Home / Current Issue / Paper 1714089
Risk-Based Maintenance Optimization
Subject area: Science,Engineering and Technology · Area of research: Operations
Abstract
RBM has been one of the most popular tools applied recently regarding the asset management of logistics, transport, or infrastructure systems that are mostly driven simultaneously by demands of service continuity, safety, and economic viability. Although recent literature has produced somewhat advanced optimization approaches, with some of those not yet applied successfully because of gaps either in the description of service or economic or downtime information, this literature review discusses most of the peer-reviewed literature available within the publication range of 2020-2025 thoroughly with respect to optimization solution of RBM incorporating concepts of RAMS, life cycle costs, and asset criticalities. In this case, the prime areas of interest with emphasis on risk information into service information, economic information, or downtime information, along with man-hour capacity or downtime information receive detailed attention and emphasis. A detailed RAMS C³ strategy is also presented to scrutinize the operational readiness of those studies, with supreme emphasis given to implementability itself. It has been gathered in this review that there might be certain limitations of those studies concerning either the description of availability or maintainability information, the usage of vague definitions of criticalities, or a lack of validation tests with real-world schedules. Consequently, based on those observations, either implementable economic information or implementable downtime information, risk information, or a checklist reporting format has been presented below.
Keywords
Risk-Based Maintenance; RAMS Framework; Maintenance Optimization; Lifecycle Cost (LCC); Criticality Analysis; Constraint-Aware Scheduling; Asset Management; Logistics Infrastructure; Availability and Maintainability; Decision Support Systems
References
[1] El-Thalji, I., Al-Ghamdi, S. G., & others. (2025). Emerging Practices in Risk-Based Maintenance: Industry 4.0 Impact and the Next Generation of RBM. Applied Sciences, 15(3), 1159. https://doi.org/10.3390/app15031159
[2] Greiner, D., & Cacereño, A. (2024). Enhancing the maintenance strategy and cost in systems with surrogate-assisted multiobjective evolutionary algorithms. Developments in the Built Environment, 19, 100478. https://doi.org/10.1016/j.dibe.2024.100478
[3] ISO. (2024a). ISO 55000:2024 Asset management — Vocabulary, overview and principles. International Organization for Standardization.
[4] ISO. (2024b). ISO 55001:2024 Asset management — Asset management system — Requirements. International Organization for Standardization.
[5] Kasraei, A., & others. (2022). Maintenance Decision Support Model for Railway Track Geometry Maintenance Planning Using Cost, Reliability, and Availability Factors: A Case Study. Transportation Research Record, 2676(12), 1–14. https://doi.org/10.1177/03611981221077089
[6] Kumari, J., Karim, R., & Khanna, P. (2025). Dynamic maintenance policy development for railway rolling stock. Journal of Quality in Maintenance Engineering, 31(5), 23–42. https://doi.org/10.1108/JQME-01-2024-0005
[7] Mellal, M. A., & Zio, E. (2022). Multi-objective availability and cost optimization by PSO and COA for series-parallel systems with subsystem failure dependencies. Microprocessors and Microsystems, 89, 104422. https://doi.org/10.1016/j.micpro.2021.104422
[8] Page, M. J., McKenzie, J. E., Bossuyt, P. M., et al. (2021). The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. BMJ, 372, n71. https://doi.org/10.1136/bmj.n71
[9] Pirbhulal, S., Gkioulos, V., & Katsikas, S. (2021). A Systematic Literature Review on RAMS analysis for critical infrastructures protection. International Journal of Critical Infrastructure Protection, 33, 100427. https://doi.org/10.1016/j.ijcip.2021.100427
[10] Rethlefsen, M. L., Kirtley, S., Waffenschmidt, S., et al. (2021). PRISMA-S: An extension to the PRISMA statement for reporting literature searches in systematic reviews. Systematic Reviews, 10, 39. https://doi.org/10.1186/s13643-020-01542-z
[11] Tseremoglou, E., Tsakalidis, A., & others. (2024). Condition-Based Maintenance scheduling of an aircraft fleet: A dynamic scheduling framework. Reliability Engineering & System Safety, 241, 109684. https://doi.org/10.1016/j.ress.2023.109684
[12] Yang, D. Y., & Frangopol, D. M. (2021). Risk-based inspection planning of deteriorating structures. Structure and Infrastructure Engineering, 18(1), 1–20. https://doi.org/10.1080/15732479.2021.1907600
[13] Zhang, N., Si, S., & Hu, C. (2020). Deep reinforcement learning for condition-based maintenance of multi-component systems with dependent competing risks. Reliability Engineering & System Safety, 205, 107084. https://doi.org/10.1016/j.ress.2020.107084
How to cite this paper
@article{1714089,
author = {Muhammad Yaasar},
title = {Risk-Based Maintenance Optimization},
journal = {Iconic Research And Engineering Journals},
year = {2026},
volume = {9},
number = {8},
pages = {44-56},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1714089.pdf},
abstract = {RBM has been one of the most popular tools applied recently regarding the asset management of logistics, transport, or infrastructure systems that are mostly driven simultaneously by demands of service continuity, safety, and economic viability. Although recent literature has produced somewhat advanced optimization approaches, with some of those not yet applied successfully because of gaps either in the description of service or economic or downtime information, this literature review discusses most of the peer-reviewed literature available within the publication range of 2020-2025 thoroughly with respect to optimization solution of RBM incorporating concepts of RAMS, life cycle costs, and asset criticalities. In this case, the prime areas of interest with emphasis on risk information into service information, economic information, or downtime information, along with man-hour capacity or downtime information receive detailed attention and emphasis. A detailed RAMS C³ strategy is also presented to scrutinize the operational readiness of those studies, with supreme emphasis given to implementability itself. It has been gathered in this review that there might be certain limitations of those studies concerning either the description of availability or maintainability information, the usage of vague definitions of criticalities, or a lack of validation tests with real-world schedules. Consequently, based on those observations, either implementable economic information or implementable downtime information, risk information, or a checklist reporting format has been presented below.},
keywords = {Risk-Based Maintenance; RAMS Framework; Maintenance Optimization; Lifecycle Cost (LCC); Criticality Analysis; Constraint-Aware Scheduling; Asset Management; Logistics Infrastructure; Availability and Maintainability; Decision Support Systems},
month = {February},
doi = {https://doi.org/10.64388/IREV9I8-1714089}
}