Fault Detection for Predictive Maintenance Applications in Control Engineering

Dear Colleagues,

This Special Issue highlights the latest advancements in fault detection techniques for predictive maintenance in control engineering systems. As industries become more dependent on automation and complex control processes, it is essential to catch faults early to avoid unexpected interruptions, cut down on maintenance costs, and enhance safety. We are interested in innovative approaches such as data-driven algorithms, machine learning, sensor fusion, and signal processing that help identify issues quickly and accurately. The focus is on real-time fault monitoring, improving diagnostic precision, and integrating these methods into broader maintenance strategies. Contributions can include research articles, case studies, and reviews that showcase both traditional and emerging solutions, tackling challenges like noise interference, system scalability, and computational demands. The aim is to support the development of reliable, autonomous fault detection systems that help make control operations more sustainable and cost-efficient.

Dr. Mohamad Nassereddine
Dr. Obada Al Khatib
Dr. Ali Hellany
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. Processes 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.