Optimizing the machining variables in CNC turning of aluminum based hybrid metal matrix composites

被引:22
|
作者
Butola, Ravi [1 ]
Kanwar, Susheem [1 ]
Tyagi, Lakshay [1 ]
Singari, Ranganath M. [1 ]
Tyagi, Mohit [2 ]
机构
[1] Delhi Technol Univ, Mech Engn Dept, New Delhi, India
[2] Dr BR Ambedkar Natl Inst Technol, Dept Ind & Prod Engn, Jalandhar, Punjab, India
来源
SN APPLIED SCIENCES | 2020年 / 2卷 / 08期
关键词
Composite; Sugarcane ash; Groundnut shell ash; Jute ash; Genetic algorithm; Taguchi; SURFACE-ROUGHNESS; MICROSTRUCTURE; BEHAVIOR;
D O I
10.1007/s42452-020-3155-8
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Aluminum based hybrid metal matrix composites (HMMC) are being employed nowadays in automobile, aeronautical, sports equipment etc. In this study, three different Al6063 based hybrid metal matrix composites (HMMC) samples having reinforcement with 3%, 6% and 9% by weight respectively are fabricated using stir casting method. Reinforcements used are waste products, namely, jute ash, groundnut shell and sugarcane. Surface roughness of these fabricated composite are is tested by varying machining parameters. The design of experiment is constructed by Taguchi method using three factors and two level, with L8 orthogonal array in which surface roughness is the output response parameter. These recorded results are analysed using analysis of variance and optimization of process parameters is done using response surface methodology and genetic algorithm. The Genetic algorithm optimization is achieved within 102 generations which is quite fast. On comparing it was found that results obtained from GA closely agreed with those obtained from the Response surface methodology.
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页数:9
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