Theoretical Study of Factory Machine Equipment: Manual vs Artificial Intelligent
Keywords:
Theoretical, Machine Tools, Factory, Manual, Artificial IntelligentAbstract
The development of industrial technology has brought significant changes in the factory operational system, especially in the use of machine tools. This study aims to describe the theoretical factory machine tools: manual vs AI and the theoretical factory machine tools manual vs AI. The research method uses triangulation comparative analysis. The results show that The study shows that the implementation of AI-based machines offers significant advantages over manual machines, especially in terms of efficiency, productivity, and predictive maintenance. Although AI implementation faces some challenges, such as initial costs and the need for skilled human resources, the long-term benefits are enormous for the industry.
References
Authored Book
Gunawan, C.I (2015). Ekonomi Makro. Malang : CV. IRDH.
Krivosheya, A., Danilchenko, J. U., Storchak, M., & Pasternak, S. (2015). Design of shaping machine and tooling systems for gear manufacturing. In Theory and Practice of Gearing and Transmissions: In Honor of Professor Faydor
L. Litvin (pp. 425-450). Cham: Springer International Publishing.
Mathew, D., Brintha, N. C., & Jappes, J. W. (2023). Artificial intelligence powered automation for industry 4.0. In New horizons for Industry 4.0 in modern business (pp. 1-28). Cham: Springer International Publishing.
Nur, R., and Suyuti, M. A. (2018). Perancangan mesin-mesin industri. Yogyakarta : Deepublish.
Youssef, H. A., El-Hofy, H. A., & Ahmed, M. H. (2023). Manufacturing technology: materials, processes, and equipment. Florida, USA : Crc Press.
Journal Article
Abdollahi, J., Keshandehghan, A., Gardaneh, M., Panahi, Y., & Gardaneh, M. (2020). Accurate detection of breast cancer metastasis using a hybrid model of artificial intelligence algorithm. Archives of Breast Cancer, 22-28.
Anaam, I. K., Hidayat, T., Pranata, R. Y., Abdillah, H., & Putra, A. Y. W. (2022, June). Pengaruh trend otomasi dalam dunia manufaktur dan industri. In Vocational Education National Seminar (VENS) (Vol. 1, No. 1).
Dewi, L. S. (2024). Peranan Artificial Intelligence dalam Meningkatkan Produktivitas Industri. Circle Archive, 1(5).
Javaid, M., Haleem, A., Singh, R. P., & Suman, R. (2022). Artificial intelligence applications for industry 4.0: A literature-based study. Journal of Industrial Integration and Management, 7(01), 83-111.
Mehrpouya, M., Dehghanghadikolaei, A., Fotovvati, B., Vosooghnia, A., Emamian, S. S., & Gisario, A. (2019). The potential of additive manufacturing in the smart factory industrial 4.0: A review. Applied Sciences, 9(18), 3865.
Mubarak, R. (2020). Implementasi Artificial Intelligence Dalam Proses Industri Manufaktur Otomotif. Jurnal Ilmu Komputer, 3(2).
Prihastono, E., & Prakoso, B. (2017). Perawatan preventif untuk mempertahankan utilitas performance pada mesin cooling tower di cv. arhu tapselindo bandung. Dinamika Teknik Industri.
Saez, M., Maturana, F. P., Barton, K., & Tilbury, D. M. (2018). Real-time manufacturing machine and system performance monitoring using internet of things. IEEE Transactions on Automation Science and Engineering, 15(4), 1735-1748.
Website
Deloitte. (2022). The state of AI in business transformation. Deloitte Insights. https://www.deloitte.com/id/en.html
Gartner. (2023). AI-driven transformation: Opportunities and risks for enterprises. Gartner Research. www.gartner.com
PwC. (2022). Sizing the prize: The economic impact of AI on the world economy. PricewaterhouseCoopers. www.pwc.com
Sathyabama Institute Of Science And Technology. Manufacturing Technology.
https://sist.sathyabama.ac.in/sist_coursematerial/uploads/SPR1301.pdf
Downloads
Published
Issue
Section
License
Copyright (c) 2025 Valentina Murni Sania; Cakti Indra Gunawan

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.




