Preventive maintenance period decision for elevator parts based on multi-objective optimization method. (December 2021)

• Record Type: Journal Article
• Authors: Niu, Dapeng; Guo, Lei; Bi, Xiaolin; Wen, Di
• Is Part Of: Journal of building engineering. Volume 44(2021)
• Publication Date: 2021-12
• Subjects: Elevator parts -- Age reduction factor -- Failure rate increasing factor -- Multi-objective optimization model -- Monte Carlo simulation method -- Maintenance period; Building -- Periodicals; 690.05
• DOI: 10.1016/j.jobe.2021.102984
• Languages: English
• ISSNs: 2352-7102

Abstract

Abstract: Elevator maintenance plays an important role in the safe and reliable operation of elevators. However, elevator maintenance is carried under some relevant norms and standards at present, and little research has been conducted to explore how to analytically make maintenance period decision for elevator parts. In addition, the unreasonable selection of the elevator maintenance period will cause excessive cost and low equipment operation efficiency. A decision-making method for elevator parts' maintenance is provided in this paper, which aims to solve the problem of seeking a reasonable maintenance cycle for elevator parts. First of all, the historical fault data of elevator parts is used to analyze their fault distribution law. In order to accurately reflect the changes of parts after maintenance and repair, the age reduction factor and the failure rate increasing factor are introduced to establish a mixed failure rate model. Accordingly, the cost rate and utilization rate model are established under the comprehensive consideration of cost and time factors in the maintenance process. Furthermore, a multi-objective optimization model is built with maintenance frequency as the decision variable. Then, Monte Carlo simulation method is used to solve the optimization model, and the best maintenance period of the parts within the service time is obtained. Finally, the proposed method is applied to the elevator parts to find out their optimum maintenance frequency, and the results show the effectiveness of the method. A reasonable maintenance period can not only reduce the risk of equipment failure, but also save costs so as to avoid excessive waste of resources. Highlights: The failure distribution law model of elevator parts was established based on the historical failure data. Age reduction factor and failure rate increasing factor were introduced to establish a mixed failure rate model. The multi-objective optimization model was established to determine maintenance period of elevator parts. Monte Carlo simulation algorithm was used to solve the optimization model.