Chemo Assisted Magnetic Abrasive Finishing: Experimental Investigations

被引:33
|
作者
Sihag, Nitesh [1 ]
Kala, Prateek [1 ]
Pandey, Pulak M. [1 ]
机构
[1] IIT Delhi, Dept Mech Engn, New Delhi 110016, India
来源
12TH GLOBAL CONFERENCE ON SUSTAINABLE MANUFACTURING - EMERGING POTENTIALS | 2015年 / 26卷
关键词
Magnetic abrasive finishing; Chemical mechanical polishing; Taguchi L-9 orthogonal array;
D O I
10.1016/j.procir.2014.07.067
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
In modern industries with advancement of technology advanced engineering materials are needed to be used like Tungsten, Titanium alloys, ceramics, various composites etc. These materials possess some special characteristics such as high hardness, high wear resistance, high toughness, high strength etc. which make them preferred over conventional materials in modern industries. Due to the stringent properties these materials are difficult to process. Different conventional finishing processes like grinding, lapping, honing, buffing etc. are generally inefficient in finishing these materials. Although processes like abrasive flow machining, magnetic field assisted finishing processes and chemomechanical finishing may be used but these may be less productive. Therefore a new process which uses combination of chemical oxidation and magnetic field assisted abrasion (magnetic abrasive finishing) has been conceived in the present work for faster processing. To establish the process experiments have been conducted on tungsten work piece and the effects of various process parameters like percentage weight of abrasive, oxidizing agent concentration, rotational speed of magnet and working gap on process response namely percentage change in average surface roughness value (Lambda R-a) was recorded. The experiments were planned using Taguchi L-9 orthogonal array. Experimental data was analyzed using analysis of variance to understand contribution of various process factors on process response. SEM micrographs have also been obtained to study the surface morphology of the finished work piece. Regression model was developed to predict the percentage change in surface roughness in terms of significant process factors. (C) 2015 Elsevier B.V.
引用
收藏
页码:539 / 543
页数:5
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