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[HTML][HTML] 3D printing of biodegradable polymers and their composites–Current state-of-the-art, properties, applications, and machine learning for potential future …
This review paper comprehensively examines the dynamic landscape of 3D printing and
Machine Learning utilizing biodegradable polymers and their composites, presenting a …
Machine Learning utilizing biodegradable polymers and their composites, presenting a …
[HTML][HTML] Machine learning in Directed Energy Deposition (DED) additive manufacturing: A state-of-the-art review
Abstract Directed Energy Deposition (DED) has become very popular for repair and rapid
prototy** in metal manufacturing industries. However, as an anisotropic and defect-prone …
prototy** in metal manufacturing industries. However, as an anisotropic and defect-prone …
Probabilistic digital twin for additive manufacturing process design and control
This paper proposes a detailed methodology for constructing an additive manufacturing
(AM) digital twin for the laser powder bed fusion (LPBF) process. An important aspect of the …
(AM) digital twin for the laser powder bed fusion (LPBF) process. An important aspect of the …
Machine learning in biomaterials, biomechanics/mechanobiology, and biofabrication: State of the art and perspective
In the past three decades, biomedical engineering has emerged as a significant and rapidly
growing field across various disciplines. From an engineering perspective, biomaterials …
growing field across various disciplines. From an engineering perspective, biomaterials …
State-of-art review on the process-structure-properties-performance linkage in wire arc additive manufacturing
H Zhang, R Li, J Liu, K Wang, Q Weijian… - Virtual and Physical …, 2024 - Taylor & Francis
ABSTRACT Wire Arc Additive Manufacturing (WAAM) can well offer improved design
flexibility and manufacturing versatility for the integrated molding of large components …
flexibility and manufacturing versatility for the integrated molding of large components …
Guided probabilistic reinforcement learning for sampling-efficient maintenance scheduling of multi-component system
In recent years, multi-agent deep reinforcement learning has progressed rapidly as reflected
by its increasing adoptions in industrial applications. This paper proposes a Guided …
by its increasing adoptions in industrial applications. This paper proposes a Guided …
[HTML][HTML] Human-in-the-loop Multi-objective Bayesian Optimization for Directed Energy Deposition with in-situ monitoring
Abstract Directed Energy Deposition (DED) is a free-form metal additive manufacturing
process characterized as toolless, flexible, and energy-efficient compared to traditional …
process characterized as toolless, flexible, and energy-efficient compared to traditional …
[HTML][HTML] Data-driven prediction and uncertainty quantification of process parameters for directed energy deposition
Laser-based directed energy deposition using metal powder (DED-LB/M) offers great
potential for a flexible production mainly defined by software. To exploit this potential …
potential for a flexible production mainly defined by software. To exploit this potential …
A Review of Generative Design Using Machine Learning for Additive Manufacturing
P Koul - Advances in Mechanical and Materials Engineering, 2024 - journals.prz.edu.pl
This review explores how generative design is combined with machine learning (ML) to
achieve additive manufacturing (AM) and its societal transformative effect. Generative …
achieve additive manufacturing (AM) and its societal transformative effect. Generative …