Modeling, Design, Optimization and Maintenance of Intelligent Manufacturing towards Industry 5.0
A special issue of Processes (ISSN 2227-9717). This special issue belongs to the section "Manufacturing Processes and Systems".
Deadline for manuscript submissions: 31 March 2025 | Viewed by 62
Special Issue Editors
Interests: testability design; data-driven-based fault detection and isolation (FDI); system control and optimization; PHM
Special Issues, Collections and Topics in MDPI journals
Interests: intelligent manufacturing; intelligent control and systems; intelligent monitoring and fault diagnosis; prognostic and health management
Interests: hybrid uncertainties; decision-making for complex networks; machine learning
Interests: data-driven complex nonlinear dynamic modelling; integrated learning optimization control of intermittent production processes; energy internet collaborative optimization based on big data
Special Issue Information
Dear Colleagues,
As the industrial sector progresses toward Industry 5.0, intelligent manufacturing systems’ modeling, design, optimization, and maintenance have garnered increasing scholarly attention. This evolution emphasizes the integration of advanced cyber–physical systems, artificial intelligence, and human-centric technologies to foster sustainability, efficiency, and resilience in production processes. Central to this paradigm shift are the principles of process modeling, multi-objective optimization, and predictive maintenance, which are applied across various scales—from individual unit operations to entire manufacturing ecosystems. These methodologies aim to enhance resource utilization, minimize energy consumption, and improve system adaptability. Industry 5.0 represents a convergence of human ingenuity and machine precision, leading to a synergistic enhancement of manufacturing capabilities that transcends the limitations of traditional industrial frameworks.
This Special Issue entitled “Modeling, Design, Optimization and Maintenance of Intelligent Manufacturing towards Industry 5.0” seeks high-quality works focusing on the latest novel advancements in technology for intelligent manufacturing systems. Topics include, but are not limited to, methods and/or application in the following areas:
- Smart manufacturing;
- Industrial fault diagnostics and prognosis;
- Predictive maintenance;
- Industrial reliability assessment;
- AI-driven optimization;
- Digital twins;
- Human–AI collaboration;
- Industrial IoT;
- Data-driven decision-making.
Dr. Yang Li
Dr. Cunsong Wang
Dr. Yan Shi
Prof. Dr. Li Jia
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
- intelligent monitoring and maintenance
- prognostic and health management
- reliability assessment
- online soft measurement
- intelligent management and control
- Industrial Internet of Things
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