Industry 4.0 and Smart Manufacturing: A Review

Year : 2025 | Volume : 03 | Issue : 02 | Page : 14 17
    By

    Heena M. Patel,

  • Mayur R. Chotaliya,

  • Darshan H. Bhalodia,

  • Parth M. Lakum,

  1. Assistant Professor, Department of Mechanical Engineering, Atmiya University, Rajkot, Gujarat, India
  2. Assistant Professor, Department of Mechanical Engineering, Atmiya University, Rajkot, Gujarat, India
  3. Assistant Professor, Department of Mechanical Engineering, Atmiya University, Rajkot, Gujarat, India
  4. Assistant Professor, Department of Mechanical Engineering, Atmiya University, Rajkot, Gujarat, India

Abstract

This review looks at Industry 4.0 and smart manufacturing’s idea, enabling technologies, implementation issues, and future prospects. Drawing on recent literature, the paper synthesizes key pillars such as the Industrial Internet of Things (IIoT), cyber-physical systems (CPS), artificial intelligence, digital twins, and additive manufacturing. It highlights integration requirements across supply chains, cyber security concerns, workforce implications, and standards activities that influence adoption. The literature survey focuses on empirical studies and systematic reviews to map progress during the 2016–2024 period. A methodology for conducting structured reviews in the Industry 4.0 domain is described. Finally, the review identifies research gaps and proposes future research directions emphasizing human-centric design, sustainability, and legacy system integration. The integration of digital, physical, and biological technology has led to a paradigm shift in production systems known as the fourth industrial revolution, or Industry 4.0. Industry 4.0 places more emphasis on intelligent, connected, and autonomous production environments than previous industrial revolutions, which were mainly concerned with mechanization, electrification, and automation. The practical implementation of this idea is known as “smart manufacturing,” which allows factories to sense, analyze, and react to real-time data across the whole product life cycle. Integrating cutting-edge information and communication technology with conventional production assets is essential to Industry 4.0. Decentralized decision-making and smooth data transmission are made possible by technologies like digital twins, cloud and edge computing, cyber-physical systems (CPS), artificial intelligence (AI), and the Industrial Internet of Things (IIoT). Predictive maintenance, mass customisation, increased operational visibility, and increased resource efficiency are all supported by these capabilities. Manufacturers increasingly see smart manufacturing as a strategic enabler for productivity, quality improvement, and disruption resistance as global competition heats up. Industry 4.0 adoption is uneven across industries and geographical areas, despite its potential advantages. High installation costs, interoperability of diverse systems, cybersecurity hazards, and the integration of legacy equipment are issues that many firms deal with. Significant organizational change is also necessary for the transition, including cross-disciplinary cooperation, new business models, and workforce reskilling. By encouraging interoperability and directing implementation, standards development and reference architectures are essential in tackling these issues.

Keywords: Industry 4.0, smart manufacturing, cyber-physical systems, IIoT, digital twin

[This article belongs to International Journal of Manufacturing and Production Engineering ]

How to cite this article:
Heena M. Patel, Mayur R. Chotaliya, Darshan H. Bhalodia, Parth M. Lakum. Industry 4.0 and Smart Manufacturing: A Review. International Journal of Manufacturing and Production Engineering. 2025; 03(02):14-17.
How to cite this URL:
Heena M. Patel, Mayur R. Chotaliya, Darshan H. Bhalodia, Parth M. Lakum. Industry 4.0 and Smart Manufacturing: A Review. International Journal of Manufacturing and Production Engineering. 2025; 03(02):14-17. Available from: https://journals.stmjournals.com/ijmpe/article=2025/view=234930


References

  1. Bogue, R. (2018). Collaborative robots: A review of capabilities, applications, and future prospects. Industrial Robot, 45(5), 502–508.
  2. Kang, H. S., Lee, J. Y., Choi, S., Kim, H., Park, J. H., & Son, J. Y. (2016). Smart manufacturing: Past research, present findings, and future directions. International Journal of Precision Engineering and Manufacturing–Green Technology, 3(1), 111–128.
  3. Lasi, H., Fettke, P., Kemper, H., Feld, T., & Hoffmann, M. (2014). Industry 4.0. Business & Information Systems Engineering, 6(4), 239–242.
  4. Lee, J., Bagheri, B., & Kao, H. A. (2015). A cyber-physical systems architecture for Industry 4.0-based manufacturing systems. Manufacturing Letters, 3, 18–23.
  5. Patel, S., Tanwar, S., Gupta, R., & Kumar, N. (2021). A deep learning framework for cybersecurity in smart manufacturing. Computers & Industrial Engineering, 153, 107080.
  6. Tao, F., Qi, Q., Liu, A., & Kusiak, A. (2018). Data-driven smart manufacturing. Journal of Manufacturing Systems, 48, 157–169.
  7. Wan, J., Chen, M., Xia, F., Di, L., & Zhou, Y. (2016). Industrial IoT: A survey on emerging technologies, applications, and challenges. IEEE Access, 4, 7630–7649.
  8. Thoben, K. D., Wiesner, S., & Wuest, T. ( 2017 ). “Industrie 4.0” and smart manufacturing-a review of research issues and application examples. International journal of automation technology, 11 ( 1 ), 4–16.
  9. Bahrin, M. A. K., Othman, M. F., Azli, N. H. N., & Talib, M. F. ( 2016 ). Industry 4.0: A review on industrial automation and robotic. Jurnal teknologi, 78 ( 6–13 ).
  10. B. Salgues, Society 5.0: Industry of the Future, Technologies, Methods and Tools, John Wiley & Sons, 2018.
  11. Besharati-Foumani, H., Lohtander, M., & Varis, J. ( 2019 ). Intelligent process planning for smart manufacturing systems: a state-of-the-art review. Procedia Manufacturing, 38, 156–162.
  12. Oluyisola, O. E., Bhalla, S., Sgarbossa, F., & Strandhagen, J. O. ( 2022 ). Designing and developing smart production planning and control systems in the industry 4.0 era: a methodology and case study. Journal of Intelligent Manufacturing, 33 ( 1 ), 311–332.
Regular Issue Subscription Review Article
Volume 03
Issue 02
Received 11/12/2025
Accepted 18/12/2025
Published 24/12/2025
Publication Time 13 Days
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