Authors :
Prasanna Adhithya Balagopal
Volume/Issue :
Volume 9 - 2024, Issue 7 - July
Google Scholar :
https://tinyurl.com/44cutm7v
Scribd :
https://tinyurl.com/7apr9jye
DOI :
https://doi.org/10.38124/ijisrt/IJISRT24JUL1389
Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.
Abstract :
Artificial Intelligence (AI) is coming to
mainstream and as emerged as a transformative force in
various fields not just limited including mechanical
engineering. This paper provides an overview of the
profound impact of AI on the practice and evolution of
mechanical engineering. The usage of AI technologies in
the field of mechanical engineering has potential to
revolutionize traditional design, manufacturing, and
maintenance processes. With AI-powered design tools
engineers now can generate optimized designs faster with
greater efficiency, leading to enhanced product
performance and reduced development cycles. Further,
Predictive/forecasting method of AI in maintenance
systems facilitate early detection of equipment failures,
thereby minimizing downtime and maintenance costs.
Keywords :
Artificial Intelligence (AI), Mechanical Engineering, Design Optimization, AI Tools, Predictive Maintenance, Robotics and Automation.
References :
- Srivastava, Sambhrant & Kumar, Vijay & Singh, Saurabh & Yadav, Pankaj & Singh, Brihaspati & Bhaskar, Amit. (2024). A Review on Application of Artificial Intelligence in Mechanical Engineering. 10.4018/979-8-3693-5271-7.ch002.
- Mondal, Surajit & Goswami, Shankha. (2024). Rise of Intelligent Machines: Influence of Artificial Intelligence on Mechanical Engineering Innovation. Spectrum of Engineering and Management Sciences. 2. 46-55. 10.31181/sems1120244h.
- Cioffi, R., Travaglioni, M., Piscitelli, G., Petrillo, A., & De Felice, F. (2020). Artificial intelligence and machine learningapplications in smart production: Progress, trends, and directions. Sustainability, 12(2), 492.https://doi.org/10.3390/su12020492.
- Arinez, J. F., Chang, Q., Gao, R. X., Xu, C., & Zhang, J. (2020). Artificial intelligence in advanced manufacturing: Current status and future outlook. Journal of Manufacturing Science and Engineering, 142(11), 110804.https://doi.org/10.1115/1.4047855
- Liu, J., Chang, H., Forrest, J. Y. L., & Yang, B. (2020). Influence of artificial intelligence on technological innovation: Evidence from the panel data of china's manufacturing sectors. Technological Forecasting and Social Change, 158,120142. https://doi.org/10.1016/j.techfore.2020.120142.
- Chang, C. W., Lee, H. W., & Liu, C. H. (2018). A review of artificial intelligence algorithms used for smart machine tools. Inventions, 3(3), 41. https://doi.org/10.3390/inventions3030041
- Rodriguez-Rodriguez, I., Rodriguez, J. V., Shirvanizadeh, N., Ortiz, A., & Pardo-Quiles, D. J. (2021). Applications ofartificial intelligence, machine learning, big data and the internet of things to the COVID-19 pandemic: Ascientometric review using text mining. International Journal of Environmental Research and Public Health, 18(16),8578. https://doi.org/10.3390/ijerph18168578.
- Hoosain, M. S., Paul, B. S., & Ramakrishna, S. (2020). The impact of 4IR digital technologies and circular thinkingon the United Nations sustainable development goals. Sustainability, 12(23), 10143.https://doi.org/10.3390/su122310143.
- Al-Gerafi, M. A., Goswami, S. S., Khan, M. A., Naveed, Q. N., Lasisi, A., AlMohimeed, A., & Elaraby, A. (2024).Designing of an effective e-learning website using inter-valued fuzzy hybrid MCDM concept: A pedagogicalapproach. Alexandria Engineering Journal, 97, 61-87. https://doi.org/10.1016/j.aej.2024.04.012.
- Soori, M., Arezoo, B., & Dastres, R. (2023). Artificial intelligence, machine learning and deep learning in advanced robotics, a review. Cognitive Robotics. https://doi.org/10.1016/j.cogr.2023.04.001
- Mohan, T. R., Roselyn, J. P., Uthra, R. A., Devaraj, D., & Umachandran, K. (2021). Intelligent machine learning based total productive maintenance approach for achieving zero downtime in industrial machinery. Computers &Industrial Engineering, 157, 107267. https://doi.org/10.1016/j.cie.2021.107267
- Jenis, J., Ondriga, J., Hrcek, S., Brumercik, F., Cuchor, M., & Sadovsky, E. (2023). Engineering applications of artificialintelligence in mechanical design and optimization. Machines, 11(6), 577.https://doi.org/10.3390/machines11060577
- Dixon, J. R. (1986, August). Artificial intelligence and design: a mechanical engineering view. In Proceedings of the Fifth AAAI National Conference on Artificial Intelligence (pp. 872-877).
- Artkın, F. (2022). Applications of artificial intelligence in mechanical engineering. Avrupa Bilim ve Teknoloji Dergisi, (45), 159-163.
- Srivastava, S., Kumar, V., Singh, S. K., Yadav, P., Singh, B., & Bhaskar, A. (2024). A Review on Application of Artificial Intelligence in Mechanical Engineering. Machine Learning Techniques and Industry Applications, 29-46.
16. Sinha, R., Paredis, C. J. J., Liang, V., and Khosla, P. K. (November 1, 2000). "Modeling and Simulation Methods for Design of Engineering Systems ." ASME. J. Comput. Inf. Sci. Eng. March 2001; 1(1): 84–91. https://doi.org/10.1115/1.1344877
Artificial Intelligence (AI) is coming to
mainstream and as emerged as a transformative force in
various fields not just limited including mechanical
engineering. This paper provides an overview of the
profound impact of AI on the practice and evolution of
mechanical engineering. The usage of AI technologies in
the field of mechanical engineering has potential to
revolutionize traditional design, manufacturing, and
maintenance processes. With AI-powered design tools
engineers now can generate optimized designs faster with
greater efficiency, leading to enhanced product
performance and reduced development cycles. Further,
Predictive/forecasting method of AI in maintenance
systems facilitate early detection of equipment failures,
thereby minimizing downtime and maintenance costs.
Keywords :
Artificial Intelligence (AI), Mechanical Engineering, Design Optimization, AI Tools, Predictive Maintenance, Robotics and Automation.