Prediction of wear performance of ZK60/CeO2 composites using machine learning models

F Aydin, R Durgut, M Mustu, B Demir - Tribology International, 2023 - Elsevier
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 …

Optimization and Prediction of Tribological Behaviour of Al‐Fe‐Si Alloy‐Based Nanograin‐Refined Composites Using Taguchi with Response Surface Methodology

S Balaji, P Maniarasan, SV Alagarsamy… - Journal of …, 2022 - Wiley Online Library
Aluminium matrix composites (AMCs) are broadly used to change the monolithic materials in
aviation, automotive, and defense industries owing to their superior characteristics such as …

Performance study on phase change material integrated solar still coupled with solar collector

T Maridurai, S Rajkumar, M Arunkumar… - Materials Today …, 2022 - Elsevier
Drinking water is a global concern. Solar desalination minimizes the energy consumption.
The present study combinessolar stills with flat plate collector (FPC) with paraffin wax. The …

Investigation of surface roughness and material removal rate of WEDM of SS304 using ANOVA and regression models

D Srinivasan, N Ganesh… - Surface Topography …, 2022 - iopscience.iop.org
Use of machine learning and artificial intelligence (AI) to analyze the complex
interdependencies of production dataset has gained momentum in recent years. Machine …

Exploratory analysis and evolutionary computing coupled machine learning algorithms for modelling the wear characteristics of AZ31 alloy

A Mishra, VS Jatti, EM Sefene - Materials Today Communications, 2023 - Elsevier
The wear resistance of magnesium alloys is one of its key technological properties that
could limit their practical application. In accordance with ASTM G99–95a standard, this study …

Experimental investigation and machine learning modeling of wear characteristics of AZ91 composites

SSH Kruthiventi, DK Ammisetti - Journal of …, 2023 - asmedigitalcollection.asme.org
This study's primary goal is to examine the effects of wear parameters on the wear-rate (WR)
of magnesium (AZ91) composites. The composites are made up of using a stir casting …

[HTML][HTML] Machine learning enabled prediction of tribological properties of Cu-TiC-GNP nanocomposites synthesized by electric resistance sintering: A comparison with …

A Samad, S Arif, S Ansari, M Muaz, M Mohsin… - Journal of Materials …, 2024 - Elsevier
In the present study, copper matrix composites were successfully produced through the
powder metallurgy route by applying the electrical resistance sintering technique. Copper …

[Retracted] Dynamic Analysis and Fabrication of Single Screw Conveyor Machine

S Moorthi, M Megaraj, L Nagarajan… - … in Materials Science …, 2022 - Wiley Online Library
The design and development of machine tools play a vital role in the current economic
growth. It facilitates the reduction of manufacturing cost coping with a quickly changing …

Effect of process parameters on machining behaviour using S/N ratio and ANOVA analysis

S Balaji, C Sivakandhan, P Maniarasan… - Materials Today …, 2023 - Elsevier
Inconel 725 super alloy is a significant and often used material for many technical
applications such as oil and gas industries, aerospace, nuclear and marine areas owing to …

Experimental Investigation of the Influence of Various Wear Parameters on the Tribological Characteristics of AZ91 Hybrid Composites and Their Machine Learning …

DK Ammisetti, SS Kruthiventi - Journal of Tribology, 2024 - asmedigitalcollection.asme.org
In the current work, the AZ91 hybrid composites are fabricated through the utilization of the
stir casting technique, incorporating aluminum oxide (Al 2 O 3) and graphene (Gr) as …