Chain Management
- Social Sciences › Decision Sciences › Management Science and Operations Research › Impact of AI and Big Data on Business and Society
- Physical Sciences › Engineering › Industrial and Manufacturing Engineering › Sustainable Industrial Ecology
- Keywords
- artificial intelligence, circular economy, circular manufacturing, resource regeneration, sustainable manufacturing, future research directions
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