State of Industry 5.0—Analysis and Identification of Current Research Trends
Open accessAbstract
The term Industry 4.0, coined to be the fourth industrial revolution, refers to a higher level of automation for operational productivity and efficiency by connecting virtual and physical worlds in an industry. With Industry 4.0 being unable to address and meet increased drive of personalization, the term Industry 5.0 was coined for addressing personalized manufacturing and empowering humans in manufacturing processes. The onset of the term Industry 5.0 is observed to have various views of how it is defined and what constitutes the reconciliation between humans and machines. This serves as the motivation of this paper in identifying and analyzing the various themes and research trends of what Industry 5.0 is using text mining tools and techniques. Toward this, the abstracts of 196 published papers based on the keyword “Industry 5.0” search in IEEE, science direct and MDPI data bases were extracted. Data cleaning and preprocessing were performed for further analysis to apply text mining techniques of key terms extraction and frequency analysis. Further topic mining i.e., unsupervised machine learning method was used for exploring the data. It is observed that the terms artificial intelligence (AI), big data, supply chain, digital transformation, machine learning, internet of things (IoT), are among the most often used and among several enablers that have been identified by researchers to drive Industry 5.0. Five major themes of Industry 5.0 addressing, supply chain evaluation and optimization, enterprise innovation and digitization, smart and sustainable manufacturing, transformation driven by IoT, AI, and Big Data, and Human-machine connectivity were classified among the published literature, highlighting the research themes that can be further explored. It is observed that the theme of Industry 5.0 as a gateway towards human machine connectivity and co-existence is gaining more interest among the research community in the recent years.
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Implementation of these technologies elevates the level of broadly applied automation to multiple domains of human activity, building an ecosystem that will extend sustainability to other domains - environmental, social and political.
“The Implementation of these technologies elevate the level of broadly applied automation to multiple domains of human activity, building an ecosystem that will extend sustainability to other domains -environmental, social and political [209].”
From SCADA Systems With Focus on Continuous Manufacturing and Steel Industry: A Survey on Architectures, Standards, Challenges and Industry 5.0 (2022) · cites this paper as [209]
The Introduction (page unavailable) links Industry 5.0 technologies to environmental stewardship and social benefit, while §3.1 describes a predicted digital ecosystem and better automation in manufacturing. The paper does not establish that implementation will broadly automate multiple domains of human activity or extend sustainability to the political domain. (LLM, conf=0.83)
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Cites
Industry 5.0: A survey on enabling technologies and potential applications
Maddikunta, P. K. R., Pham, Q.-V., B, P., Deepa, N., Dev, K., Gadekallu, T. R., Ruby, R., & Liyanage, M. (2022) · Journal of Industrial Information Integration · doi:10.1016/j.jii.2021.100257 · Cited by 1,890 · see citing works
Latent Dirichlet allocation (LDA) and topic modeling: models, applications, a survey
Jelodar, H., Wang, Y., Yuan, C., Feng, X., Jiang, X.-H., Li, Y., & Zhao, L. (2017) · Multimedia tools and applications · doi:10.1007/s11042-018-6894-4 · Cited by 1,875 · see citing works
Industry 5.0—A Human-Centric Solution
Nahavandi, S. (2019) · Sustainability · doi:10.3390/su11164371 · Cited by 1,718 · see citing works
Vaidya, S., Ambad, P., & Bhosle, S. (2018) · Procedia Manufacturing · doi:10.1016/j.promfg.2018.02.034 · Cited by 1,352 · see citing works
Industry 5.0 and Human-Robot Co-working
Demir, K. A., Döven, G., & Sezen, B. (2019) · Procedia Computer Science · doi:10.1016/j.procs.2019.09.104 · Cited by 749 · see citing works
Digital transformation of industrial businesses: A dynamic capability approach
Ghosh, S., Hughes, M., Hodgkinson, I. R., & Hughes, P. (2021) · Technovation · doi:10.1016/j.technovation.2021.102414 · Cited by 581 · see citing works
Beautiful and Functional: A Review of Biomimetic Design in Additive Manufacturing
du Plessis, A., Broeckhoven, C., Yadroitsava, I., Yadroitsev, I., Hands, C. H., Kunju, R., & Bhate, D. (2019) · Additive Manufacturing · doi:10.1016/j.addma.2019.03.033 · Cited by 448 · see citing works
Fraga‐Lamas, P., Lopes, S. I., & Fernández‐Caramés, T. M. (2021) · Sensors · doi:10.3390/s21175745 · Cited by 434 · see citing works
An overview of topic modeling and its current applications in bioinformatics
Liu, L., Tang, L., Dong, W., et al. (2016) · SpringerPlus · doi:10.1186/s40064-016-3252-8 · Cited by 412 · see citing works
Ghobakhloo, M., Fathi, M., Iranmanesh, M., Maroufkhani, P., & Morales, M. E. (2021) · Journal of Cleaner Production · doi:10.1016/j.jclepro.2021.127052 · Cited by 357 · see citing works
Innovation in the Era of IoT and Industry 5.0: Absolute Innovation Management (AIM) Framework
Aslam, F., Aimin, W., Li, M., & Rehman, K. U. (2020) · Information · doi:10.3390/info11020124 · Cited by 356 · see citing works
Mbunge, E., Muchemwa, B., Jiyane, S., & Batani, J. (2021) · Global Health Journal · doi:10.1016/j.glohj.2021.11.008 · Cited by 352 · see citing works
Towards The Resilient Operator 5.0: The Future of Work in Smart Resilient Manufacturing Systems
Romero, D., & Stahre, J. (2021) · Procedia CIRP · doi:10.1016/j.procir.2021.11.183 · Cited by 337 · see citing works
Christian, H., Agus, M., & Suhartono, D. (2016) · ComTech Computer Mathematics and Engineering Applications · doi:10.21512/comtech.v7i4.3746 · Cited by 300 · see citing works
The internet of things security: A survey encompassing unexplored areas and new insights
Omolara, A. E., Alabdulatif, A., Abiodun, O. I., Alawida, M., Alabdulatif, A., Alshoura, W. H., & Arshad, H. (2021) · Computers & Security · doi:10.1016/j.cose.2021.102494 · Cited by 294 · see citing works
Welbers, K., van Atteveldt, W., & Benoit, K. R. (2017) · Communication Methods and Measures · doi:10.1080/19312458.2017.1387238 · Cited by 291 · see citing works
Systematic review of smart health monitoring using deep learning and Artificial intelligence
Sujith, A. V. L. N., Sajja, G. S., Mahalakshmi, V. J., Nuhmani, S., & Prasanalakshmi, B. (2021) · Neuroscience Informatics · doi:10.1016/j.neuri.2021.100028 · Cited by 251 · see citing works
Text Mining for Big Data Analysis in Financial Sector: A Literature Review
Bach, M. P., Krstić, Ž., Seljan, S., & Turulja, L. (2019) · Sustainability · doi:10.3390/su11051277 · Cited by 235 · see citing works
Sustainable and Smart Manufacturing: An Integrated Approach
Abubakr, M., Abbas, A. T. M., Tomaz, Í. D. V., Soliman, M. S., Luqman, M., & Hegab, H. A. (2020) · Sustainability · doi:10.3390/su12062280 · Cited by 214 · see citing works
Sazvar, Z., Tafakkori, K., Oladzad, N., et al. (2021) · Computers & Industrial Engineering · doi:10.1016/j.cie.2021.107406 · Cited by 188 · see citing works
Frederico, G. F. (2021) · Logistics · doi:10.3390/logistics5030049 · Cited by 176 · see citing works
Vrchota, J., Řehoř, P., Maříková, M., & Pech, M. (2020) · Sustainability · doi:10.3390/su13010281 · Cited by 164 · see citing works
Coupry, C., Noblecourt, S., Richard, P., Baudry, D., & Bigaud, D. (2021) · Applied Sciences · doi:10.3390/app11156810 · Cited by 160 · see citing works
Internet of Nano-Things, Things and Everything: Future Growth Trends
Miraz, M. H., Ali, M., Excell, P., & Picking, R. (2018) · Future Internet · doi:10.3390/fi10080068 · Cited by 156 · see citing works
A state-of-the-art review on mobile robotics tasks using artificial intelligence and visual data
Cebollada, S., Payá, L., Flores, M., Peidró, A., & Reinoso, Ó. (2020) · Expert Systems with Applications · doi:10.1016/j.eswa.2020.114195 · Cited by 156 · see citing works
A futuristic perspective on human-centric assembly
Wang, L. (2021) · Journal of Manufacturing Systems · doi:10.1016/j.jmsy.2021.11.001 · Cited by 154 · see citing works
Impact of IoT on Manufacturing Industry 4.0: A New Triangular Systematic Review
Kalsoom, T., Ahmed, S., Rafi-ul-Shan, P. M., Azmat, M., Akhtar, P., Pervez, Z., Imran, M. A., & Rehman, M. U. (2021) · Sustainability · doi:10.3390/su132212506 · Cited by 136 · see citing works
An Exploratory Bibliometric Analysis of the Birth and Emergence of Industry 5.0
Madsen, D. Ø., & Berg, T. (2021) · Applied System Innovation · doi:10.3390/asi4040087 · Cited by 117 · see citing works
What kind of innovation policy does the bioeconomy need?
Schütte, G. (2018) · New Biotechnology · doi:10.1016/j.nbt.2017.04.003 · Cited by 107 · see citing works
Process Automation in an IoT–Fog–Cloud Ecosystem: A Survey and Taxonomy
Chegini, H., Naha, R. K., Mahanti, A., & Thulasiraman, P. (2021) · IoT · doi:10.3390/iot2010006 · Cited by 105 · see citing works
Narula, S., Puppala, H., Kumar, A., V, Frederico, G. F., Dwivedy, M., Prakash, S., & Talwar, V. (2021) · Journal of Cleaner Production · doi:10.1016/j.jclepro.2021.127141 · Cited by 92 · see citing works
Anthopoulos, L. G., & Kazantzi, V. (2021) · Sustainable Cities and Society · doi:10.1016/j.scs.2021.103492 · Cited by 92 · see citing works
The Economic Aspect of Digital Sustainability: A Systematic Review
Cricelli, L., & Strazzullo, S. (2021) · Sustainability · doi:10.3390/su13158241 · Cited by 82 · see citing works
Industry 5.0 and its applications in orthopaedics
Haleem, A., & Javaid, M. (2018) · Journal of Clinical Orthopaedics and Trauma · doi:10.1016/j.jcot.2018.12.010 · Cited by 79 · see citing works
Review on industrial mathematics and materials at Industry 1.0 to Industry 4.0
Vinitha, K., Prabhu, R. A., Bhaskar, R., et al. (2020) · Materials Today Proceedings · doi:10.1016/j.matpr.2020.06.331 · Cited by 78 · see citing works
Text-Mining Techniques and Tools for Systematic Literature Reviews: A Systematic Literature Review
Feng, L., Chiam, Y. K., & Lo, S. K. (2017) · Asia-Pacific Software Engineering Conference (APSEC) · doi:10.1109/apsec.2017.10 · Cited by 75 · see citing works
A review of machine learning for new generation smart dispatch in power systems
Yin, L., Gao, Q., Zhao, L., Zhang, B., Wang, T., Li, S., & Liu, H. (2019) · Engineering Applications of Artificial Intelligence · doi:10.1016/j.engappai.2019.103372 · Cited by 75 · see citing works
Ammar, M., Haleem, A., Javaid, M., Bahl, S., & Verma, A. (2021) · Materials Today Proceedings · doi:10.1016/j.matpr.2021.09.248 · Cited by 74 · see citing works
Intelligent Sensors for Real-Time Decision-Making
Coito, T., Firme, B., Martins, M. S. E., et al. (2021) · Automation · doi:10.3390/automation2020004 · Cited by 72 · see citing works
The effect of industrial revolutions on the transformation of social and economic systems
Melnyk, L. H., Kubatko, O. V., Dehtyarova, I. B., et al. (2019) · Problems and Perspectives in Management · doi:10.21511/ppm.17(4).2019.31 · Cited by 71 · see citing works
A comparison of content analysis usage and text mining in CSR corporate disclosure
Aureli, S. (2017) · The International Journal of Digital Accounting Research · doi:10.4192/1577-8517-v17_1 · Cited by 66 · see citing works
Miglani, A., & Kumar, N. (2021) · Computer Communications · doi:10.1016/j.comcom.2021.07.009 · Cited by 65 · see citing works
Design of Scalable IoT Architecture Based on AWS for Smart Livestock
Dineva, K., & Atanasova, T. V. (2021) · Animals · doi:10.3390/ani11092697 · Cited by 60 · see citing works
The fourth industrial revolution of supply chains: A tertiary study
Barata, J. (2021) · Journal of engineering and technology management · doi:10.1016/j.jengtecman.2021.101624 · Cited by 58 · see citing works
Khurana, S., Haleem, A., Luthra, S., Huisingh, D., & Mannan, B. (2020) · Journal of Cleaner Production · doi:10.1016/j.jclepro.2020.124466 · Cited by 54 · see citing works
Conceptual Model of Digital Platform for Enterprises of Industry 5.0
Gorodetsky, V., Larukchin, V., & Skobelev, P. O. (2019) · Studies in computational intelligence · doi:10.1007/978-3-030-32258-8_4 · Cited by 40 · see citing works
Rehman, K. U., Aslam, F., Mata, M., Martins, J., Abreu, A., Lourenço, A. M., & Mariam, S. (2021) · Sustainability · doi:10.3390/su13137054 · Cited by 32 · see citing works
Namugera, F., Wesonga, R., & Jehopio, P. J. (2019) · Computational Social Networks · doi:10.1186/s40649-019-0063-4 · Cited by 29 · see citing works
Deepu, T. S., & Ravi, V. (2021) · Intelligent Systems with Applications · doi:10.1016/j.iswa.2021.200048 · Cited by 29 · see citing works
Enabling intelligent Mg-sheet processing utilizing efficient machine-learning algorithm
Shariati, M., Weber, W. E. J., Bohlen, J., et al. (2020) · Materials Science and Engineering A · doi:10.1016/j.msea.2020.139846 · Cited by 22 · see citing works
Technology and Corporate Social Responsibility
Potočan, V. (2021) · Sustainability · doi:10.3390/su13158658 · Cited by 22 · see citing works
Local Productive Systems’ Transitions to Industry 4.0+
Bellandi, M., & Propris, L. D. (2021) · Sustainability · doi:10.3390/su132313052 · Cited by 21 · see citing works
Mizrahi, D., Zuckerman, I., & Laufer, I. (2020) · Sensors · doi:10.3390/s20247026 · Cited by 18 · see citing works
Guo, Q., Yu, H., Dan, Z., et al. (2021) · Sustainability · doi:10.3390/su132212503 · Cited by 18 · see citing works
Information Technology Infrastructures Supporting Industry 5.0 Facilities
Massaro, A. S. (2021) · doi:10.1002/9781119716907.ch2 · Cited by 17 · see citing works
Model based systems engineering—A text mining based structured comprehensive overview
Akundi, A., & Mondragón, O. (2021) · Systems Engineering · doi:10.1002/sys.21601 · Cited by 15 · see citing works
Self-citationA Secure Corroboration Protocol for Internet of Things (IoT) Devices Using MQTT Version 5 and LDAP
Vithanage, N. N. N., Thanthrige, S. S. H., Kapuge, M. C. K. P., et al. (2021) · International Conference on Information Networking · doi:10.1109/icoin50884.2021.9333910 · Cited by 11 · see citing works
Effect of Human-Robot Interaction on the Fleet Size of AIV Transporters in FMS
Martin, L., Gonzalez-Romo, M., Sahnoun, M., et al. (2021) · International Conference on Cyber Management and Engineering (CyMaEn) · doi:10.1109/cymaen50288.2021.9497273 · Cited by 10 · see citing works
State of the Art and Technology Innovation
Massaro, A. S. (2021) · Wiley eBooks · doi:10.1002/9781119716907.ch1 · Cited by 5 · see citing works
Variations in cycle-time when using knowledge-based tasks for humans and robots
Fast–Berglund, Å., & Thorvald, P. (2021) · IFAC-PapersOnLine · doi:10.1016/j.ifacol.2021.08.017 · Cited by 4 · see citing works
Flagged first, then by citations
Research works printed but not linked: 7
- Madsen, E.S.; Bilberg, A.; Hansen, D.G. Industry 4.0 and digitalization call for vocational skills, applied industrial engineering, and less for pure academics. In Proceedings of the 5th P&OM World Conference, Production and Operations Management, P&OM, Havana, Cuba, 6-10 September 2016.
- Skobelev, P.O.; Borovik, S.Y. On the way from Industry 4.0 to Industry 5.0: From digital manufacturing to digital society. Industry 4.0 2017, 2, 307-311.
- Müller, J. Enabling Technologies for Industry 5.0: Results of a Workshop with Europe's Technology Leaders; European Commission: Brussels, Belgium, 2020.
- Hearst, M. What is text mining. SpringerPlus 2016, 5, 1608.
- Wiedemann, G.; Niekler, A. Hands-On: A Five Day Text Mining Course for Humanists and Social Scientists in R. Available online: http://ceur-ws.org/Vol-1918/wiedemann.pdf (accessed on 10 November 2021).
- Petersen, J.A.; Paulich, J.B.; Khodakarami, F.; Spyropoulou, S.; Kumar, V. Customer-based Execution Strategy in a Global Digital Economy. Int. J. Res. Mark. 2021, in press. [CrossRef] · DOI
- Margherita, E.G.; Braccini, A.M. Socio-technical perspectives in the Fourth Industrial Revolution-Analysing the three main visions: Industry 4.0, the socially sustainable factory of Operator 4.0 and Industry 5.0. In Proceedings of the 7th International Workshop on Socio-Technical Perspective in IS Development (STPIS 2021), Trento, Italy, 14-15 October 2021.
Cited by
Sorted by citations
Lv, Z. (2023) · Research · doi:10.34133/research.0071 · Cited by 108 · see citing works
“[50] discovered that the key technologies of 5IR were peopleoriented solutions and human–computer interaction (HCI).”
Sverko, M., Grbac, T. G., & Mikuc, M. (2022) · IEEE Access · doi:10.1109/access.2022.3211288 · Cited by 71 · see citing works
“0 [209] singled out AI, Big data, supply chain, digital transformation, ML and IoT as key enablers identified by”
Background
- Authors
- Akundi, A., Euresti, D., Luna, S., Ankobiah, W., Lopes, A., & Edinbarough, I.
- Affiliations
- The University of Texas Rio Grande Valley (US)
- The University of Texas at El Paso (US)
- Corresponding author
- Akundi, Aditya
- Venue
- Applied System Innovation
- Publisher
- MDPI AG
- Published
- 2022-02-17
- Volume
- 5
- Issue
- 1
- Pages
- 27
- ISSN
- 2571-5577 (ISSN-L)
- OpenAlex
- W4212802598
- Cited by
- 482
- References
- 61
- Citations by year
- 2026: 80 · 2025: 129 · 2024: 143 · 2023: 104 · 2022: 26
- FWCI
- 46.13
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Applied System Innovation (publishedVersion, cc-by)
- ScholarWorks @ UTRGV (The University of Texas Rio Grande Valley) (submittedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Topics
- Physical Sciences › Engineering › Industrial and Manufacturing Engineering › Digital Transformation in Industry
- Social Sciences › Decision Sciences › Management Science and Operations Research › Impact of AI and Big Data on Business and Society
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Advanced Data and IoT Technologies
- Keywords
- Industry 5.0, Industry 4.0, research trends, human-machine collaboration, personalized production, supply chain optimization, digital transformation, smart manufacturing, sustainable manufacturing, artificial intelligence, big data, Internet of Things, machine learning, keyword extraction, topic modeling
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