Wear Resistance Prediction Model for Magnesium Metal Composite by Response Surface Methodology using Central Composite Design

被引：0

作者：

Sagar P. ^{[1
]}

Handa A. ^{[1
,2
]}

机构：

[1] I.K. Gujral Punjab Technical University, Kapurthala

[2] Department of Mechanical Engineering, I.K. Gujral Punjab Technical University, Kapurthala

来源：

International Journal of Performability Engineering | 2020年 / 16卷 / 10期

关键词：

Central composite design; Friction stir processing; Magnesium metal composite; Response surface methodology; Wear morphology;

D O I：

10.23940/ijpe.20.10.p4.15251534

中图分类号：

学科分类号：

摘要：

Recently, friction stir processing (FSP) has emerged as a pioneering approach for the manufacture of composites with enhanced mechanical and tribological properties. The present study examines the impact of process parameters such as tool rotation speed and FSP pass number on the AZ61A/TiC magnesium metal composite for responses such as hardness and wear resistance. To minimize number of experiments, the design of experiments (DOE) was configured according to the response surface methodology (RSM) using central composite design (CCD). Analysis of variance (ANOVA) was conducted to develop a mathematical and empirical model for studying the relationship between tool rotation and number of passes for responses such as microhardness and wear resistance. Microhardness was checked on the Vickers microhardness testing machine, and tribological behavior was examined on the pin-on-disc tribotester. Wear tracks were analyzed via scanning electron microscopy (SEM). The responses were predicted using validated mathematical model, and contour plots were generated to study the interaction and influence of process parameters. Finally, the findings suggested that both selected parameters are significant and largely influence the responses. © 2020 Totem Publishers Ltd. All rights reserved.

引用

页码：1525 / 1534

页数：9

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