Innovative Approaches to Modeling, Optimization, Control, and Monitoring in Industrial Processes
A special issue of Processes (ISSN 2227-9717). This special issue belongs to the section "Process Control and Monitoring".
Deadline for manuscript submissions: 31 October 2025 | Viewed by 304
Special Issue Editors
Interests: optimal control; adaptive control; predictive control, learning control, optimization, and their industrial applications
Interests: data driven soft sensing; fault detection & diagnosis; multimodal machine learning; industrial AI
Interests: artificial intelligence; industrial big data; process monitoring; fault diagnosis; soft sensing; data model security
Special Issue Information
Dear Colleagues,
Innovative modeling, optimization, control, and monitoring methods are essential for modern industrial processes, enhancing efficiency and sustainability in a competitive landscape. Advanced modeling techniques enable a detailed understanding of complex industrial systems, while optimization methods refine and enhance process performance. In particular, cutting-edge control strategies ensure system stability, adaptability, and safety, while real-time monitoring technologies provide actionable insights for improved decision-making and operational reliability and safety. Together, these methods help industries boost productivity, reduce waste, save costs, and comply with strict environmental and quality standards.
Furthermore, the era of Big Data and the rise of machine learning approaches has further transformed modeling and optimization in industrial processes. By analyzing large volumes of operational data, these methods reveal hidden patterns, offering a deeper understanding of system dynamics. Integrating innovative modeling with optimization and control frameworks is crucial for addressing challenges like process uncertainty and nonlinearity. Advanced monitoring techniques, enhanced by digital tools, facilitate predictive maintenance, reduce downtime, and improve safety. However, a significant gap remains between theoretical frameworks and practical applications. Bridging this gap is essential for advancing the field and ensuring that innovative solutions meet the challenges faced by modern industries.
This Special Issue, ‘Innovative Approaches to Modeling, Optimization, Control, and Monitoring in Industrial Processes’, aims to highlight original research contributions focused on practical applications. Topics include the following:
- The development of novel modeling techniques for complex industrial processes, including chemical, energy, and manufacturing systems.
- Advanced optimization methods for process improvement, scheduling, and resource allocation.
- State-of-the-art control strategies for nonlinear, high-dimensional, or uncertain systems.
- Safety control theories and applications for industrial processes.
- Innovative monitoring technologies for real-time analysis, fault detection, and predictive maintenance.
- Security and robustness of data-driven models in process monitoring systems.
- The integration of modeling, optimization, and control for sustainable energy-efficient processes.
- Case studies showcasing the applications of innovative methodologies to real-world industrial challenges.
Prof. Dr. Yuanqiang Zhou
Dr. Le Yao
Dr. Xiaoyu Jiang
Dr. Zheren Zhu
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 100 words) can be sent to the Editorial Office for announcement on this website.
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.
Keywords
- process modeling
- process optimization
- process control
- process monitoring
- process system engineering
- machine learning
- big data
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