Importance measure-based maintenance strategy optimization: Fundamentals, applications and future directions in AI and IoT

doi:10.1007/s42524-024-4003-0

Front. Eng

2024, Vol. 11

Issue (3) : 542-567 https://doi.org/10.1007/s42524-024-4003-0

Systems Engineering Theory and Application

Importance measure-based maintenance strategy optimization: Fundamentals, applications and future directions in AI and IoT

Hongyan DUI¹(

), Xinmin WU¹, Shaomin WU², Min XIE³

¹. School of Management, Zhengzhou University, Zhengzhou 450001, China
². Kent Business School, University of Kent, Canterbury, Kent CT2 7FS, UK
³. Department of Systems Engineering and Engineering Management, City University of Hong Kong, Hong Kong 999077, China

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Abstract

Numerous maintenance strategies have been proposed in the literature related to reliability. This paper focuses on the utilization of reliability importance measures to optimize maintenance strategies. We analyze maintenance strategies based on importance measures and identify areas lacking sufficient research. The paper presents principles and formulas for advanced importance measures within the context of optimizing maintenance strategies. Additionally, it classifies methods of maintenance strategy optimization according to importance measures and outlines the roles of these measures in various maintenance strategies. Finally, it discusses potential challenges that optimization of maintenance strategies based on importance measures may encounter with future technologies.

Keywords maintenance strategy importance measure reliability maintenance cost

Corresponding Author(s): Hongyan DUI

Just Accepted Date: 16 May 2024 Online First Date: 28 June 2024 Issue Date: 26 September 2024

Cite this article:

Hongyan DUI,Xinmin WU,Shaomin WU, et al. Importance measure-based maintenance strategy optimization: Fundamentals, applications and future directions in AI and IoT[J]. Front. Eng, 2024, 11(3): 542-567.

URL:

https://academic.hep.com.cn/fem/EN/10.1007/s42524-024-4003-0
https://academic.hep.com.cn/fem/EN/Y2024/V11/I3/542

Fig.1 The retrieval process and result analysis of MSO.

Tab.1 Important research fields and objectives of MSO

Fig.2 The retrieval process and result analysis of importance measures.

Fig.3 The retrieval process of papers of IMMSO.

References	IMs	Advantages	Limitations
Wu and Coolen (2013)	$I k C (t)$	Distinguishing between maintenance costs for faulty components and system failures; Investigating processes within finite periods; Considering different maintenance costs for various components; Applicable to diverse maintenance scenarios	Only applicable to binary systems with binary components; Only considering fixed costs; Neglecting economic dependence among components; Only considering minimal maintenance
Gupta et al. (2013)	$I i C E I M (t)$	Simultaneously considering operating time, severity of failures, system structure, and total failure cost; Applicable for prioritizing basic events such as inspections, fault detection, and maintenance activities; Considering different maintenance costs for various components	Only considering fixed costs; Neglecting economic dependence among components
Gravette and Barker (2015)	$I a, i$	Considering the availability of maintenance-centric components; Considering the impact of maintenance activities; Applicable for determining optimal inspection frequencies	Only applicable to binary systems with binary components; Only analyzing systems related to series and parallel configurations; Only considering perfect maintenance
Dui et al. (2022e)	$I i P$	Considering the time value during the recovery process; Considering performance loss in the metro network due to cascading failures	Only applicable to binary networks with binary nodes; Neglecting realistic factors such as connection path length, transfer time, etc
Dui et al. (2023i)	$I j$	Applicable to other network resource allocations with characteristics; Considering the impact of maintenance efficiency and degradation on yield loss	Neglecting realistic factors such as costs Only considering perfect maintenance
Lin et al. (2016)	$C I O q (t)$	Applicable to multi-state systems with multi-state components; Considering the impact of multiple interdependent degradation processes and maintenance tasks; Distinguishing between discrete and continuous degradation processes	Neglecting parameter uncertainty; Considering fixed detection intervals; Assuming corrective maintenance for component failures is immediate Only considering perfect maintenance
Si et al. (2012)	$I l, q I I M (i)$	Applicable to multi-state systems with multi-state components; Simultaneously considering the probability distribution of component states, transition rates, and system maintenance costs; Regarding maintenance costs as system performance; Considering imperfect maintenance	Only analyzing systems related to series and parallel configurations; Neglecting economic dependence among components
Dui et al. (2017c)	$I i I I M, C (t)$	Considering the joint impact of maintenance costs and time on system reliability; Considering different maintenance costs for various components Distinguishing between critical components and non-critical components	Neglecting economic dependence among components
Chen et al. (2022)	$I i M C I M (t)$	Distinguishing between maintenance costs for faulty components and system failures; Distinguishing between critical components and non-critical components	Only applicable to binary components; Neglecting economic dependence among components
Zhu et al. (2021)	$I M i M R U L − π$ $I M i M R S P − π$	Considering time dependency, remaining useful life, and maintenance behaviors (considering system reliability, average remaining system profit, and maintenance costs); Combining characteristics of time-dependent and time-independent life importance; Providing an extension of importance to incoherent systems; Considering imperfect maintenance	Only applicable to binary components; Assuming no loss of reliability within replacement intervals; Neglecting economic dependence among components
Lin and Wang (2010)	$U C E L (t k, i)$	Considering economic dependence and structural dependence; Emphasizing the interval between two maintenance time points	Only applicable to systems related to series and parallel configurations
Zhang et al. (2022)	$I i I B M P (t)$ $I i J I B M P (t) X k (t)$	Applicable to multi-state systems; Considering the correlation between the two components; Considering the changes in maintenance costs (rate) resulting from component state changes; Considering different maintenance costs for various components	Only applicable to binary components; Neglecting economic dependence among components
Dui et al. (2019b)	$I i I I M (t) X m (t)$	Applicable to multi-state systems; Reflecting the relative importance of system performance between two components; Distinguishing between critical components and non-critical components	Only applicable to binary components; Neglecting constraints on maintaining resources
Chen and Feng (2022)	$I B G r (T r)$	Introducing survival signature to calculate system reliability and reduce the number of calculations; Considering four different types of components; Considering different maintenance degrees for different maintenance types, including perfect maintenance and minimum maintenance; Considering replacement costs and maintenance costs with economic dependence	Only applicable to binary systems with binary components; Neglecting constraints on maintaining resources
Dui et al. (2023j)	$Δ U m$	Applicable to multi-state systems with multi-state components; Distinguishing between critical components and non-critical components. Considering the probability of component state transition and the variable maintenance cost of the system; Considering the influence of wind speed and temperature	Neglecting economic dependence among components; Only applicable to direct-drive permanent magnet turbo systems with specific structures;
Dui et al. (2023k)	$C M P i \| j (t; e t)$	Applicable to multi-state systems with multi-state components; Distinguish between deterministic and stochastic external impact environment; Distinguishing between critical components and non-critical components; Considering different maintenance costs for various components	Neglecting economic dependence among components; Only considering perfect maintenance
Do and Bérenguer (2022)	$I M M R L i (t)$	Considering mean residual life, dynamic changes in component states, and system structure.	Only applicable to binary systems; Only applicable to non-repairable systems; Neglecting structural dependence among components; Only considering perfect maintenance
Do and Bérenguer (2022)	$I M M R L − c i (t)$	Considering maintenance costs, improvements in mean residual life, and economic dependencies between components
Han et al. (2021)	$I l F B$	Applicable to multi-state systems; Investigating large-scale and continuous production activities; Considering the functional dependencies of components; Considering component performance states and mission reliability	Assuming no starvation and blocking in production; Assuming component degradation follows a time-homogeneous Markov process. Neglecting constraints on maintaining resources; Only considering perfect maintenance

Tab.2 Contrastive analysis of extensions of importance measures on maintenance

Fig.4 IMs-based MSO process.

References	IMs	Systems	Types of Maintenance Strategies	Rules
Si et al. (2012)	$I l, q I I M$	Multi-state	Condition-based maintenance	A
Chen et al. (2022)	MCIM	Binary	Opportunity maintenance
Dui et al. (2022f)	I	Binary	Corrective maintenance
Gao et al. (2007)	JRI & JFI	Binary	Corrective maintenance
Dui et al. (2018)	Birnbaum importance & IIM	Binary	Adaptive maintenance	B
Zhang et al. (2022)	REIM & MEM	Multi-state	Corrective maintenance
Zhang (2020)	Approximate measure & rate measure	Multi-state
Zio et al. (2007)	Performance achievement worth measure	Multi-state
Dui et al. (2020)	JIIM	Multi-state
Bai et al. (2021)	$I R R W$ & $I R A W$	Binary
Petritoli et al. (2018)	IM	Multi-state	Preventive Maintenance
Dui et al. (2021b)	Birnbaum importance, IIM	Binary	Preventive Maintenance
Wu and Coolen (2013)	$I k C$	Binary	Corrective maintenance	C
Gupta et al. (2013)	CEIM	Binary	Corrective maintenance
Han et al. (2021)	Functional importance	Multi-state	Predictive Maintenance
Dui et al. (2017c)	$I i I I M, C$	Multi-state	Preventive Maintenance
Wu et al. (2016)	CMP	Binary	Preventive Maintenance
Shi et al. (2020)	RAWM	Multi-state	Condition-based maintenance
Nguyen et al. (2014)	Birnbaum structure importance	Binary	Condition-based maintenance
Vu et al. (2016)	Birnbaum structure importance	Binary	Opportunity maintenance
Nguyen et al. (2017)	Birnbaum structure importance	Binary	Opportunity maintenance
Zhao et al. (2019)	Birnbaum importance	Binary	Adaptive maintenance
Dui et al. (2023i)	CMP	Multi-state	Corrective maintenance	D
Dui et al. (2019b)	JIIM	Binary	Preventive Maintenance
Dui et al. (2023d)	Environmental importance	Binary
Dui et al. (2021c)	CMP	Binary
Dui et al. (2021d)	JIIM	Multi-state
Zhang et al. (2020)	IIM	Multi-state
Chen et al. (2021)	IIM & Griffith IM	Multi-state	Adaptive maintenance

Tab.3 Reference analysis of optimization rules based on IMs

Tab.4 Reference analysis of optimization algorithms based on IMs

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