An investigation on wear characteristics of additive manufacturing materials

Kumar, Ayush; Choudhary, Abhishek; Tiwari, Abhishek; James, C.; Kumar, Harish; Arora, Pawan Kumar; Khan, Shahroz Akhtar

doi:10.1016/j.matpr.2021.01.263

Cited by 15 publications

(7 citation statements)

References 31 publications

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“…However, a relatively constant and high oxygen (32-35 wt%) level was shown that an oxide layer mostly covered the worn surface. Oxide can be generated between solid surfaces of the two frictional pairs due to the oxidative wear mechanism, especially under a high sliding distance designated in this study (2500 m) [64]. It can be concluded that the growth of oxide layers and adhesive transfer of material between the sample and wearing disc were the main dominant wear mechanisms under the 40 and 60 N applied loads regardless of the as-built microstructure [46].…”

Section: Correlation Of Worn Surface and Normal Applied Load With The...mentioning

confidence: 63%

“…Specifically, the lower microhardness in the building plane can be attributed to the coarsened microstructure localized inside the MPs. According to the Archard equation, hardness is inversely proportional to wear volume [63], significantly influencing the wear rate [64]. Hence, hardness can be considered an effective parameter and indicates a higher wear resistance in the scanning plane than in the building plane [65][66][67].…”

Section: Microhardnessmentioning

confidence: 99%

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Microstructure-induced anisotropic tribological properties of Sc-Zr modified Al–Mg alloy (Scalmalloy®) produced via laser powder bed fusion process

Abdi,

Salehi,

Fatemi

et al. 2023

Int J Adv Manuf Technol

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In this study, the correlation between the microstructure and tribological performance of Sc and Zr-modified Al–Mg alloy (Scalmalloy®) samples produced via laser powder bed fusion process was evaluated via a dry sliding Pin-on-Disc wear test under different planes, directions, and various normal applied loads. The results revealed a remarkable dependency of wear properties on the as-built microstructure so that different behaviors were observed along the scanning and building planes. The microstructural examination indicated the presence of bi-modal grains and finely shaped equiaxed grains observed in the building and scanning planes, respectively. Increasing the applied loads from 20 to 40 N led to a significant increase in the coefficient of friction (COF) while increasing the load from 40 to 60 N, slightly decreasing the COF for the studied samples. No dependency was found between the COF and the corresponding microstructure at the highest applied load. The anisotropic wear resistance and COF values were predominant at the lowest applied load. Due to tailored as-built microstructural features and different microhardness values, lower wear rates were noticed along the scanning plane for all applied loads. Under the 20 N applied load, however, the worn surface of the scanning plane showed a clearer and smoother surface compared to the building plane surfaces. Ultra-fine equiaxed grains along the scanning plane and columnar grains along the building plane were determined as the main factors creating anisotropic tribological behavior. The outcomes of this study can pave the way toward producing more wear-resistant surfaces and developing components for critical wear applications in as-built conditions with no need for expensive and time-consuming surface treatments.

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Section: Correlation Of Worn Surface and Normal Applied Load With The...mentioning

confidence: 63%

Section: Microhardnessmentioning

confidence: 99%

Microstructure-induced anisotropic tribological properties of Sc-Zr modified Al–Mg alloy (Scalmalloy®) produced via laser powder bed fusion process

Abdi,

Salehi,

Fatemi

et al. 2023

Int J Adv Manuf Technol

View full text Add to dashboard Cite

show abstract

“…However, the approach based on quantum neural networks requires further improvement. When it comes to interventional practice, QNNs have the potential for stenosis detection in X-ray coronary angiography [202], and they can be also applied to selecting medicines for patients with high accuracy [203,204]. Thus, QNNs may also provide some insight into the reduction in computational cost.…”

Section: Quantum Neural Networkmentioning

confidence: 99%

Cardiac Healthcare Digital Twins Supported by Artificial Intelligence-Based Algorithms and Extended Reality—A Systematic Review

Rudnicka,

Proniewska,

Perkins

et al. 2024

Electronics

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Recently, significant efforts have been made to create Health Digital Twins (HDTs), Digital Twins for clinical applications. Heart modeling is one of the fastest-growing fields, which favors the effective application of HDTs. The clinical application of HDTs will be increasingly widespread in the future of healthcare services and has huge potential to form part of mainstream medicine. However, it requires the development of both models and algorithms for the analysis of medical data, and advances in Artificial Intelligence (AI)-based algorithms have already revolutionized image segmentation processes. Precise segmentation of lesions may contribute to an efficient diagnostics process and a more effective selection of targeted therapy. In this systematic review, a brief overview of recent achievements in HDT technologies in the field of cardiology, including interventional cardiology, was conducted. HDTs were studied taking into account the application of Extended Reality (XR) and AI, as well as data security, technical risks, and ethics-related issues. Special emphasis was put on automatic segmentation issues. In this study, 253 literature sources were taken into account. It appears that improvements in data processing will focus on automatic segmentation of medical imaging in addition to three-dimensional (3D) pictures to reconstruct the anatomy of the heart and torso that can be displayed in XR-based devices. This will contribute to the development of effective heart diagnostics. The combination of AI, XR, and an HDT-based solution will help to avoid technical errors and serve as a universal methodology in the development of personalized cardiology. Additionally, we describe potential applications, limitations, and further research directions.

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“…In order to handle such problems, cloud-based collaboration architecture with peer selfmanaging node can be one solution. The collaboration architecture can facilitate in bridging between selfmanaging nodes to share among them available manufacturing resources in building a scalable and dynamic AM cloud [5][6][7] . As the essential requirement in context of Industry 4.0, it is highly recommended to adopt AM for end-part manufacture on integrating cloud-based AM technology with cyber-physical schemes [8][9][10] .…”

Section: Introductionmentioning

confidence: 99%

A Perspective on Advances in Cloud-based Additive Manufacturing

Khan¹,

Arora²,

Kumar³

et al. 2022

Evergreen

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With advances in technology coupled with Industry 4.0, it has become a reality to provide real time information along with monitoring 3D printing process remotely. The unique benefits associated with additive manufacturing (AM) is its potential to produce complex-shaped personalized products with reduced material waste, fewer cost of manufacture, lesser consumption of energy during manufacturing, while allowing in producing the products on-demand. This paper covers the features of cloud-based Additive Manufacturing (AM) by describing about Sustainable Distributed Manufacturing, Automated Order-Processing, Smart resource efficiency improvement, Big data-driven, smart and sustainable manufacturing, resource sharing between different stakeholders, rapid product development with cloud-based AM Platform (CAMP) and cloud-based manufacturing process monitoring. The paper aims to study the recent advances that took place in cloud-based AM and enlist its salient features to help researchers and manufacturing industry adopt the same and get the basic information. Big data-driven, smart and sustainable manufacturing is the present need of manufacturing at its full potential with secure, real-time communication and intelligent process monitoring and diagnostics.

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An investigation on wear characteristics of additive manufacturing materials

Cited by 15 publications

References 31 publications

Microstructure-induced anisotropic tribological properties of Sc-Zr modified Al–Mg alloy (Scalmalloy®) produced via laser powder bed fusion process

Microstructure-induced anisotropic tribological properties of Sc-Zr modified Al–Mg alloy (Scalmalloy®) produced via laser powder bed fusion process

Cardiac Healthcare Digital Twins Supported by Artificial Intelligence-Based Algorithms and Extended Reality—A Systematic Review

A Perspective on Advances in Cloud-based Additive Manufacturing

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