[HTML][HTML] Machine learning in predicting mechanical behavior of additively manufactured parts
S Nasiri, MR Khosravani - Journal of materials research and technology, 2021 - Elsevier
Although applications of additive manufacturing (AM) have been significantly increased in
recent years, its broad application in several industries is still under progress. AM also …
recent years, its broad application in several industries is still under progress. AM also …
An insight on Powder Mixed Electric Discharge Machining: A state of the art review
S Srivastava, M Vishnoi… - Proceedings of the …, 2023 - journals.sagepub.com
Electrical discharge machining (EDM) is an exigent focus of interest for researchers since its
inception. EDM has a wide range of applications due to its non-contact machining process …
inception. EDM has a wide range of applications due to its non-contact machining process …
[HTML][HTML] Exploring the intricacies of machine learning-based optimization of electric discharge machining on squeeze cast TiB2/AA6061 composites: Insights from …
Abstract Aluminium (Al) Alloy-6061/TiB 2 was developed with Squeeze casting while varying
composite quantities with titanium diboride (TiB 2). The metallographic structure of the …
composite quantities with titanium diboride (TiB 2). The metallographic structure of the …
[HTML][HTML] Machining parameter optimization and experimental investigations of nano-graphene mixed electrical discharge machining of nitinol shape memory alloy
Excellent characteristics of Nitinol shape memory alloys (SMAs) makes them favourable for
use in industrial applications. Precision machining of such advanced alloys becomes a key …
use in industrial applications. Precision machining of such advanced alloys becomes a key …
Investigation into the effect of energy density on densification, surface roughness and loss of alloying elements of 7075 aluminium alloy processed by laser powder …
In this study, the effects of volume energy density (VED) on densification behaviour, surface
morphology and loss of alloying elements of 7075 aluminium alloy processed by laser …
morphology and loss of alloying elements of 7075 aluminium alloy processed by laser …
Prediction of wear performance of ZK60/CeO2 composites using machine learning models
In this study, ZK60 magnesium matrix composites were produced with different content of
CeO 2 (0.25, 0.5 and 1 wt%) by hot pressing. The wear behaviour of the samples was …
CeO 2 (0.25, 0.5 and 1 wt%) by hot pressing. The wear behaviour of the samples was …
A sustainable cooling/lubrication method focusing on energy consumption and other machining characteristics in high-speed turning of aluminum alloy
Understanding energy implications and machining performance standards is vital as
industries move toward sustainability. Modern machining techniques including high-speed …
industries move toward sustainability. Modern machining techniques including high-speed …
A comparative study of linear, random forest and adaboost regressions for modeling non-traditional machining
Non-traditional machining (NTM) has gained significant attention in the last decade due to
its ability to machine conventionally hard-to-machine materials. However, NTMs suffer from …
its ability to machine conventionally hard-to-machine materials. However, NTMs suffer from …
The investigation of the effect of particle size on wear performance of AA7075/Al2O3 composites using statistical analysis and different machine learning methods
F Aydin - Advanced Powder Technology, 2021 - Elsevier
Abstract In this study, 7075-Al 2 O 3 (5 wt%) composites with a particle size of 0.3 µm, 2 µm,
and 15 µm were developed by hot pressing. The dry sliding wear performance of the …
and 15 µm were developed by hot pressing. The dry sliding wear performance of the …
A fatigue life prediction approach for laser-directed energy deposition titanium alloys by using support vector regression based on pore-induced failures
L Dang, X He, D Tang, Y Li, T Wang - International Journal of Fatigue, 2022 - Elsevier
A support vector regression (SVR) algorithm was chosen in this study to develop a fatigue
life prediction model by post-mortem fractography analysis. Models based on the SVR …
life prediction model by post-mortem fractography analysis. Models based on the SVR …