Intelligent Operation, Maintenance, and Scheduling of Industrial Manufacturing Processes
A special issue of Processes (ISSN 2227-9717). This special issue belongs to the section "Manufacturing Processes and Systems".
Deadline for manuscript submissions: 31 May 2026 | Viewed by 138
Special Issue Editors
Interests: cybersecurity and privacy; efficient deep learning; sustainable manufacturing
Special Issues, Collections and Topics in MDPI journals
Interests: machine learning; software engineering; discrete event systems; formal methods; wireless networking; real-time distributed systems
Special Issues, Collections and Topics in MDPI journals
2. Department of Electrical and Computer Engineering, New Jersey Institute of Technology, Newark, NJ 07102, USA
Interests: deep reinforcement learning; intelligent optimization algorithms; autonomous vehicles; detection model; artificial intelligence; intelligent manufacturing
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Industrial manufacturing processes, including process manufacturing and discrete manufacturing, are complex systems in the real world. Operation, maintenance, and scheduling problems are crucial to an industrial manufacturing process, affecting its efficiency, energy consumption, production costs, safety and stability. In recent years, the theory and technology of artificial intelligence have been evolving rapidly. Applications of artificial intelligence technology, like deep learning, machine learning, evolutionary computation, and heuristic algorithms, are gradually affecting all walks of life in the real world. Integrating artificial intelligence technology with specific industrial manufacturing processes to solve its intelligent operation, maintenance, and scheduling problems is an important demand of industry and a growing research field in academia. Related research can improve operation efficiency, ensure safety and stability, and save energy consumption and production costs, which can further improve the level of intelligent manufacturing in an industrial manufacturing process. While there has been some existing research on these challenges, a lot of related problems issues remain unsolved.
This Special Issue provides a platform to exchange research works, technical trends and practical experience related to fault diagnosis, process control, operation research, applied mathematics and management science. The goal is to broaden the intelligent manufacturing research community and promote the application of artificial intelligence in industrial manufacturing processes. Topics to be covered include, but are not limited to, the following:
- Design, control and optimization of assembly systems
- Design, control and optimization of disassembly systems
- Digital twin techniques in manufacturing
- Emission control and energy saving in manufacturing
- End-of-life product recycling
- Formal methods in the modeling, verification and analysis of manufacturing systems, such as Petri nets, finite automata, UML, queuing theory, model checking techniques, etc.
- Heuristic search algorithms
- Intelligent factory
- Real-time task allocation
- Real-time task scheduling
- Machine learning and reinforcement learning in manufacturing
- Smart sensing and control
- Smart logistics management
- System simulation and performance evaluation
- Sustainability manufacturing
- Workstation load balancing in manufacturing, assembly and disassembly
Dr. Bin Hu
Prof. Dr. Jiacun Wang
Dr. Xiwang Guo
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 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 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
- intelligent manufacturing
- human–robot collaboration
- disassembly line optimization
- artificial intelligence and machine learning
- smart sensing and control
- real-time scheduling and operation
- sustainable manufacturing
- digital twin and system simulation
- energy-efficient production
- heuristic and evolutionary optimization
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