Qiang Wang, Chongjun Yang, Juan Zhou, Jiaqi Xu, Benyao Chen, Kai Zhu, Linlin Wu, Xiaomeng Xu, Wanbing Su
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引用次数: 0
Abstract
To solve the challenge of accurate in-service traction elevator failure prediction, maintenance cycle and steady availability, a novel reliability model is proposed which combines orthogonal defect classification (ODC) and Markov analysis (MA). The elevator failure data are classified by the ODC method. Then, the failure rate and maintenance rate of the elevator parts are obtained based on triangular fuzzy theory. By analyzing the maintenance function of each part, the optimum maintenance cycle of the elevator is determined. Finally, the transient state and steady state equations are established by MA to determine the steady availability of elevators. A case study on elevator accidents and failure data is used to validate the effectiveness of the proposed method. The results show that the system steady state availability of elevators in the study was 0.9002.
期刊介绍:
The Journal of Risk and Reliability is for researchers and practitioners who are involved in the field of risk analysis and reliability engineering. The remit of the Journal covers concepts, theories, principles, approaches, methods and models for the proper understanding, assessment, characterisation and management of the risk and reliability of engineering systems. The journal welcomes papers which are based on mathematical and probabilistic analysis, simulation and/or optimisation, as well as works highlighting conceptual and managerial issues. Papers that provide perspectives on current practices and methods, and how to improve these, are also welcome