Assessment of the optimal preventive maintenance period using stochastic hybrid modelling

被引：3

作者：

D'Urso, D. ^{[1
]}

Sinatra, A. ^{[1
]}

Compagno, L. ^{[1
]}

Chiacchio, F. ^{[1
]}

机构：

[1] Univ Catania, Dept Elect Elect & Comp Engn, Catania, Italy

来源：

3RD INTERNATIONAL CONFERENCE ON INDUSTRY 4.0 AND SMART MANUFACTURING | 2022年 / 200卷

关键词：

Stochastic Hybrid Automation; Monte Carlo Simulation; Preventive Maintenance; Bearings; FAILURE RATE MODEL; DYNAMIC RELIABILITY;

D O I：

10.1016/j.procs.2022.01.367

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

Also the maintenance world is heading towards the era of artificial intelligence applied to the evaluation of the residual life of devices and predictive maintenance. On the other hand, when the operating conditions can change significantly and randomly, influencing the performance of the system subject to aging phenomena, then the use of a stochastic hybrid approach for the reliability modeling of the system can lead to a closer representation of the reality. This latter approach is applied to the evaluation of the costs associated with the preventive maintenance of the bearings of a centrifugal pump used in petroleum processes. The evaluation is obtained by means of the Monte Carlo simulation methodology. (C) 2022 The Authors. Published by Elsevier B.V.

引用

页码：1664 / 1673

页数：10

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