Advances in Failure Detection and Diagnostic Strategies: Enhancing Reliability and Safety
A special issue of Computers (ISSN 2073-431X).
Deadline for manuscript submissions: 31 December 2025 | Viewed by 822
Special Issue Editor
2. Cybersecurity at MIT Sloan (CAMS), Massachusetts Institute of Technology, 77 Massachusetts Ave., Cambridge, MA 02139, USA
Interests: failure detection; diagnosis; vibration analysis; digital image processing; advanced data analytics; artificial intelligence
Special Issue Information
Dear Colleagues,
With the proliferation of sensors, real-time data collection, and databases of maintenance actions, there has never been as much data available for monitoring, anomaly detection, diagnosis, prediction, failure of accident prevention, and for optimizing maintenance. All the data available, along with powerful tools based on machine learning and artificial intelligence for their analysis, significantly contribute to improvements in diagnosis in many different fields, as well as contributing to anticipating failures and reducing operating and maintenance costs. The benefits of these new analysis strategies help to avoid unexpected failures, improving the reliability and safety of systems while reducing costs related to unavailability and expensive unplanned repairs. In addition, monitoring, detection, diagnosis, and prediction can be applied to a variety of fields including medical diagnosis, telemedicine, signal processing, defect detection in materials, or education.
This Special Issue seeks articles that present and evaluate novel approaches of data acquisition and analysis, with the objective of improving diagnosis, preventing failures, optimizing maintenance, and minimizing costs. We also invite papers submissions that explore innovative technologies in this field.
Potential topics include the following:
- Diagnostic strategies;
- Incipient failure detection;
- Reliability engineering;
- Signal analysis for anomaly detection;
- Medical diagnosis using soft computing techniques;
- Telemedicine and remote monitoring;
- Condition monitoring;
- Prognostics and health management (PHM);
- Reliability enhancement;
- Accident prevention;
- Fault-tolerant systems;
- Defect detection on materials;
- Data-driven maintenance;
- AI and IoT;
- Digital twins;
- Prevention and detection of cyber attacks.
Dr. Rafael Palacios
Guest Editor
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. Computers 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 1800 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
- incipient failure detection
- diagnostic strategies
- reliability engineering
- anomaly detection
- condition monitoring
- prognostics and health management (PHM)
- reliability enhancement
- data-driven maintenance
- AI and IoT
- digital twins
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