2023
DOI: 10.3390/ma16134610
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Additive Manufacturing Post-Processing Treatments, a Review with Emphasis on Mechanical Characteristics

Abstract: Additive manufacturing (AM) comes in various types of technologies and comparing it with traditional fabrication methods provides the possibility of producing complex geometric parts directly from Computer-Aided Designs (CAD). Despite answering challenges such as poor workability and the need for tooling, the anisotropy of AM constructions is the most serious issue encountered by their application in industry. In order to enhance the microstructure and functional behavior of additively fabricated samples, post… Show more

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Cited by 36 publications
(7 citation statements)
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“…In addition, Figure 11 shows how many samples in the series exhibited the specified behavior and found that almost equal numbers of samples exhibited the listed behaviors. Moreover, when comparing Figure 12 and Figure 13 , it is seen that the heat treatment caused the unification of the structure of the samples, relief of the residual stress, and elimination of internal defects and structural distortions [ 24 , 25 ]. Therefore, the PEKK HT samples did not exhibit brittle behavior and showed higher values of Young’s modulus and elongation at a break compared to PEKK, about 3381 MPa and 42%, respectively.…”
Section: Resultsmentioning
confidence: 99%
“…In addition, Figure 11 shows how many samples in the series exhibited the specified behavior and found that almost equal numbers of samples exhibited the listed behaviors. Moreover, when comparing Figure 12 and Figure 13 , it is seen that the heat treatment caused the unification of the structure of the samples, relief of the residual stress, and elimination of internal defects and structural distortions [ 24 , 25 ]. Therefore, the PEKK HT samples did not exhibit brittle behavior and showed higher values of Young’s modulus and elongation at a break compared to PEKK, about 3381 MPa and 42%, respectively.…”
Section: Resultsmentioning
confidence: 99%
“…Vibration data can help identify any anomalies, such as excessive vibrations or oscillations that may affect the surface roughness. In the FDM-based 3D printing process, for instance, vibration data were integrated to monitor the vibration of the extruder and the table [ 67 ]. Vibration data can also be integrated into the machine learning models to enhance the accuracy of surface roughness predictions and further optimize the additive manufacturing process.…”
Section: Ai-based Surface Roughness Prediction Overviewmentioning
confidence: 99%
“…Furthermore, post-build treatments significantly contribute to the final surface quality of additively manufactured components [ 65 , 66 ]. For example, it can significantly improve the mechanical properties, i.e., surface roughness of the parts, making them more suitable for a wide range of applications [ 67 ]. Different post-processing techniques have been used by many researchers, such as shot peening (SP), laser shock peening (LSP), hot isostatic pressing (HIP), friction stir processing (FSP), and heat treatments (HT), to realize the better performance of the AM parts [ 66 ].…”
Section: Introductionmentioning
confidence: 99%
“…Ultem’s inherent shape-memory properties allow it to return to a predefined shape after deformation, a significant attribute for adaptive filtration systems. , This combined with its self-healing capabilities extends its longevity and performance under challenging conditions. Furthermore, its remarkable mechanical strength ensures the stability and integrity of the adsorbent, even under the stress of high adsorbate loadings. Moreover, the presence of diverse functional groups in Ultem may allow for potential interactions with DMMP, thus enhancing the adsorption efficacy. Economically, Ultem stands out for being cost-effective and straightforward to prepare. , Crucially, Ultem facilitates nondestructive adsorption of DMMP, preserving the molecular integrity of the adsorbate, which is pivotal for subsequent analytical or decontamination processes.…”
Section: Introductionmentioning
confidence: 99%