A Fast Diagnosis Method of Escalator Reversal Faults Based on Dynamic Information and Multiattribute Decision-Making

Mingxing Jia, Zhiheng Pan, Guanghai Li, Chunhua Chen, Chen Wang and Jia-Bao Liu

Journal of Mathematics, 2021, vol. 2021, 1-10

Abstract: There are many reasons for escalator reversal failure, and the reasons are distributed in different locations. It is difficult to locate the specific location of the fault in the actual fault troubleshooting. At the same time, the information related to the failure is not used in the troubleshooting, so there is a problem of inefficient troubleshooting. To this end, this paper proposes a multiattribute decision-making method that integrates dynamic information and gives the optimal troubleshooting order to improve the efficiency of the troubleshooting. First of all, according to the structure of the escalator components, the escalator reversal fault tree is established. Secondly, a static decision matrix is established by comprehensively considering the failure probability, search cost, and influence degree of the bottom event of the fault tree. Finally, the influence matrix of information on each attribute is given by the dynamic information obtained in troubleshooting, the static decision fusion influence matrix determines the dynamic decision matrix, the dynamic decision matrix is weighted and normalized, and the Technique for Order Preference by Similarity to Ideal Solution is used to determine the optimal troubleshooting order. Taking the reversal failure of a certain type of escalators as an example, the method of multiattribute decision-making of fusion dynamic information is used to shorten the troubleshooting time, improve the efficiency of troubleshooting, and verify the effectiveness of this method.

Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jjmath:6294869

DOI: 10.1155/2021/6294869

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