A Time-Replacement Policy for Multistate Systems with Aging Components under Maintenance, from a Component Perspective

This study aims for multistate systems (MSSs) with aging multistate components (MSCs) to construct a time-replacement policy and thereby determine the optimal time to replace the entire system. The nonhomogeneous continuous time Markov models (NHCTMMs) quantify the transition intensities among the d...

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Main Authors: Chao-Hui Huang, Chun-Ho Wang
Format: Article
Language:English
Published: Hindawi Limited 2019-01-01
Series:Mathematical Problems in Engineering
Online Access:http://dx.doi.org/10.1155/2019/9651489
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spelling doaj-abfb5b3bce814e4687a723d06ccce13a2020-11-25T02:15:10ZengHindawi LimitedMathematical Problems in Engineering1024-123X1563-51472019-01-01201910.1155/2019/96514899651489A Time-Replacement Policy for Multistate Systems with Aging Components under Maintenance, from a Component PerspectiveChao-Hui Huang0Chun-Ho Wang1Department of Applied Science, R.O.C. Naval Academy, No. 669, Junxiao Rd., Zuoying District, Kaohsiung City 81345, TaiwanDepartment of Power Vehicle and Systems Engineering, Chung Cheng Institute of Technology, National Defense University, No. 75, Shiyuan Rd., Daxi Township, Taoyuan County 33551, TaiwanThis study aims for multistate systems (MSSs) with aging multistate components (MSCs) to construct a time-replacement policy and thereby determine the optimal time to replace the entire system. The nonhomogeneous continuous time Markov models (NHCTMMs) quantify the transition intensities among the degradation states of each component. The dynamic system state probabilities are therefore assessed using the established NHCTMMs. Solving NHCTMMs is rather complicated compared to homogeneous continuous time Markov models (HCTMMs) in determining reliability related performance indexes. Often, traditional mathematics cannot acquire accurate explicit expressions, in particular, for multiple components that are involved in designed system configuration. To overcome this difficulty, this study uses Markov reward models and the bound approximation approach to assess rewards of MSSs with MSCs, including such things as total maintenance costs and the benefits of the system staying in acceptable working states. Accordingly, we established a long-run expected benefit (LREB) per unit time, representing overall MSS performance through a lifetime, to determine the optimal time to replace the entire system, at which time the LREB values are maximized. Finally, a simulated case illustrates the practicability of the proposed approach.http://dx.doi.org/10.1155/2019/9651489
collection DOAJ
language English
format Article
sources DOAJ
author Chao-Hui Huang
Chun-Ho Wang
spellingShingle Chao-Hui Huang
Chun-Ho Wang
A Time-Replacement Policy for Multistate Systems with Aging Components under Maintenance, from a Component Perspective
Mathematical Problems in Engineering
author_facet Chao-Hui Huang
Chun-Ho Wang
author_sort Chao-Hui Huang
title A Time-Replacement Policy for Multistate Systems with Aging Components under Maintenance, from a Component Perspective
title_short A Time-Replacement Policy for Multistate Systems with Aging Components under Maintenance, from a Component Perspective
title_full A Time-Replacement Policy for Multistate Systems with Aging Components under Maintenance, from a Component Perspective
title_fullStr A Time-Replacement Policy for Multistate Systems with Aging Components under Maintenance, from a Component Perspective
title_full_unstemmed A Time-Replacement Policy for Multistate Systems with Aging Components under Maintenance, from a Component Perspective
title_sort time-replacement policy for multistate systems with aging components under maintenance, from a component perspective
publisher Hindawi Limited
series Mathematical Problems in Engineering
issn 1024-123X
1563-5147
publishDate 2019-01-01
description This study aims for multistate systems (MSSs) with aging multistate components (MSCs) to construct a time-replacement policy and thereby determine the optimal time to replace the entire system. The nonhomogeneous continuous time Markov models (NHCTMMs) quantify the transition intensities among the degradation states of each component. The dynamic system state probabilities are therefore assessed using the established NHCTMMs. Solving NHCTMMs is rather complicated compared to homogeneous continuous time Markov models (HCTMMs) in determining reliability related performance indexes. Often, traditional mathematics cannot acquire accurate explicit expressions, in particular, for multiple components that are involved in designed system configuration. To overcome this difficulty, this study uses Markov reward models and the bound approximation approach to assess rewards of MSSs with MSCs, including such things as total maintenance costs and the benefits of the system staying in acceptable working states. Accordingly, we established a long-run expected benefit (LREB) per unit time, representing overall MSS performance through a lifetime, to determine the optimal time to replace the entire system, at which time the LREB values are maximized. Finally, a simulated case illustrates the practicability of the proposed approach.
url http://dx.doi.org/10.1155/2019/9651489
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