Advanced Materials, Machinability and Intelligent Manufacturing Systems.
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| Title: | Advanced Materials, Machinability and Intelligent Manufacturing Systems. |
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| Authors: | Burduk, Anna1 (AUTHOR) kamil.krot@pwr.edu.pl, Batako, Andre2 (AUTHOR), Michael, Anthony Xavior3 (AUTHOR), Butdee, Suthep4 (AUTHOR), Machado, Jose5 (AUTHOR), Krot, Kamil1 (AUTHOR) |
| Source: | Materials (1996-1944). Apr2026, Vol. 19 Issue 7, p1435. 5p. |
| Subjects: | Machining, Manufacturing process automation, Composite materials, Artificial intelligence, Smart materials, Machine learning, Electric metal-cutting, Sustainability |
| Abstract: | This article focuses on recent advances in the integration of advanced materials, machinability, and intelligent manufacturing systems, highlighting research that addresses challenges in processing high-performance materials and optimizing manufacturing processes. It discusses the application of machine learning and artificial intelligence methods to improve process prediction, decision support, and material selection in industries such as aerospace, automotive, and energy. Key contributions include studies on electrical discharge machining (EDM) optimization, manufacturability assessment for small-batch production, composite laminate reinforcement, adhesive joint quality, and sustainable thermal management materials. The article also reviews developments in metal forming models, ultrasonic liquid metal processing, and precision forming technologies relevant to emerging energy systems, emphasizing the growing role of intelligent computational tools in enhancing manufacturing efficiency and product reliability. [Extracted from the article] |
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| Database: | Engineering Source |
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| Abstract: | This article focuses on recent advances in the integration of advanced materials, machinability, and intelligent manufacturing systems, highlighting research that addresses challenges in processing high-performance materials and optimizing manufacturing processes. It discusses the application of machine learning and artificial intelligence methods to improve process prediction, decision support, and material selection in industries such as aerospace, automotive, and energy. Key contributions include studies on electrical discharge machining (EDM) optimization, manufacturability assessment for small-batch production, composite laminate reinforcement, adhesive joint quality, and sustainable thermal management materials. The article also reviews developments in metal forming models, ultrasonic liquid metal processing, and precision forming technologies relevant to emerging energy systems, emphasizing the growing role of intelligent computational tools in enhancing manufacturing efficiency and product reliability. [Extracted from the article] |
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| ISSN: | 19961944 |
| DOI: | 10.3390/ma19071435 |
