Digital Twins for Sustainable Industrial Processes

Dear Colleagues,

The rapid evolution of industrial processes has underscored the importance of integrating advanced technologies to achieve sustainability, efficiency, and resilience. Among these advancements, Digital Twins have emerged as transformative tools, enabling real-time data integration, predictive analytics, and enhanced decision-making capabilities across various industrial domains. By bridging the physical and digital worlds, Digital Twins allow for the monitoring, simulation, and optimization of processes, fostering sustainability by minimizing resource consumption, reducing emissions, and improving operational performance. As industries focus on meeting global sustainability goals, the use of Digital Twins presents extraordinary opportunities to transform processes and systems.

This Special Issue on “Digital Twins for Sustainable Industrial Processes” seeks high-quality contributions that explore the development, application, and impact of Digital Twins in promoting sustainable industrial practices. The objective is to advance knowledge and innovation in this field, providing a platform for interdisciplinary research and practical insights that address current challenges and future opportunities. Submissions are encouraged to focus on the creation, integration, and utilization of Digital Twins, as well as the methodologies and technologies that support their deployment in industrial contexts.

Topics include, but are not limited to, the following:

• The development of Digital Twins for the real-time monitoring and optimization of industrial processes;
• Methodologies for integrating Digital Twins with sustainability assessments, such as life cycle assessment (LCA) or life cycle sustainability assessment (LCSA);
• Applications of Digital Twins to reduce resource consumption and emissions across industries;
• Case studies demonstrating the deployment of Digital Twins in energy-intensive sectors;
• Innovations in sensor integration, data acquisition, and machine learning for Digital Twin implementation;
• Simulation and modeling techniques to support Digital Twin functionalities;
• Role of Digital Twins in achieving circular economy goals;
• Interdisciplinary approaches combining Digital Twins with IoT, Blockchain, or Artificial Intelligence for sustainable industrial applications.

We invite researchers and practitioners from diverse backgrounds to contribute original research articles, reviews, and case studies that align with the scope of this Special Issue.

Thank you for considering this Special Issue, and I look forward to your valuable contributions.

Sincerely,

Dr. Karoline Figueiredo
Dr. Ana Evangelista
Dr. Arti M. Siddhpura
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 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.