Optimization of graphene based minimum quantity lubrication of Inconel718 turning with multiple machining performances

被引:5
|
作者
Amrita, M. [1 ]
Kamesh, B. [1 ]
机构
[1] Gayatri Vidya Parishad Coll Engn, Mech Engn, Visakhapatnam 530017, Andhra Pradesh, India
关键词
Inconel718; Grey relational method; Graphene; Minimum quantity lubrication; Optimization;
D O I
10.1016/j.matpr.2020.04.568
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Inconel 718 is a 'hard to machine' material due to its toughness and work hardenability. Researchers are working on possible methods to improve its machinability. In the initial part of the work, different concentrations of graphene based cutting fluids are used for machining Inconel718 and best concentration of graphene in cutting fluid is determined based on tool wear. In the second part of the work, turning parameters for machining Inconel 718 are optimized while machining using MQL application of best concentration of graphene based cutting fluid. Single response optimization is performed to identify input parameters which optimize resultant cutting forces, surface roughness, cutting temperature, tool wear and metal removal rate individually. Mutliresponse optimization is also performed giving equal importance to multiple machining performances in one case and by giving unequal importance in other case. (C) 2020 Elsevier Ltd. All rights reserved.
引用
收藏
页码:1337 / 1344
页数:8
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