-
CiteScore
-
Impact Factor
Volume 1, Issue 1, Next-Generation Computing Systems and Technologies
Volume 1, Issue 1, 2025
Submit Manuscript Edit a Special Issue
Article QR Code
Article QR Code
Scan the QR code for reading
Popular articles
Next-Generation Computing Systems and Technologies, Volume 1, Issue 1, 2025: 1-10

Open Access | Review Article | 09 October 2025
Next-Generation Computing Technology for Electric Vehicle Manufacturing – Concept, Challenges and Future Research
1 Department of Mechanical Engineering, GIET University, Odisha, Gunupur 765022, India
2 Department of Computer Science and Engineering, NIST University, Berhampur 761008, India
* Corresponding Author: Kali Charan Rath, [email protected]
Received: 02 September 2025, Accepted: 04 September 2025, Published: 09 October 2025  
Abstract
The electric vehicle (EV) manufacturing industry rapidly progresses from Industry 4.0 to Industry 5.0, next-generation computing technologies are emerging as disruptive enablers. This paper explores about the advanced computing paradigms to improve efficiency, robustness and adaptation across EV manufacturing ecosystems in the revolved vehicle industry in order to satisfy the increasing needs of intelligent automation, real-time decision-making and sustainable production. Through the integration of industrial case studies, literature reviews and rigorous technology mapping, the paper work validates the potential of these technologies to optimize resource utilization, speed up computer operations and overcome complications to extensive adoption. The results highlight the significance of strong frameworks to make balance between innovation and sustainability. Conclusion section is highlighting the convergence of cutting edge technology to propel the progress of autonomous, secure and human-centered electric vehicle production, thereby prompting the way of sustainability and industrial transformation.

Graphical Abstract
Next-Generation Computing Technology for Electric Vehicle Manufacturing – Concept, Challenges and Future Research

Keywords
smart manufacturing
intelligent automation
human-centric automation
next-generation computing technologies

Data Availability Statement
Not applicable.

Funding
This work was supported without any funding.

Conflicts of Interest
The authors declare no conflicts of interest.

Ethical Approval and Consent to Participate
Not applicable.

References
  1. Akter, S., Badhon, M. B., Bhuiyan, M. K. I., Hasan, H. M., Akter, F., & Islam, M. N. U. (2024). Quantum-edge cloud computing for iot: Bridging the gap between cloud, edge, and quantum technologies. Edge, and Quantum Technologies (September 29, 2024). https://dx.doi.org/10.2139/ssrn.5036779
    [Google Scholar]
  2. Azamfirei, V., Psarommatis, F., Granlund, A., & Lagrosen, Y. (2024). Towards Zero-Defect Manufacturing: a review on measurement-assisted processes and their technologies. Procedia Computer Science, 232, 1001–1010.
    [CrossRef]   [Google Scholar]
  3. Balakera, N., Konstantinidis, F. K., Tsimiklis, G., Latsa, E., & Amditis, A. (2023, February). Iiot network system from data collection to cyber-physical system transmission under the industry 5.0 era. In International Congress on Information and Communication Technology (pp. 929-941). Singapore: Springer Nature Singapore.
    [CrossRef]   [Google Scholar]
  4. Chelliah, P. R., Rahmani, A. M., Colby, R., Nagasubramanian, G., & Ranganath, S. (Eds.). (2024). Model Optimization Methods for Efficient and Edge AI: Federated Learning Architectures, Frameworks and Applications. John Wiley & Sons.
    [Google Scholar]
  5. Eren, H., Karaduman, Ö., & Gençoğlu, M. T. (2025). Security and Privacy in the Internet of Everything (IoE): A Review on Blockchain, Edge Computing, AI, and Quantum-Resilient Solutions. Applied Sciences, 15(15), 8704.
    [CrossRef]   [Google Scholar]
  6. Jun, H. B. (2022). A review on the advanced maintenance approach for achieving the zero-defect manufacturing system. Frontiers in Manufacturing Technology, 2, 920900.
    [CrossRef]   [Google Scholar]
  7. Kasoju, A. (2024). AI-Driven Anomaly Detection in Cyber-Physical Systems: A Technical Approach to Real-Time Threat Mitigation. Iconic Research and Engineering Journals, 8(4), 804–817.
    [Google Scholar]
  8. Okuyelu, O., & Adaji, O. (2024). AI-driven real-time quality monitoring and process optimization for enhanced manufacturing performance. Journal of Advanced Mathematics and Computer Science, 39(4), 81–89. https://dx.doi.org/10.9734/jamcs/2024/v39i41883
    [Google Scholar]
  9. Pizoń, J., & Gola, A. (2023). Human–machine relationship—perspective and future roadmap for industry 5.0 solutions. Machines, 11(2), 203.
    [CrossRef]   [Google Scholar]
  10. Raja Santhi, A., & Muthuswamy, P. (2023). Industry 5.0 or industry 4.0 S? Introduction to industry 4.0 and a peek into the prospective industry 5.0 technologies. International Journal on Interactive Design and Manufacturing (IJIDeM), 17(2), 947-979.
    [CrossRef]   [Google Scholar]
  11. Ramírez-Gordillo, T., Mora, H., Pujol-Lopez, F. A., Jimeno-Morenilla, A., & Maciá-Lillo, A. (2023, April). Industry 5.0: Towards human centered design in human machine interaction. In The International Research & Innovation Forum (pp. 661-672). Cham: Springer International Publishing.
    [CrossRef]   [Google Scholar]
  12. Sharma, M., Tomar, A., & Hazra, A. (2024). Edge computing for industry 5.0: Fundamental, applications, and research challenges. IEEE Internet of Things Journal, 11(11), 19070–19093.
    [CrossRef]   [Google Scholar]
  13. Sarkar, B., & Paul, R. K. (2025). AI-Driven Manufacturing Processes. In AI for Advanced Manufacturing and Industrial Applications (pp. 19–59). Springer Nature Switzerland.
    [CrossRef]   [Google Scholar]
  14. Thakur, P., & Sehgal, V. K. (2021). Emerging architecture for heterogeneous smart cyber-physical systems for industry 5.0. Computers & Industrial Engineering, 162, 107750.
    [CrossRef]   [Google Scholar]
  15. Tamizshelvan, C., & Vijayalakshmi, V. (2024). Cloud data access governance and data security using distributed infrastructure with hybrid machine learning architectures. Wireless Networks, 30(4), 2099–2114.
    [CrossRef]   [Google Scholar]
  16. Verma, S. K., Verma, V., & Ansari, M. T. J. (2024). A transition from Industry 4.0 to Industry 5.0: Securing Industry 5.0 for sustainability. In Computational Intelligence Applications in Cyber Security (pp. 1–15). CRC Press.
    [Google Scholar]
  17. Wang, K. S. (2013). Towards zero-defect manufacturing (ZDM)—a data mining approach. Advances in Manufacturing, 1(1), 62–74.
    [CrossRef]   [Google Scholar]
  18. Zhao, L. P., Li, B. H., & Yao, Y. Y. (2023). A novel predict-prevention quality control method of multi-stage manufacturing process towards zero defect manufacturing. Advances in Manufacturing, 11(2), 280–294.
    [CrossRef]   [Google Scholar]

Cite This Article
APA Style
Rath, K. C., & Mishra, B. K. (2025). Next-Generation Computing Technology for Electric Vehicle Manufacturing – Concept, Challenges and Future Research. Next-Generation Computing Systems and Technologies, 1(1), 1–10. https://doi.org/10.62762/NGCST.2025.183832

Article Metrics
Citations:

Crossref

0

Scopus

0

Web of Science

0
Article Access Statistics:
Views: 141
PDF Downloads: 74

Publisher's Note
ICCK stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and Permissions
CC BY Copyright © 2025 by the Author(s). Published by Institute of Central Computation and Knowledge. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/), which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made.
Next-Generation Computing Systems and Technologies

Next-Generation Computing Systems and Technologies

ISSN: pending (Online)

Email: [email protected]

Portico

Portico

All published articles are preserved here permanently:
https://www.portico.org/publishers/icck/