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Additive manufacturing
ISSN 2214-7810 · Elsevier BV · 19 artikel di indeks
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Artikel Jurnal Teks lengkap
Research and application of machine learning for additive manufacturing
Additive manufacturing (AM) is poised to bring a revolution due to its unique production paradigm. It offers the prospect of mass customization, flexible production, on-demand and decentralized manufacturing. However, a number of challenges stem from not only the complexity of manufacturing systems…
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Lessons from nature: 3D printed bio-inspired porous structures for impact energy absorption – A review
As a result of their mechanical characteristics, biological structures often provide inspiration for the development of high-performance mechanical structures. Nevertheless, traditional production processes are often incapable of precisely reproducing the intricate and exquisite nature of…
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A review of Laser Powder Bed Fusion Additive Manufacturing of aluminium alloys: Microstructure and properties
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In-situ sensing, process monitoring and machine control in Laser Powder Bed Fusion: A review
Process monitoring and sensing is widely used across many industries for quality assurance, and for increasing machine uptime and reliability. Though still in the emergent stages, process monitoring is beginning to see strong adoption in the additive manufacturing community through the use of…
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Vat photopolymerization of polymers and polymer composites: Processes and applications
Synthesis and manufacturing of polymers and their composites have been a topic of interest recently in research and development owing to their wide margin of superiority over traditionally employed industrial materials. Polymer composites provide a higher strengths, easily customizable product…
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A review of multi-scale and multi-physics simulations of metal additive manufacturing processes with focus on modeling strategies
Numerical simulations have recently shown their potential as a robust, cheap and reliable tool for predicting the quality of components produced by metal additive manufacturing (MAM) processes. Despite the advantages of the MAM processes over conventional manufacturing methods, there is still a…
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Fused deposition modelling: Current status, methodology, applications and future prospects
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A machine learning method for defect detection and visualization in selective laser sintering based on convolutional neural networks
Part defects and irregularities that influence the part quality is an especially large problem in additive manufacturing (AM) processes such as selective laser sintering (SLS). Destructive and non-destructive testing procedures are currently mostly used for quality control and defect detection of…
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A comprehensive review of the photopolymerization of ceramic resins used in stereolithography
In recent years, there have been rapid advances in our understanding of ceramic stereolithography (CSL) as a precise and high-resolution additive manufacturing (AM) technique to fabricate complex ceramic parts. This review highlights the theoretical background and engineering capabilities of CSL…
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Defect structure process maps for laser powder bed fusion additive manufacturing
Accurate detection, characterization, and prediction of defects has great potential for immediate impact in the production of fully-dense and defect free metal additive manufacturing (AM) builds. Accordingly, this paper presents Defect Structure Process Maps (DSPMs) as a means of quantifying the…
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Machine learning in additive manufacturing: State-of-the-art and perspectives
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Hot isostatic pressing in metal additive manufacturing: X-ray tomography reveals details of pore closure
Hot isostatic pressing (HIP) of additively manufactured metals is a widely adopted and effective method to improve the density and microstructure homogeneity within geometrically-complex metal structures fabricated with laser powder bed fusion (LPBF). The role of pores in the fatigue performance of…
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Laser powder bed fusion of AA7075 alloy: Influence of process parameters on porosity and hot cracking
Laser powder bed fusion (LPBF) is an attractive technology of manufacturing high-strength aluminium alloy parts for the aircraft and automobile industries, limited by poor processability of these alloys. This work was aimed at finding the process window for the LPBF manufacturing of defect-free…
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Artikel Jurnal
Invited review: Machine learning for materials developments in metals additive manufacturing
In metals additive manufacturing (AM), materials and components are concurrently made in a single process as layers of metal are fabricated on top of each other in the near-final topology required for the end-use product. Consequently, tens to hundreds of materials and part design degrees of…