Digital Twin and Artificial Intelligence for Prognostics and Health Management

Dear Colleagues,

We are pleased to invite you to contribute to a Special Issue on "Digital Twin and Artificial Intelligence for Prognostics and Health Management". This Special Issue explores the transformative potential of digital twin technology and artificial intelligence (AI) in advancing the field of Prognostics and Health Management (PHM), emphasizing the critical role of mathematical models and methods in enhancing predictive capabilities, reliability, and efficiency.

In recent years, the integration of digital twin systems and AI has revolutionized industries by enabling real-time monitoring, fault detection, and predictive maintenance. However, achieving accurate and reliable PHM outcomes requires addressing key challenges, such as the development of robust mathematical frameworks, optimization techniques, and scalable AI models. This Special Issue aims to gather groundbreaking research that integrates mathematical methods including statistical modeling, optimization algorithms, and simulation techniques with advanced AI to address these challenges and enable intelligent decision-making in PHM.

In this Special Issue, we welcome original research articles and reviews. Research areas may include (but are not limited to) the following:

• Digital Twin modeling and its applications in PHM;
• AI-driven predictive maintenance for smart factories;
• Mathematical optimization methods for enhancing AI performance;
• Prognostics and fault detection in robotics and composite materials;
• Data-driven techniques for real-time health monitoring;
• Statistical approaches to uncertainty quantification in PHM systems;
• Development of scalable AI models for complex industrial systems;
• Case studies on the implementation of digital twin and AI in PHM applications.

This Special Issue will serve as a platform to advance the knowledge and application of digital twin and AI technologies in PHM, focusing on their mathematical underpinnings and practical implications across diverse domains, including smart factories, robotics, and composite materials.

We look forward to your valuable contributions to this Special Issue and hope to advance this exciting field together.

Prof. Dr. Chang Wan Kim
Dr. Izaz Raouf
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-anonymized 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.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 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.