Intelligent Process Planning for Smart Manufacturing Systems
A special issue of Machines (ISSN 2075-1702). This special issue belongs to the section "Advanced Manufacturing".
Deadline for manuscript submissions: 31 March 2026 | Viewed by 1
Special Issue Editors
Interests: intelligent product design; manufacturing execution system; industrial production service system; social manufacturing
Special Issues, Collections and Topics in MDPI journals
Interests: social manufacturing; intelligent manufacturing; industrial engineering; cyber–physical–social systems; product collaborative design
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Process planning mainly involves determining the required equipment, operational sequences, machining process, parameters, and related factors necessary to produce specific parts or product components. The outcomes of process planning influence not only product quality but also the efficiency and cost-effectiveness of the entire production process. In practical tasks, computer-aided process planning techniques are usually applied to reuse historical process data, improve planning efficiency, and reduce reliance on human expertise. Generally, computer-aided process planning can be categorized into retrieval-based, derivative, generative, and hybrid approaches. In recent years, the rapid development of both small and large AI models has introduced new opportunities and directions for process planning. Against this backdrop, this Special Issue aims to bring together researchers to present advanced theories and technologies in the field of intelligent process planning, particularly in the context of smart manufacturing systems. The topics of interest include, but are not limited to:
- Knowledge base construction for intelligent process planning;
- Adaptive and dynamically evolving reasoning models for intelligent process planning;
- Application of large language models in intelligent process planning;
- Process planning for additive manufacturing;
- Evaluation of process planning results and feedback-driven improvement.
Dr. Maolin Yang
Prof. Dr. Pingyu Jiang
Guest Editors
Manuscript Submission Information
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Keywords
- intelligent process planning
- artificial intelligence
- large language model
- smart manufacturing
- intelligent manufacturing
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