A preventive maintenance policy and a method to approximate the failure process for multi-component systems

被引:0
|
作者
Wu, Shaomin [1 ]
Asadi, Majid [2 ]
机构
[1] Univ Kent, Kent Business Sch, Canterbury CT2 7PE, Kent, England
[2] Univ Isfahan, Fac Math & Stat, Dept Stat, Esfahan 8174673441, Iran
关键词
(T) Maintenance policy; Stochastic processes; Non-homogeneous Poisson process (NHPP); Generalised renewal process (GRP); Superposition of generalised renewal processes (SGRP); REPAIRABLE SYSTEMS; RENEWAL PROCESS; POINT PROCESS; SUPERPOSITION; OPTIMIZATION; INTENSITY; MODELS;
D O I
10.1016/j.ejor.2024.05.039
中图分类号
C93 [管理学];
学科分类号
12 ; 1201 ; 1202 ; 120202 ;
摘要
Numerous maintenance policies have been proposed in the reliability mathematics and engineering literature. Nevertheless, little has been reported on their practical applications in industries. This gap is largely due to restrictive assumptions of the maintenance policies. Two of the main assumptions are that maintenance is conducted on typical components and that the reliability of an item under maintenance is known (where the item can be a component or a system composed of multiple components). These assumptions do not often hold in the real world: maintenance is often performed on a collection of components such as an integrated circuit plate and the reliability of each individual component may not be known. To reduce these gaps, this paper develops a new maintenance policy for a collection of components and an approximate method to estimate the reliability of this collection based on the failure data collected from the field. The maintenance policy considers that a system is composed of three subsystems with different levels of maintenance effectiveness (i.e, minimal, imperfect, and perfect). The approximate estimate of the reliability of each subsystem is derived based on the failure data that are time between failures of the system but not those of the components that cause the system to fail. An algorithm for simulating the superposition of generalised renewal processes is then proposed. Numerical examples are used to illustrate the proposed approximation method.
引用
收藏
页码:825 / 835
页数:11
相关论文
共 50 条
  • [21] A new multi-objective optimization model for preventive maintenance and replacement scheduling of multi-component systems
    Moghaddam, Kamran S.
    Usher, John S.
    ENGINEERING OPTIMIZATION, 2011, 43 (07) : 701 - 719
  • [22] Maintenance Policy for Multi-Component System with Fuzzy Lifetimes
    赵瑞清
    高金伍
    Tsinghua Science and Technology, 2003, (01) : 49 - 54
  • [23] Approximate evaluation of average downtime under an integrated approach of opportunistic maintenance for multi-component systems
    Peng, Hao
    Zhu, Qiushi
    COMPUTERS & INDUSTRIAL ENGINEERING, 2017, 109 : 335 - 346
  • [24] Preventive maintenance decision model of multi-component system with degradation interaction
    Yang Z.
    Zhao J.
    Cheng Z.
    Xi Tong Gong Cheng Yu Dian Zi Ji Shu/Systems Engineering and Electronics, 2018, 40 (04): : 823 - 832
  • [25] Impact of few failure data on the opportunistic replacement policy for multi-component systems
    Laggoune, Radouane
    Chateauneuf, Alaa
    Aissani, Djamil
    RELIABILITY ENGINEERING & SYSTEM SAFETY, 2010, 95 (02) : 108 - 119
  • [26] Optimization of the Preventive Maintenance for a Multi-component System Using Genetic Algorithm
    Dahia, Zakaria
    Bellaouar, Ahmed
    Billel, Soulmana
    RENEWABLE ENERGY FOR SMART AND SUSTAINABLE CITIES: ARTIFICIAL INTELLIGENCE IN RENEWABLE ENERGETIC SYSTEMS, 2019, 62 : 313 - 320
  • [27] Multi-level predictive maintenance for multi-component systems
    Nguyen, Kim-Anh
    Phuc Do
    Grall, Antoine
    RELIABILITY ENGINEERING & SYSTEM SAFETY, 2015, 144 : 83 - 94
  • [28] A condition-based maintenance policy for multi-component systems with Levy copulas dependence
    Li, Heping
    Deloux, Estelle
    Dieulle, Laurence
    RELIABILITY ENGINEERING & SYSTEM SAFETY, 2016, 149 : 44 - 55
  • [29] Modified iterative aggregation procedure for maintenance optimisation of multi-component systems with failure interaction
    Zhang, Zhuoqi
    Wu, Su
    Lee, Seungchul
    Ni, Jun
    INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE, 2014, 45 (12) : 2480 - 2489
  • [30] Discrete maintenance optimization of complex multi-component systems
    Bris, Radim
    Byczanski, Petr
    Gono, Radomir
    Rusek, Stanislav
    RELIABILITY ENGINEERING & SYSTEM SAFETY, 2017, 168 : 80 - 89