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Advances in Reliability Engineering for Complex Systems
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Advances in Reliability Engineering for Complex Systems

A special issue of Systems (ISSN 2079-8954). This special issue belongs to the section "Complex Systems and Cybernetics".

Deadline for manuscript submissions: 30 June 2026 | Viewed by 6207

Special Issue Editors

Dr. Randy Buchanan

E-Mail Website
Guest Editor
U.S. Army Engineer Research and Development Center (ERDC), Vicksburg, MS 39180, USA
Interests: electrical and systems engineering; resilience; reliability; control systems; cryogenics; space systems; ML/AI; high performance computing; applied physics
Special Issues, Collections and Topics in MDPI journals
Dr. Mohammad Marufuzzaman

E-Mail Website
Guest Editor
Industrial & Systems Engineering, Mississippi State University, Starkville, MS, USA
Interests: supply chain optimization with applications in renewable energy; stochastic programming; decomposition methods; solving large scale supply chain network problems and supply chain risk management

Special Issue Information

Dear Colleagues,

This Special Issue of Systems invites you to address recent advances in reliability engineering for complex systems that enable the development of highly dependable systems by proactively identifying and mitigating potential failure points and consider related topics such as downtime, operational efficiency, cost savings, and safety. Modeling and simulations that provide analysis and optimization advancements regarding physical implementation are becoming increasingly useful as system complexity increases.  Contributions to this Special Issue should explore the application of artificial intelligence and machine learning for data automation and analytics to leverage vast data potentially available for complex systems. They may also study intricate complex systems that present numerous interconnected components, requiring advanced reliability techniques to analyze interactions and potential failure pathways. To address emerging research and practices, it is imperative to identify and communicate these aspects and other exemplary research efforts. The goal of this Special Issue is to highlight significant research advancements and provide articles that contribute to the body of knowledge enhancing overall reliability engineering within complex systems.

Dr. Randy Buchanan
Dr. Mohammad Marufuzzaman
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Systems is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • systems
  • complex
  • reliability
  • failure
  • modeling and simulation
  • artificial intelligence
  • efficiency
  • optimization
  • sustainability
  • predictive

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Published Papers (6 papers)

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Research

21 pages, 861 KB  
Article
Safety Evaluation and Management Optimization Strategies for Building Operations Under the Integrated Metro Station–Commercial Development Model: A Case Study
by Yijing Huang, Heng Yu, Xiaoyu Ju and Xiulin Pan
Systems 2025, 13(12), 1081; https://doi.org/10.3390/systems13121081 - 1 Dec 2025
Viewed by 129
Abstract
With the rapid development of metro–commercial integration, ensuring the safety of building operations has become increasingly critical. This study proposes a comprehensive safety evaluation framework tailored to integrated metro–commercial complexes. The framework establishes a hierarchical indicator system encompassing risk management, human safety management, [...] Read more.
With the rapid development of metro–commercial integration, ensuring the safety of building operations has become increasingly critical. This study proposes a comprehensive safety evaluation framework tailored to integrated metro–commercial complexes. The framework establishes a hierarchical indicator system encompassing risk management, human safety management, facility and equipment safety, intelligent information management, and integrated crowd and operational risk. By combining historical records, real-time sensor data, and management logs, secondary indicators are quantified and normalized, while a hybrid weighting method integrating expert judgment and statistical analysis ensures both theoretical validity and empirical robustness. A case study demonstrates the framework’s applicability, yielding an overall operational safety score of 0.601, which corresponds to a “Moderate” level. Detailed analysis identifies deficiencies in flood resilience, intelligent monitoring reliability, and crowd-related fire risks, underscoring the complexity of safety challenges in such facilities. Targeted optimization measures—including enhanced drainage redundancy, condition-based equipment maintenance, improved intelligent monitoring, evacuation corridor expansion, and catering fire safety upgrades—are shown to substantially improve the composite safety index and operational resilience. This study contributes a dynamic, data-driven, and interpretable evaluation methodology that not only supports scientific safety management in metro–commercial buildings but also provides a reference for broader applications in multifunctional urban infrastructure. Full article
(This article belongs to the Special Issue Advances in Reliability Engineering for Complex Systems)
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24 pages, 1681 KB  
Article
Reliability Assessment for Multivariate Degradation System Based on Uncertainty and Chatterjee Correlation Coefficient
by Jiayin Tang, Mengjia Jiang and Yamin Mao
Systems 2025, 13(11), 953; https://doi.org/10.3390/systems13110953 - 27 Oct 2025
Viewed by 417
Abstract
Considering the effects of complex correlations between variables and uncertainty of degradation processes in multivariate degradation systems, a system reliability assessment method that integrated Chatterjee correlation coefficient and stochastic process theory is proposed. First, due to temporal uncertainty and measurement error in the [...] Read more.
Considering the effects of complex correlations between variables and uncertainty of degradation processes in multivariate degradation systems, a system reliability assessment method that integrated Chatterjee correlation coefficient and stochastic process theory is proposed. First, due to temporal uncertainty and measurement error in the univariate degradation process, a general Wiener-process-based state space model is constructed to determine the marginal distributions. Secondly, the nonlinear and asymmetric correlation between variables is analyzed by the nonparametric Chatterjee correlation coefficient. The multivariate joint degradation model is constructed by combining the Vine copula technique. The copula structure selection is optimized based on the goodness-of-fit criterion for modeling the degradation dependency network. In order to verify the validity of the method, comparative experiments based on the C-MAPSS aero-engine degradation dataset are conducted. Compared with the independent model ignoring the correlation of the variables, Vine copula with Chatterjee coefficient shows the rationality of the system reliability assessment. The system reliability curve lies between the cases of complete independence and complete dependence of variables. Compared to the traditional Vine copula model with Kendall coefficient, the method in this paper shows a significant improvement in asymmetric correlation characterization, with a Vuong test value of 6.37. The assessment method given in this paper provided an improved paradigm for reliability assessments of complex systems. Full article
(This article belongs to the Special Issue Advances in Reliability Engineering for Complex Systems)
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23 pages, 4483 KB  
Article
D2T2 Analysis of a Loss of Main Feed Water Accident
by Silvia Tolo and John Andrews
Systems 2025, 13(10), 927; https://doi.org/10.3390/systems13100927 - 21 Oct 2025
Viewed by 230
Abstract
The availability of accurate models capturing the realistic behaviour of complex systems is critical for the safe operation and optimal management of nuclear installations. However, the dynamic nature of such systems and the resulting dense network of interdependencies existing among their parts are [...] Read more.
The availability of accurate models capturing the realistic behaviour of complex systems is critical for the safe operation and optimal management of nuclear installations. However, the dynamic nature of such systems and the resulting dense network of interdependencies existing among their parts are no match for current risk modelling techniques, which rely on oversimplifying premises. Dependencies are often simplified or ignored, with conservative assumptions introduced to compensate, leading to results of uncertain realism. Alternative methods address these limitations but often remain difficult to scale, interpret, or integrate into established Probabilistic Safety Assessment practice. The Dynamic and Dependent Tree Theory (D2T2) offers a bridging framework that preserves the familiar FT/ET structure while enabling dependencies to be represented directly at the basic-event, intermediate, or subsystem level through compact submodels. This paper applies D2T2 to a loss of main feed water accident in a boiling water reactor, capturing dependencies from maintenance strategies to subsystem interactions. Results show that D2T2 improves reliability predictions compared with conventional FT/ET, aligns closely with dynamic benchmarks, and remains computationally tractable. Beyond accuracy, the approach makes modelling assumptions explicit and transparent, promoting deeper system understanding while lowering barriers to adoption in safety-critical applications. Full article
(This article belongs to the Special Issue Advances in Reliability Engineering for Complex Systems)
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21 pages, 4238 KB  
Article
Time-Varying Reliability Analysis of Integrated Power System Based on Dynamic Bayesian Network
by Jiacheng Wei, Tong Chen, Haolin Wen and Haobang Liu
Systems 2025, 13(7), 541; https://doi.org/10.3390/systems13070541 - 2 Jul 2025
Viewed by 953
Abstract
In response to the limitations of traditional static reliability analysis methods in characterizing the reliability changes of the Integrated Power System, this paper proposes a time-varying reliability analysis framework based on a Dynamic Bayesian Network. By embedding a multi-physics coupled degradation model into [...] Read more.
In response to the limitations of traditional static reliability analysis methods in characterizing the reliability changes of the Integrated Power System, this paper proposes a time-varying reliability analysis framework based on a Dynamic Bayesian Network. By embedding a multi-physics coupled degradation model into the conditional probability nodes of the Dynamic Bayesian Network, a joint stochastic differential equation for the degradation process was constructed, and the dynamic correlation between continuous degradation and discrete fault events throughout the entire life cycle was achieved. A modified method for modeling continuous degradation systems was proposed, which effectively solves the numerical stability problem of modeling complex degradation systems. Finally, the applicability and correctness of the model were verified through numerical examples, and the results showed that the analysis framework can be effectively applied to time-varying reliability assessment and dynamic health management of complex equipment systems such as the Integrated Power System. Full article
(This article belongs to the Special Issue Advances in Reliability Engineering for Complex Systems)
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27 pages, 3051 KB  
Article
Evaluating the Robustness of the Global LNG Trade Network: The Impact of the Russia–Ukraine Conflict
by Ruodan Ma and Zongsheng Huang
Systems 2025, 13(7), 509; https://doi.org/10.3390/systems13070509 - 25 Jun 2025
Viewed by 1369
Abstract
This study examines how the Russia–Ukraine conflict has affected the robustness of the global liquefied natural gas (LNG) trade network—an essential component of the global energy transition. As environmental concerns intensify worldwide, LNG is gaining strategic importance due to its cleaner emissions and [...] Read more.
This study examines how the Russia–Ukraine conflict has affected the robustness of the global liquefied natural gas (LNG) trade network—an essential component of the global energy transition. As environmental concerns intensify worldwide, LNG is gaining strategic importance due to its cleaner emissions and greater flexibility compared to traditional fossil fuels. However, the global LNG trade network remains vulnerable to geopolitical shocks, particularly due to its concentrated structure. In this context, we construct the LNG trade network from 2020 to 2023 and employ complex network analysis to explore its structural characteristics. We assess network robustness under various attack strategies, budget constraints, and phases of the conflict. Furthermore, we utilize the difference-in-differences (DID) method to evaluate the conflict’s impact on network robustness. Our findings reveal that the global LNG trade network exhibits a distinct center–periphery structure and regional clustering. Although the network scale has continuously expanded, its connectivity still requires improvement. The Russia–Ukraine conflict has significantly weakened network robustness, with negative impacts intensifying across attack phases and under greater budget constraints. The optimal attack strategy causes the most severe degradation, followed by high-importance attacks, while random and low-importance attacks exert limited influence. Our DID-based analysis further confirms the conflict’s significant negative impact. To strengthen its resilience, the global LNG trade network should diversify its partnerships and invest in infrastructure enhancements. Full article
(This article belongs to the Special Issue Advances in Reliability Engineering for Complex Systems)
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29 pages, 2684 KB  
Article
Comparisons Between Quantitative FMECA Methods: A Case Study on Power Transformer Risk Assessments
by Andrés A. Zúñiga, João F. P. Fernandes and Paulo J. C. Branco
Systems 2025, 13(6), 450; https://doi.org/10.3390/systems13060450 - 7 Jun 2025
Viewed by 2110
Abstract
The efficacy of new FMECA methods can be assessed through qualitative comparisons of the failure mode rankings. This approach is suitable for a few failure modes but can become impractical or lead to misleading results for more extensive problems. This fact motivated us [...] Read more.
The efficacy of new FMECA methods can be assessed through qualitative comparisons of the failure mode rankings. This approach is suitable for a few failure modes but can become impractical or lead to misleading results for more extensive problems. This fact motivated us to introduce an alternative approach for comparing different FMECA methods based on agreement coefficients, enabling a statistical comparison between rankings generated by independent raters. Despite its relevance, the application of agreement coefficients is limited in the FMECA context. Our proposed approach utilizes Cohen’s kappa coefficient to evaluate the agreement between six FMECA configurations based on a type-2 fuzzy inference system and a reference FMECA ranking. We conducted an FMECA on power transformers to test our approach, identifying fourteen potential failure modes. Results show that, based on the agreement coefficient, our proposed approach proves effective for a statistical comparison of different FMECA methods rather than a qualitative comparison between rankings. Full article
(This article belongs to the Special Issue Advances in Reliability Engineering for Complex Systems)
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