Cyber-Physical Systems in Smart Manufacturing: Current Progress and Future Perspectives
DOI:
https://doi.org/10.54518/jaei.4.1.2026.1473Keywords:
Artificial Intelligence, Big Data Analytics, Cyber-Physical Systems, Intelligent Industrial Systems, Systematic Literature ReviewAbstract
Digital transformation has significantly reshaped modern engineering by integrating intelligent technologies that enhance industrial efficiency, flexibility, resilience, and sustainability. This study aims to review recent advances in engineering technologies supporting intelligent industrial systems while identifying current implementation challenges and future research opportunities. A Systematic Literature Review (SLR) approach was employed by analyzing scientific publications published between 2021 and 2025 retrieved through Google Scholar from reputable international databases. The review focuses on the integration of Cyber-Physical Systems, Artificial Intelligence, the Internet of Things, Big Data Analytics, Cloud Computing, Edge Computing, Digital Twin, and intelligent robotics for Smart Manufacturing and the transition toward Industry 5.0. The findings indicate that the convergence of these technologies significantly improves real-time monitoring, predictive maintenance, data-driven decision-making, operational efficiency, production flexibility, and industrial resilience. Nevertheless, several challenges remain, including cybersecurity risks, interoperability issues, data governance, infrastructure investment, and workforce readiness. Future engineering systems should therefore emphasize interoperable architectures, trustworthy artificial intelligence, sustainable engineering practices, and effective human–technology collaboration to support adaptive, resilient, and sustainable industrial ecosystems. This review provides a comprehensive overview of emerging engineering technologies and offers valuable insights for researchers, engineers, industrial practitioners, and policymakers involved in next-generation intelligent industrial development.
References
Aldoseri, A., Al-Khalifa, K. N., & Hamouda, A. M. (2023). Re-thinking data strategy and integration for artificial intelligence: concepts, opportunities, and challenges. Applied Sciences, 13(12), 7082.
Alojaiman, B. (2023). Technological modernizations in the industry 5.0 era: A descriptive analysis and future research directions. Processes, 11(5), 1318.
Dritsas, E., & Trigka, M. (2025). A survey on the applications of cloud computing in the industrial internet of things. Big data and cognitive computing, 9(2), 44.
Hamdouna, M., & Khmelyarchuk, M. (2025). Technological innovations shaping sustainable competitiveness—A systematic review. Sustainability, 17(5), 1953.
Islam, M. T., Sepanloo, K., Woo, S., Woo, S. H., & Son, Y. J. (2025). A review of the industry 4.0 to 5.0 transition: exploring the intersection, challenges, and opportunities of technology and human–machine collaboration. Machines, 13(4), 267.
Jin, J., Pang, Z., Kua, J., Zhu, Q., Johansson, K. H., Marchenko, N., & Cavalcanti, D. (2025). Cloud-fog automation: The new paradigm towards autonomous industrial cyber-physical systems. IEEE Journal on Selected Areas in Communications.
Kuchuk, H., & Malokhvii, E. (2024). Integration of IoT with cloud, fog, and edge computing: a review. Advanced Information Systems, 8(2), 65-78.
Paraskevas, K. (2025). Data integration and storage strategies in heterogeneous analytical systems: architectures, methods, and interoperability challenges. Information, 16(11), 932.
Secundo, G., Spilotro, C., Gast, J., & Corvello, V. (2025). The transformative power of artificial intelligence within innovation ecosystems: a review and a conceptual framework. Review of Managerial Science, 19(9), 2697-2728.
Singh, M., Kumar, A., Khanna, N. N., Laird, J. R., Nicolaides, A., Faa, G., ... & Suri, J. S. (2024). Artificial intelligence for cardiovascular disease risk assessment in personalised framework: a scoping review. EClinicalMedicine, 73.
Soori, M., Dastres, R., Arezoo, B., & Jough, F. K. G. (2024). Intelligent robotic systems in Industry 4.0: A review. Journal of Advanced Manufacturing Science and Technology, 4(3), 2024007.
Sulaiman, N. S., Fauzi, M. A., Wider, W., Rajadurai, J., Hussain, S., & Harun, S. A. (2022). Cyber–information security compliance and violation behaviour in organisations: A systematic review. Social Sciences, 11(9), 386.
Zhukabayeva, T., Zholshiyeva, L., Karabayev, N., Khan, S., & Alnazzawi, N. (2025). Cybersecurity solutions for industrial internet of things–edge computing integration: Challenges, threats, and future directions. Sensors, 25(1), 213.
Zong, Z., & Guan, Y. (2025). AI-driven intelligent data analytics and predictive analysis in Industry 4.0: Transforming knowledge, innovation, and efficiency. Journal of the knowledge economy, 16(1), 864-903.
