Industrial IoT-Enabled Modeling and Optimization for the Process Industry—2nd Edition
A special issue of Processes (ISSN 2227-9717). This special issue belongs to the section "Process Control and Monitoring".
Deadline for manuscript submissions: 10 November 2025 | Viewed by 358
Special Issue Editors
Interests: industrial big data; optimization and scheduling; modeling and simulation
Special Issues, Collections and Topics in MDPI journals
Interests: modeling, simulation, and optimization of manufacturing and energy systems
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Due to the success of the first edition in terms of both the quantity and the quality of the published papers, the Guest Editors are happy to announce a second edition of the Special Issue “Industrial IoT-Enabled Modeling and Optimization for the Process Industry”.
The application of intelligence in manufacturing has emerged as a compelling topic for researchers and industries around the world. Given severe resource and market pressure, there is an urgent need to improve the efficiency and decarbonization of industries through smart manufacturing strategies. Industrial IoT represents the core of smart manufacturing through integrating advanced sensing, communication, and data mining technologies. With the development of artificial intelligence (AI) techniques, including machine learning (ML), reinforcement learning (RL), and large language models (LLMs), the integration of Industrial IoT into AI has shown great potential in addressing these challenges. It facilitates complicated decision making in all aspects of the production process, including supply chains, product quality, energy scheduling, and equipment diagnosis, through the acquisition and utilization of whole-process data. AI techniques have greatly facilitated the modeling and optimization of manufacturing processes but also involve a number of challenges, e.g., how to integrate mechanism knowledge into industrial big data in the modeling of industrial processes and how to deal with multiple and coupled objectives in the optimization of the production process.
This Special Issue will summarize new theories and their applications in industrial IoT-enabled modeling and optimization, especially in industry applications. Possible topics include, but are not limited to, the following:
- Industrial IoT-enabled process modeling;
- Process monitoring and fault diagnosis;
- Industrial process optimization;
- Production and logistics optimization;
- Smart manufacturing;
- Machine learning applications in smart manufacturing;
- LLM applications in smart manufacturing.
Dr. Gongzhuang Peng
Dr. Shenglong Jiang
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
- production planning and scheduling
- process optimization
- artificial intelligence
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