Resilience-oriented approach of dynamic production and maintenance scheduling optimisation considering operational uncertainty

ABSTRACT

One of the main challenges in operating multistate manufacturing systems (MMSs) is maintaining stable and robust production against various disruptions. Therefore, an urgent need exists for an operation and maintenance (O&M) method that optimises MMS resilience, i.e. the capability of withstanding or recover from disruptions of various sources. Consequently, this study proposes an integrated resilience-oriented production and maintenance scheduling approach for MMSs. This approach enhances MMS resilience by reinforcing its adaptivity to the variation in production requirements. Based on a conceptual investigation of operational uncertainty and its mechanism of disruption, this study devotes to (i) formulating a performance loss-based resilience measurement with consideration of operational uncertainties and (ii) proposing a reinforcement learning-based approach to schedule MMS operation and maintenance activities for MMS components of different performance states. An industrial case study of a ferrite phase shifter manufacturing system is subsequently conducted to validate the proposed approach. Results demonstrate the effectiveness of the proposed approach in the resilience optimisation of MMSs.

KEYWORDS:

• Production and maintenance scheduling
• resilience
• multistate manufacturing system
• operational uncertainty
• reinforcement learning

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

The authors confirm that the data supporting the findings of this study are available within the article and its supplementary materials.

Additional information

Funding

This study was supported by the National Natural Science Foundation of China (Grant Nos. 72071007).

Notes on contributors

Yuqi Cai

Yuqi Cai received his Bachelor of Engineering degree in aerocraft quality and reliability from Beihang University in 2022. He is a master candidate at the School of Reliability and Systems Engineering, Beihang University in the People’s Republic of China. His research interests are intelligent operation and maintenance, prognostics and health management of intelligent manufacturing system, he has published over 10 papers on international journals and conferences including IEEE Transactions on Reliability and etc.

Yihai He

Yihai He is a professor(PhD supervisor) at the School of Reliability and Systems Engineering, Beihang University in People’s Republic of China. He received the PhD degree in manufacturing and systems engineering from Beihang University in 2006. His main research interests are reliability in manufacturing, advanced quality engineering techniques and PHM of intelligent manufacturing system, he has published over 100 papers on international journals and conferences including International Journal of Production Research, Reliability Engineering & System safety and etc. His homepage is: http://qpr.buaa.edu.cn.

Rui Shi

Rui Shi received her Bachelor of Engineering degree in safety engineering from Beihang University in 2024. She is a master candidate at the School of Reliability and Systems Engineering, Beihang University in the People’s Republic of China. Her main research interests are operational risk modelling and predictive maintenance of intelligent manufacturing systems, she has published over 5 papers on international journals and conferences including IEEE Transactions on Reliability and etc.

Tianyu Feng

Tianyu Feng received her Bachelor of Engineering degree in safety engineering from Northeastern University in 2023. She is a master candidate at the School of Reliability and Systems Engineering, Beihang University in the People’s Republic of China. Her main research interests are process robustness modelling and PHM of intelligent manufacturing system, she has published over 5 papers on international journals and conferences including Computers & Industrial Engineering and etc.

Jiayang Li

Jiayang Li received his Bachelor of Engineering degree in aerocraft quality and reliability from Beihang University in 2024. He is a master candidate at the School of Reliability and Systems Engineering, Beihang University in the People’s Republic of China. His main research interests are mission reliability modelling and production scheduling of intelligent manufacturing systems, he has published over 3 papers on international journals and conferences including IEEE Transactions on Reliability and etc.