Research on integrated scheduling of equipment predictive maintenance and production decision based on physical modeling approach

• Autorzy: Zhang Qinglei , Yang Lei , Duan Jianguo , Qin Jiyun , Zhou Ying

Identyfikatory

DOI

10.17531/ein/175409

• Języki publikacji: EN

Abstrakty

EN

Equipment performance deteriorates continuously during the production process, which makes it difficult to achieve the expected effect of production decisions made in advance. Predictive maintenance and production decisions integrated scheduling aim to rationalise maintenance activities. It has been extensively researched. However, past studies have assumed that faults obey a specific probability distribution based on historical data. It is difficult to analyse equipment that is brand new into service or has poor historical failure data. Thus, in this paper, we construct a twin model of a device based on a physical modelling approach and tune it to ensure high fidelity of the model. Degradation curves were created based on equipment characteristics and developed maintenance activities.Develop an integrated scheduling model for predictive maintenance and production decisions with the goal of minimising maximum processing time. An improved genetic algorithm is used to solve the problem optimally. Finally, apply a practical scenario to verify the effectiveness of the proposed method.

Słowa kluczowe

EN

physical modelling; degradation curve; predictive maintenance; production decision; improved genetic algorithm

• Wydawca: Polskie Naukowo-Techniczne Towarzystwo Eksploatacyjne
• Czasopismo: Eksploatacja i Niezawodność
• Rocznik: 2024
• Tom: Vol. 26, no. 1
• Strony: art. no. 175409
• Opis fizyczny: Bibliogr. 24 poz., rys., tab., wykr.

Twórcy

autor

Zhang Qinglei

• China Institute of FTZ Supply Chain, Shanghai MaritimeUniversity, China

autor

Yang Lei

• School ofLogistics Engineering, Shanghai Maritime University, China

autor

Duan Jianguo

• China Institute of FTZ Supply Chain, Shanghai MaritimeUniversity, China

autor

Qin Jiyun

• China Institute of FTZ Supply Chain, Shanghai MaritimeUniversity, China

autor

Zhou Ying

• China Institute of FTZ Supply Chain, Shanghai MaritimeUniversity, China

Bibliografia

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