Additive Manufacturing: Experiments, Simulations and Data-Driven Modelling (Second Edition)
A special issue of Crystals (ISSN 2073-4352). This special issue belongs to the section "Crystalline Metals and Alloys".
Deadline for manuscript submissions: 20 April 2025 | Viewed by 122
Special Issue Editors
Interests: additive manufacturing; laser-material interaction; tribology; process automation, modelling
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Interests: additive manufacturing; 3D printing; coating; metals; concrete; ceramics; AM experiments; simulations; machine learning; smart manufacturing; process parameters optimization
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Interests: sustainable and smart manufacturing; materials for energy applications; materials processing; integration of mechanics and materials in manufacturing
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2. Additive Manufacturing Technologies Research and Application Center-EKTAM, Gazi University, 06560 Ankara, Turkey
3. Manufacturing Technologies Center of Excellence-URTEMM A.S., 06980 Ankara, Turkey
Interests: non-traditional manufacturing methods; machine; theory and dynamics; machine dynamics; system dynamics and control; mechatronics; modelling and simulation of dynamic systems; mechanical vibrations
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Interests: organic/inorganic membranes applications; surface modification of nanoparticles; bioconversion
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Interests: developing mechanical and energy technologies for various applications
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Interests: experimental optics; spectroscopy; lasers and plasma; surface studies and processing with lasers; laser interactions; lasers and plasma physics; nanostructured thin-film technology (PLD, MAPLE, and combinatorial); surface physics and engineering; biophysics and biomedicine; nano-biotechnologies; gas- and biosensors; plasma and laser theory
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Interests: additive manufacturing; laser metal processing; biocompatible materials; surface microstructuring; deposition and modification of thin solid structures via high intensity laser irradiation
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Interests: laser processing; nuclear physics and relativity
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Interests: pulsed laser deposition; modification and characterization of nanostructured thin coatings; matrix-assisted pulsed laser evaporation (MAPLE); laser surface studies and processing; biomaterials thin layers; tissue engineering; biomimetic metallic implants; optoelectronics and sensors
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Interests: metal additive manufacturing (AM); novel AM process development and process planning; rapid prototyping; multiscale multiphysics AM process modeling; remanufacturing automation; AM process monitoring and control; digital materials processing
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Special Issue Information
Dear Colleagues,
Additive manufacturing (AM) utilizes a layer-upon-layer technique to produce three-dimensional (3D) components via a computer-aided design (CAD) model, promising manufacturing advantages compared to conventional approaches, such as manufacturing intricate geometries, controlling the heat-affected zone, and removing numerous technological steps, thus reducing the final manufacturing cost. AM has been explored in automotive, biomedical, aerospace, and industrial applications based on the facts mentioned above, and it has been widely applied to various materials, including metals, ceramics, polymers, and ceramic-reinforced metal matrix composites (CMMCs), a mixture of metals and ceramics. In AM, operating conditions influence the properties of the manufactured parts and the in-service life. One way to determine the optimum operating conditions is to conduct a series of experiments by utilizing the trial-and-error method, increasing the manufacturing direct and indirect costs. On the other hand, this can be performed by using an experimentally validated simulation model linked with data-driven models (machine learning), leading towards smart manufacturing.
The primary purpose of this Special Issue of Crystals, titled “Additive Manufacturing: Experiments, Simulations and Data-driven Modelling”, is to deliver an intercontinental forum for ground-breaking research on process parameters’ optimization, the development of new alloys and compounds, ceramics and CMMCs for AM experiments, sophisticated simulation model development, and the implementation of machine learning in AM processes.
Dr. Muhammad Arif Mahmood
Dr. Asif Ur Rehman
Prof. Dr. Marwan Khraisheh
Prof. Dr. Metin U. Salamci
Dr. Rashid Ur Rehman
Dr. Uzair Sajjad
Dr. Carmen Ristoscu
Dr. Andrei C. Popescu
Dr. Mihai Oane
Prof. Dr. Ion N. Mihailescu
Prof. Dr. Frank Liou
Guest Editors
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Keywords
- additive manufacturing
- metals
- ceramics
- ceramic-reinforced metal matrix composites
- experiments
- simulations
- machine learning
- process parameters optimization
- smartification of additive manufacturing
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