Reliability in Mechanical Systems: Innovations and Applications
A special issue of Machines (ISSN 2075-1702). This special issue belongs to the section "Machines Testing and Maintenance".
Deadline for manuscript submissions: 30 November 2025 | Viewed by 382
Special Issue Editors
Interests: uncertainty quantification; aircraft reliability engineering
Special Issues, Collections and Topics in MDPI journals
Interests: inverse finite element method; structural health monitoring; composite-airfoil structure; deformation reconstruction; cross-sectional variation
Interests: AI in mechanical systems; reliability engineering; sustainability
Special Issue Information
Dear Colleagues,
Reliability and mechanical systems are fundamental to the advancement of modern engineering and technology. The integration of advanced computational methods, artificial intelligence, and big data analytics has revolutionized the way we approach reliability analysis, mechanical design, and system optimization. This Special Issue aims to explore the latest innovations and applications in reliability and mechanical systems, with a focus on enhancing system performance, safety, and sustainability.
The application of advanced technologies, such as machine learning, predictive maintenance, and digital twins, has significantly improved the reliability and efficiency of mechanical systems. These technologies enable real-time monitoring, fault detection, and predictive analytics, which are crucial for minimizing downtime and optimizing operational performance. Furthermore, the integration of reliability analysis into the design phase ensures that mechanical systems are robust, durable, and capable of withstanding various operational stresses.
This Special Issue invites contributions that address the challenges and opportunities of reliability and mechanical systems. Topics of interest include, but are not limited to, the following:
- Advanced reliability analysis techniques: Novel methods for assessing and improving the reliability of mechanical systems.
- Predictive maintenance and condition monitoring: Strategies for the real-time monitoring and predictive maintenance of mechanical systems.
- Digital twins in mechanical systems: Application of digital twins for the simulation, monitoring, and optimization of mechanical systems.
- Machine learning and AI in reliability engineering: Use of machine learning and AI for fault detection, diagnosis, and prognosis in mechanical systems.
- Reliability-based design optimization: Integration of reliability analysis into the design optimization process.
- Risk assessment and management: Techniques for risk assessment and management in mechanical systems.
- Sustainability and reliability: Approaches to enhancing the sustainability of mechanical systems using reliability analysis.
- Case studies and practical applications: Real-world applications and case studies demonstrating the impact of reliability and mechanical system innovations.
Dr. Feng Zhang
Dr. Feifei Zhao
Dr. Fan Yang
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. Machines 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
- reliability analysis
- mechanical systems
- predictive maintenance
- digital twins
- machine learning
- risk assessment
- sustainability
- system optimization
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