New Advances in Mathematical Applications for Reliability Analysis
A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "D1: Probability and Statistics".
Deadline for manuscript submissions: 10 November 2025 | Viewed by 66
Special Issue Editors
Interests: reliability modeling; machine learning; RUL prediction; digital twin; AM
Interests: LED packaging; wide-bandgap power electronics packaging and reliability; fault diagnosis and prognostics
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Advancing reliability analysis through mathematical applications lies at the intersection of engineering, mathematics, statistics, and computer science. This convergence drives transformative progress in assessing and enhancing the performance, safety, and longevity of complex systems, including mechanical systems, electronic components, and industrial processes. By employing advanced mathematical models and computational techniques, reliability analysis provides critical insights into product and system behavior, failure mechanisms, and risk mitigation, ultimately improving decision-making processes across diverse industries. Maximizing the potential of these methodologies requires the careful formulation of research problems, the selection of appropriate models, and the application of advanced algorithms.
This Special Issue aims to showcase the latest advancements in mathematical methods and models for reliability assessment across various engineering and scientific domains. It will explore topics such as probabilistic modeling, statistical inference, stochastic models, machine learning and deep learning approaches, and optimization techniques applied to reliability assessment. Contributions may include theoretical developments, computational algorithms, case studies, and interdisciplinary applications. Researchers and practitioners are invited to submit original research articles, review papers, and methodological advancements that enhance the understanding and implementation of reliability analysis in real-world scenarios.
Dr. Mesfin Ibrahim
Dr. Jiajie Fan
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 100 words) can be sent to the Editorial Office for announcement on this website.
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. Mathematics is an international peer-reviewed open access semimonthly journal published by MDPI.
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Keywords
- reliability analysis
- probabilistic modeling
- statistical inference
- markov models
- stochastic models and methods
- machine learning in reliability
- optimization techniques
- system failure prediction
- risk assessment
- fault detection and diagnostics
- survival analysis
- bayesian methods
- structural reliability
- reliability modeling
- failure data analysis
- maintenance modeling
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