Development and Implementation of Digital Twins for Industrial Processes
A special issue of Processes (ISSN 2227-9717). This special issue belongs to the section "Manufacturing Processes and Systems".
Deadline for manuscript submissions: 15 January 2026 | Viewed by 16
Special Issue Editors
Interests: modeling; simulation and control of chemical reactors; in-line monitoring and control of chemical processes; real-time optimization of chemical processes; numerical techniques and procedures for real-time applications
Special Issues, Collections and Topics in MDPI journals
2. Programa de Engenharia Química/COPPE, Universidade Federal do Rio de Janeiro, Rio de Janeiro 21921-972, RJ, Brazil
Interests: process control; MPC/NMPC; data-based methods for monitoring and control; fault detection and diagnosis; chemical and biochemical processes; process system engineering; process control artificial intelligence; neural networks autonomous systems
Special Issues, Collections and Topics in MDPI journals
Interests: dynamic optimization; real-time monitoring and control systems; optimal control; machine learning; hybrid models; modeling and simulation of particulate systems
Special Issue Information
Dear Colleagues,
The concept of a digital twin (DT) involves the digital transformation of a physical system. The virtual models of physical entities are key aspects of a DT. The fast development of computational capabilities and numerical procedures encourages the construction of mathematical models of different complexities for the representation of process behavior for different services of the DT, including monitoring, control, optimization and design. As industrial processes normally involve multiple input and output variables and present a nonlinear character, the demand for such process models has grown steadily over the last few years. These models have to be calibrated/updated as the physical twin evolves over time, and machine learning techniques can help with that purpose. Other central components of digital twins are real-time and historical data, the integration architecture and communication protocols. Considering this scenario, this Special Issue of Processes is dedicated to the discussion of matters related to the development and application of digital twins in real industrial environments. Topics of interest involve (but are not limited to) the following:
- Development and validation of innovative models for representation of actual industrial processes;
- Development and implementation of innovative numerical procedures for the solution of mathematical models used to represent actual industrial processes;
- Use of digital twins for purposes of monitoring, diagnosis, prognostics and health management, control, optimization and design of actual industrial processes;
- Development and implementation of software platforms used to allow the online and real-time implementation of digital twins in industrial environments;
- Comparative performance analyses of different digital twin approaches;
- Development and application of KPIs (key performance indicators) for evaluation of digital twin efficiency and performance;
- Development and implementation of strategies for fitting and training digital twins, based on both phenomenological and machine learning approaches.
- Development and validation of innovative methodologies using large language models (LLM) to enhance DT capabilities.
Prof. Dr. Jose Carlos Pinto
Prof. Dr. Maurício Bezerra De Souza, Jr.
Prof. Dr. Marcellus G. F. De Moraes
Dr. Maurício M. Câmara
Guest Editors
Manuscript Submission Information
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Keywords
- digital twin
- modeling
- simulation
- monitoring
- control
- optimization
- machine learning
- real-time
- industrial process
- industrial digitalization
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