Can large language models solve complex engineering issues? Practical applications in reliability systems engineering

Yue Zhang; Yanjie Song; Yi Ren; Lining Xing; Qiang Feng; Ruifeng Xiang; Zili Wang; Witold Pedrycz

doi:10.1016/j.eng.2025.07.037

Engineering ›› DOI: 10.1016/j.eng.2025.07.037

review-article

Can large language models solve complex engineering issues? Practical applications in reliability systems engineering

Author information +

History +

PDF (2388KB)

Cite this article

Download citation ▾

Yue Zhang, Yanjie Song, Yi Ren, Lining Xing, Qiang Feng, Ruifeng Xiang, Zili Wang, Witold Pedrycz. Can large language models solve complex engineering issues? Practical applications in reliability systems engineering. Engineering DOI:10.1016/j.eng.2025.07.037

登录浏览全文

4963

注册一个新账户忘记密码

References

Publishing order | Descend order by publishing year | Descend order by cited within

[1]	Guo D, Yang D, Zhang H, Song J, Zhang R, Xu R, et al.Deepseek-R1: incentivizing reasoning capability in LLMs via reinforcement learning.2025. arXiv: 2501.12948.

[2]

Wei J, Wang X, Schuurmans D, Bosma M, Xia F, Chi E, et al.Chain-of-thought prompting elicits reasoning in large language models.In: Proceedings of the 36th International Conference on Neural Information Processing System; 2022 Nov 28–Dec 9; New Orleans, L A, USA. Red Hook: Curran Associates Inc.; 2022. p. 24824–37.

[3]	Nejjar M, Zacharias L, Stiehle F, Weber I.LLMs for science: usage for code generation and data analysis.J Softw Evol Process 2025; 37(1):e2723.

[4]	Wang Y, Guo S, Tan CW.From code generation to software testing: AI copilot with context-based RAG.IEEE Softw 2025; 42(4):34-42.

[5]	Di J Rocco, Di DRuscio, Di CSipio, Nguyen PT, Rubei R.On the use of large language models in model-driven engineering.Soft Syst Model 2025; 24(3):923-948.

[6]	Zhai Y, Yang T, Xu K, Feng D, Yang C, Ding B, et al.Enhancing decision-making for LLM agents via step-level Q-value models.Proc Conf AAAI Artif Intell 2025; 39(25):27161-27169.

[7]	Wang Z.Current status and prospects of reliability systems engineering in China.Front Eng Manag 2021; 8:492-502.

[8]	Kaiser J, Lauscher A, Eichler A.Large language models for human-machine collaborative particle accelerator tuning through natural language.Sci Adv 2025; 11(1):eadr4173.

[9]	Kim J, Lee S, Kim H.Robust vulnerability detection in solidity-based Ethereum smart contracts using fine-tuned transformer encoder models.IEEE Access 2024; 12:154700-154717.

[10]	Pang Z, Luan Y, Chen J, Li T.ParInfoGPT: an LLM-based two-stage framework for reliability assessment of rotating machine under partial information.Reliab Eng Syst Saf 2024; 250:110312.

[11]	Sun Y, Zhang Q, Bao J, Lu Y, Liu S.Empowering digital twins with large language models for global temporal feature learning.J Manuf Syst 2024; 74:83-99.

[12]	Wong MF, Tan CW.Aligning crowd-sourced human feedback for reinforcement learning on code generation by large language models.2025. arXiv: 2503.15129.

[13]

Wang H, Li YF.Large language model empowered by domain-specific knowledge base for industrial equipment operation and maintenance.In: Proceedings of the 2023 5th International Conference on System Reliability and Safety Engineering (SRSE); 2023 Oct 20–23; Beijing, China. New York City: IEE E; 2023. p. 474–9.

[14]	Kang S, An G, Yoo S.A quantitative and qualitative evaluation of LLM-based explainable fault localization.Proc ACM Softw Engl 2024; 1(FSE):1424-1446.

[15]

Roy D, Zhang X, Bhave R, Bansal C, Las-Casas P, Fonseca R, et al.Exploring LLM-based agents for root cause analysis.In: Proceedings of the 32nd ACM International Conference on the Foundations of Software Engineering; 2024 Jul 15–19; Porto de Galinhas, Brazil. New York City: Association for Computing Machinery (ACM); 2024. p. 208–19.

[16]	Wong MF, Guo S, Hang CN, Ho SW, Tan CW.Natural language generation and understanding of big code for AI-assisted programming: a review.Entropy 2023; 25(6):888.

[17]	Mostajabdaveh M, Yu TT, Ramamonjison R, Carenini G, Zhou Z, Zhang Y.Optimization modeling and verification from problem specifications using a multi-agent multi-stage LLM framework.INFOR Inf Syst Oper Res 2024; 62(4):599-617.

[18]	HegedűSC, Varga P.Co-pilots for arrowhead-based cyber-physical system of systems engineering.In: Proceedings of the NOMS2024–2024 IEEE Network Operations and Management Symposium; 2024 May 6–10; Seoul, Republic of Korea. New York City: IEE E; 2024. p. 1–6.

[19]	Feng Q, Zhang Y, Sun B, Guo X, Fan D, Ren Y, et al.Multi-level predictive maintenance of smart manufacturing systems driven by digital twin: a matheuristics approach.J Manuf Syst 2023; 68:443-454.