System Reliability and Predictive Maintenance in Industrial Engineering—2nd Edition
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Applied Industrial Technologies".
Deadline for manuscript submissions: 30 November 2025 | Viewed by 54
Special Issue Editors
Interests: industrial plant engineering; industrial reliability; safety and maintenance of industrial plants; job safety; multicriteria decision making methodologies applied to industrial plant engineering and operations
Special Issues, Collections and Topics in MDPI journals
Interests: industrial plant engineering; maintenance; industrial safety and risk; reliability; manufacturing systems; additive manufacturing
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
We are pleased to announce the second edition of a Special Issue that will bring together cutting-edge research, innovative methodologies, and practical applications in the field of system reliability and predictive maintenance.
Today, companies focus on achieving operational excellence by optimizing the performances of physical assets. A critical element in achieving this goal is ensuring high levels of asset reliability and availability, leveraging technological evolution in ICTs and system automation. The widespread integration of sensors and monitoring systems in industrial plants, coupled with artificial intelligence (AI) and data-driven tools and techniques, allow decision-makers to access real-time data on operating conditions, performance, and safety. Furthermore, these technologies provide advanced forecasting capabilities for more efficient and effective maintenance decisions.
The Special Issue is open to contributions from both academics and industry engineers who want to share their experiences, insights, and research findings. It will discuss state-of-the-art approaches, methods, tools, and techniques in systems reliability and predictive maintenance.
Topics
We welcome original and high-quality contributions that explore innovative solutions, methodologies, and industrial applications in predictive maintenance and system reliability. Topics of interest include, but are not limited to, the following:
- Predictive maintenance and Analytics: Data-driven and AI-driven predictive maintenance techniques for industrial systems; artificial intelligence (AI) for reliability analysis; machine learning (ML) for maintenance decisions; big data and asset performance management; operational benefits of predictive maintenance strategies.
- Condition monitoring and Diagnostics: Real-time monitoring; anomaly detection; fault diagnosis of assets/equipment.
- Risk based reliability: Reliability allocation and optimization; reliability for business continuity; innovative computing technologies in reliability; reliability for safety.
- Digital twins and Advanced Simulations: Research and development of digital twins for predictive maintenance and decision support.
- IoT and Industry 4.0 and 5.0 in Maintenance: IoT-enabled smart maintenance systems and their implementation in industrial plants; reliability of monitoring systems and sensor networks.
- Case Studies in Industrial Contexts.
Application Areas:
- Manufacturing industry.
- Chemical and process industry.
- Oil and gas industry.
- Energy production and distribution.
Dr. Natalia Trapani
Dr. Filippo De Carlo
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. Applied Sciences is an international peer-reviewed open access semimonthly 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
- system reliability
- predictive maintenance
- condition monitoring and diagnostics
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