Advances in Metal Rolling Process: Modelling, Analysis, and Application
A special issue of Materials (ISSN 1996-1944). This special issue belongs to the section "Manufacturing Processes and Systems".
Deadline for manuscript submissions: 20 May 2025 | Viewed by 309
Special Issue Editors
Interests: rolling; roll pass design; dynamic fracture; residual stress
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Advances in Metal Rolling Process: Modelling, Analysis, and Application focuses on various innovations, including:
- Material Flow Models: These predict metal behavior during deformation, such as elongation, grain refinement, and phase transformations, especially in hot rolling.
- Machine Learning Models: AI techniques, like machine learning, are used to predict rolling process outcomes based on large sets of experimental or simulation data, aiding in optimization and quality control.
- Innovative Process Analysis: Studying factors like roll force, temperature management, friction, advanced lubrication and residual stresses enhances process control and product quality, and reduce defects and energy consumption.
- Advanced Materials: These include rolling advanced high-strength steels (AHSS), titanium alloys, and other specialty materials used in high-performance industries such as aerospace, defense, and energy.
- Automation and Smart Rolling Mills: The integration of automation and real-time data acquisition enables continuous process monitoring and adjustments, leading to improved product consistency and reduced waste.
This field combines advanced modeling, real-time data, and material science to advance the limits of metal rolling.
Prof. Dr. Youngseog Lee
Dr. Sangmin Byon
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.
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Keywords
- smart mills
- automation
- machine learning
- energy efficiency
- process optimization
- surface quality
- advanced materials
- material flow
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