The DOI matches its Crossref record.
Industry 4.0 and Industry 5.0—Inception, conception and perception
Open accessAbstract
Industry 4.0, an initiative from Germany, has become a globally adopted term in the past decade. Many countries have introduced similar strategic initiatives, and a considerable research effort has been spent on developing and implementing some of the Industry 4.0 technologies. At the ten-year mark of the introduction of Industry 4.0, the European Commission announced Industry 5.0. Industry 4.0 is considered to be technology-driven, whereas Industry 5.0 is value-driven. The co-existence of two Industrial Revolutions invites questions and hence demands discussions and clarifications. We have elected to use five of these questions to structure our arguments and tried to be unbiased for the selection of the sources of information and for the discussions around the key issues. It is our intention that this article will spark and encourage continued debate and discussion around these topics.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
No references could be resolved yet.
Research works printed but not linked: 18
- Vogel-Heuser, 2016, Guest editorial: Industry 4.0–prerequisites and visions, IEEE Trans Autom Sci Eng, 13
- Zuehlke, 2010, SmartFactory—towards a factory-of-things, Annu Rev Control, 34, 129, 10.1016/j.arcontrol.2010.02.008 · DOI · Paper page
- Lu, 2020, Smart manufacturing process and system automation – a critical review of the standards and envisioned scenarios, J Manuf Syst, 56, 312, 10.1016/j.jmsy.2020.06.010 · DOI · Paper page
- Wang, 2016, Towards smart factory for Industry 4.0: a self-organized multi-agent system with big data based feedback and coordination, Comput Netw, 101, 158, 10.1016/j.comnet.2015.12.017 · DOI · Paper page
- Zhong, 2017, Intelligent manufacturing in the context of Industry 4.0: a review, Engineering, 3, 616, 10.1016/J.ENG.2017.05.015 · DOI · Paper page
- Longo, 2020, Value-oriented and ethical technology engineering in Industry 5.0: a human-centric perspective for the design of the factory of the future, Appl Sci, 10, 4182, 10.3390/app10124182 · DOI · Paper page
- Bednar, 2020, Socio-technical perspectives on smart working: creating meaningful and sustainable systems, Inf Syst Front, 22, 281, 10.1007/s10796-019-09921-1 · DOI · Paper page
- Liu, 2017, Augmented reality-assisted intelligent window for cyber-physical machine tools, J Manuf Syst, 44, 280, 10.1016/j.jmsy.2017.04.008 · DOI
- Zhu, 2019, Visualisation of the digital twin data in manufacturing by using augmented reality, Procedia CIRP, 81, 898, 10.1016/j.procir.2019.03.223 · DOI · Paper page
- Villani, 2020, The INCLUSIVE system: a general framework for adaptive industrial automation, IEEE Trans Autom Sci Eng
- Flores, 2020, Human Capital 4.0: a workforce competence typology for Industry 4.0, J Manuf Technol Manag, 31, 687, 10.1108/JMTM-08-2019-0309 · DOI · Paper page
- Demir, 2019, Industry 5.0 and human-robot co-working, Procedia Comput Sci, 158, 688, 10.1016/j.procs.2019.09.104 · DOI · Paper page
- Longo, 2020, Value-oriented and ethical technology engineering in Industry 5.0: a human-centric perspective for the design of the factory of the future, Appl Sci, 10, 4182, 10.3390/app10124182 · DOI · Paper page
- Nahavandi, 2019, Industry 5.0—a human-centric solution, Sustainability, 11, 4371, 10.3390/su11164371 · DOI · Paper page
- Lu, 2021, Humans are not machines—anthropocentric human–machine symbiosis for ultra-flexible smart manufacturing, Engineering, 7, 734, 10.1016/j.eng.2020.09.018 · DOI
- Huang, 2021, Digital technologies and automation: the human and eco-centered foundations for the factory of the future [TC Spotlight], IEEE Robot Autom Mag, 28, 174, 10.1109/MRA.2021.3095732 · doi:10.1109/mra.2021.3095732
- Agreement, 2015, vol. 4
- Talberth, 2017, Genuine progress indicator 2.0: pilot accounts for the US, Maryland, and City of Baltimore 2012–2014, Ecol Econ, 142, 1, 10.1016/j.ecolecon.2017.06.012 · DOI
Cited by
AI revolutionizing industries worldwide: A comprehensive overview of its diverse applications
Rashid, A. B., & Kausik, M. A. K. (2024) · Hybrid Advances · doi:10.1016/j.hybadv.2024.100277 · Cited by 764
The digitization of agricultural industry – a systematic literature review on agriculture 4.0
Abbasi, R., Martinez, P., & Ahmad, R. (2022) · Smart Agricultural Technology · doi:10.1016/j.atech.2022.100042 · Cited by 531
ESG and Industry 5.0: The role of technologies in enhancing ESG disclosure
Asif, M., Searcy, C., & Castka, P. (2023) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2023.122806 · Cited by 325
Pregnolato, M., Gunner, S., Voyagaki, E., De Risi, R., Carhart, N., Gavriel, G., Tully, P., Tryfonas, T., Macdonald, J., & Taylor, C. (2022) · Automation in Construction · doi:10.1016/j.autcon.2022.104421 · Cited by 253
Maturity Assessment for Industry 5.0: A Review of Existing Maturity Models
Hein-Pensel, F., Winkler, H., Brückner, A., Wölke, M., Jabs, I., Mayan, I. J., Kirschenbaum, A., Friedrich, J., & Zinke-Wehlmann, C. (2023) · Journal of Manufacturing Systems · doi:10.1016/j.jmsy.2022.12.009 · Cited by 215
Metadata
- Authors
- Xu, X., Lu, Y., Vogel-Heuser, B., & Wang, L.
- Venue
- Journal of Manufacturing Systems
- Publisher
- Elsevier BV
- Published
- 2021-10
- Volume
- 61
- Pages
- 530-535
- ISSN
- 0278-6125 (ISSN-L)
- OpenAlex
- W3205172848
- Cited by
- 2,557
- References
- 0
- FWCI
- 178.25
- Type
- journal article
- Language
- en
- Open access
- hybrid
- Licence
- www.elsevier.com/tdm/userlicense/1.0/ (tdm)
- www.elsevier.com/legal/tdmrep-license (tdm)
- creativecommons.org/licenses/by-nc-nd/4.0/ (vor, 17 d)
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Industry 4.0 and Industry 5.0—Inception, conception and perception. https://app.cochat.ai/papers/10.1016/j.jmsy.2021.10.006
- The paper
- Xu, X., Lu, Y., Vogel-Heuser, B., & Wang, L. (2021). Industry 4.0 and Industry 5.0—Inception, conception and perception. Journal of Manufacturing Systems. https://doi.org/10.1016/j.jmsy.2021.10.006
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.