Intelligent Systems in Engineering Design: Enhancing Efficiency and Accuracy

Authors

  • S. Balamuralitharan, Radhika.V, Santhoshkumar S., Someshwar Siddi, Satya Sravani

Keywords:

Intelligent systems, engineering design, artificial intelligence, design optimization, machine learning, design automation, expert systems, decision support, computational engineering.

Abstract

In a few years, the adoption of intelligent systems into engineering design has transformed the conventional design method. These systems are powered by artificial intelligence (AI), machine learning (ML) and expert systems and help engineers to optimize the process, minimize the design error, and increase the overall efficiency. The role of intelligent systems in engineering design, existing research in the field, a methodological framework of implementing such systems and the analysis of their influence on the performance of design are the focus of the current paper. With case studies and simulations, the results show dramatic increases in speed of decision-making, precision in design, and use of resources. The findings indicate that the intelligent systems play a crucial role in the introduction of a new epoch of intelligent engineering, creating a basis for new achievements in self-designed environments.

Downloads

Download data is not yet available.

References

P. Arévalo and D. Ochoa-Correa, “Toward enhanced efficiency: soft sensing and intelligent modeling in industrial electrical systems,” Processes, vol. 12, no. 7, p. 1365, Jun. 2024, doi: 10.3390/pr12071365.

K. Gao, Y. Huang, A. Sadollah, and L. Wang, “A review of energy-efficient scheduling in intelligent production systems,” Complex & Intelligent Systems, vol. 6, no. 2, pp. 237–249, Sep. 2019, doi: 10.1007/s40747-019-00122-6.

X. Zheng, S. Zhou, R. Xu, and H. Chen, “Energy-efficient scheduling for multi-objective two-stage flow shop using a hybrid ant colony optimisation algorithm,” International Journal of Production Research, vol. 58, no. 13, pp. 4103–4120, Jul. 2019, doi: 10.1080/00207543.2019.1642529.

M. W. L. Moreira, J. J. P. C. Rodrigues, V. Korotaev, J. Al-Muhtadi, and N. Kumar, “A comprehensive review on smart decision support systems for health care,” IEEE Systems Journal, vol. 13, no. 3, pp. 3536–3545, Jan. 2019, doi: 10.1109/jsyst.2018.2890121.

H. Sarker, “AI-Based modeling: techniques, applications and research issues towards automation, intelligent and smart systems,” SN Computer Science, vol. 3, no. 2, Feb. 2022, doi: 10.1007/s42979-022-01043-x.

Sircar, K. Yadav, K. Rayavarapu, N. Bist, and H. Oza, “Application of machine learning and artificial intelligence in oil and gas industry,” Petroleum Research, vol. 6, no. 4, pp. 379–391, Jun. 2021, doi: 10.1016/j.ptlrs.2021.05.009.

R. Yanes, P. Martinez, and R. Ahmad, “Towards automated aquaponics: A review on monitoring, IoT, and smart systems,” Journal of Cleaner Production, vol. 263, p. 121571, Apr. 2020, doi: 10.1016/j.jclepro.2020.121571.

M. Injadat, A. Moubayed, A. B. Nassif, and A. Shami, “Machine learning towards intelligent systems: applications, challenges, and opportunities,” Artificial Intelligence Review, vol. 54, no. 5, pp. 3299–3348, Jan. 2021, doi: 10.1007/s10462-020-09948-w.

E. S. Mohamed, Aa. Belal, S. K. Abd-Elmabod, M. A. El-Shirbeny, A. Gad, and M. B. Zahran, “Smart farming for improving agricultural management,” The Egyptian Journal of Remote Sensing and Space Science, vol. 24, no. 3, pp. 971–981, Sep. 2021, doi: 10.1016/j.ejrs.2021.08.007.

G. Adamides et al., “Smart Farming techniques for climate change adaptation in Cyprus,” Atmosphere, vol. 11, no. 6, p. 557, May 2020, doi: 10.3390/atmos11060557.

M. Bacco, P. Barsocchi, E. Ferro, A. Gotta, and M. Ruggeri, “The Digitisation of Agriculture: a Survey of Research Activities on Smart Farming,” Array, vol. 3–4, p. 100009, Sep. 2019, doi: 10.1016/j.array.2019.100009.

M. Fernandes, S. M. Vieira, F. Leite, C. Palos, S. Finkelstein, and J. M. C. Sousa, “Clinical Decision Support Systems for Triage in the Emergency Department using Intelligent Systems: a Review,” Artificial Intelligence in Medicine, vol. 102, p. 101762, Nov. 2019, doi: 10.1016/j.artmed.2019.101762.

W. Jia, M. Sun, J. Lian, and S. Hou, “Feature dimensionality reduction: a review,” Complex & Intelligent Systems, vol. 8, no. 3, pp. 2663–2693, Jan. 2022, doi: 10.1007/s40747-021-00637-x.

M. Khalifa and M. Albadawy, “AI in diagnostic imaging: Revolutionising accuracy and efficiency,” Computer Methods and Programs in Biomedicine Update, vol. 5, p. 100146, Jan. 2024, doi: 10.1016/j.cmpbup.2024.100146.

E. Bwambale, F. K. Abagale, and G. K. Anornu, “Smart irrigation monitoring and control strategies for improving water use efficiency in precision agriculture: A review,” Agricultural Water Management, vol. 260, p. 107324, Nov. 2021, doi: 10.1016/j.agwat.2021.107324.

Downloads

Published

22.12.2024

How to Cite

S. Balamuralitharan. (2024). Intelligent Systems in Engineering Design: Enhancing Efficiency and Accuracy. International Journal of Intelligent Systems and Applications in Engineering, 12(23s), 3028 –. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/7590

Issue

Section

Research Article