International Journal of Engineering and Modern Technology (IJEMT )
E-ISSN 2504-8848
P-ISSN 2695-2149
VOL. 10 NO. 1 2024
DOI: https://doi.org/10.56201/ijemt.v10.no1.2024.pg83.107
Toyosi Mercy Fatoba, Glory Jaiyeoba , Oluwafemi Timothy Oladosu , and Muhideen Oyetunji Oyewole
This in-depth exploration uncovers the game-changing effect of smart factories on the continuous improvement of the production process, harnessing the power of advanced technologies. By closely examining key components such as Machine Learning, Virtual Reality, Additive Manufacturing, and Big Data Analysis, this study provides a detailed understanding of how these innovations shape the smart factory landscape. It highlights the adaptability and efficacy of these techniques by showcasing real-world implementations through case studies across several industrial sectors, going beyond the technical aspects. Moreover, the review delves into the practicalities of implementation, discussing strategies like Advanced Sensing, Control, Platform, and Model (ASCPM), and Visualization, Informatics, and Digital Manufacturing (VIDM). A SWOT analysis reveals the internal strengths and weaknesses, recognizing factors like interoperability, decentralization, and modularity, while also addressing challenges such as the need for personnel training and substantial investment. Looking ahead, the paper emphasizes the exciting opportunities presented by smart factories, including sustainable development, cost reduction, and the emergence of new business models. It also addresses potential threats, such as job losses and cybersecurity concerns. Ultimately, the review paints a human picture of smart factories, showcasing their roles or significance in the continuous improvement of the production process through their transformative impact on efficiency, waste reduction, cost savings, and innovation in manufacturing. The future research recommendations underscore the need to focus
Smart Factory; Continuous Process Improvement; Industry 4.0; Connected Industries; Cyber-Physical System.
He, S., Zhu, J., He, P., & Lyu, M. R. (2016). Experience Report: System Log Analysis for Anomaly
Detection. 2016 IEEE 27th International Symposium on Software Reliability Engineering
(ISSRE), 207–218. https://doi.orHe,g/10.1109/ISSRE.2016.21
Milic, S. D., & Babic, B. M. (2020). Toward the Future—Upgrading Existing Remote Monitoring
Concepts to IIoT Concepts. IEEE Internet of Things Journal, 7(12), 11693–11700.
https://doi.org/10.1109/JIOT.2020.2999196
Chen, G., Wang, P., Feng, B., Li, Y., & Liu, D. (2020). The framework design of smart factory in
discrete manufacturing industry based on cyber-physical system. International Journal of
Computer
Integrated
Manufacturing,
33(1),
79–101.
https://doi.org/10.1080/0951192X.2019.1699254