Effect of type and percentage of reinforcement for optimization of the cutting force in turning of Aluminium matrix nanocomposites using response surface methodologies

被引:10
|
作者
Priyadarshi, Devinder [1 ]
Sharma, Rajesh Kumar [2 ]
机构
[1] DAV Inst Engn & Technol, Dept Mech Engn, Jalandhar, Punjab, India
[2] Natl Inst Technol, Dept Mech Engn, Hamirpur, Himachal Prades, India
关键词
Aluminium matrix nanocomposites; Cutting force; Optimization; RSM; Turning; MACHINING PARAMETERS; COMPOSITE; ROUGHNESS; GRAPHITE; DESIGN; ALLOY; FINISH;
D O I
10.1007/s12206-016-0255-x
中图分类号
TH [机械、仪表工业];
学科分类号
0802 ;
摘要
Aluminium matrix composites (AMCs) now hold a significant share of raw materials in many applications. It is of prime importance to study the machinability of such composites so as to enhance their applicability. Sufficient work has been done for studying the machining of AMCs with particle reinforcements of micron range. This paper presents the study of AMCs with particle reinforcement of under micron range i.e. nanoparticles. This paper brings out the results of an experimental investigation of type and weight percent of nanoparticles on the tangential cutting force during turning operation. SiC, Gr and SiC-Gr (in equal proportions) were used with Al-6061 alloy as the matrix phase. The results indicate that composites with SiC require greater cutting force followed by hybrid and then Gr. Increase in the weight percent also significantly affected the magnitude of cutting force. RSM was used first to design and analyze the experiments and then to optimize the turning process and obtain optimal conditions of weight and type of reinforcements for turning operation.
引用
收藏
页码:1095 / 1101
页数:7
相关论文
共 38 条
  • [31] Machinability characteristics in Zn-40Al alloy: The effect of addition of copper and silicon and optimization of cutting parameters using response surface methodology
    Bayraktar, Senol
    Pehlivan, Gulsah
    JOURNAL OF ALLOYS AND COMPOUNDS, 2025, 1010
  • [33] The effect of secondary nanofiller on mechanical properties and formulation optimization ofHDPE/nanoclay/nanoCaCO3hybrid nanocomposites using response surface approach
    Alavitabari, Seyedemad
    Mohamadi, Mahboube
    Javadi, Azizeh
    Garmabi, Hamid
    JOURNAL OF VINYL & ADDITIVE TECHNOLOGY, 2021, 27 (01): : 54 - 67
  • [34] Multi-Response Optimization of Cutting Force and Surface Roughness in Carbon Fiber Reinforced Polymer End Milling Using Back Propagation Neural Network and Genetic Algorithm
    Laot, Philipus Andreas Lega
    Suhardjono
    Sutikno
    Sampurno
    EXPLORING RESOURCES, PROCESS AND DESIGN FOR SUSTAINABLE URBAN DEVELOPMENT, 2019, 2114
  • [35] Optimization of surface roughness and cutting force during AA7039/Al2O3 metal matrix composites milling using neural networks and Taguchi method
    Karabulut, Sener
    MEASUREMENT, 2015, 66 : 139 - 149
  • [36] Structural Optimization of the Thin-Type Four-Axis Force/Moment Sensor for a Robot Finger Using Response Surface Methodology and Desirability Function
    Hayashi, Yuichiro
    Tsujiuchi, Nobutaka
    Koizumi, Takayuki
    Oshima, Hiroko
    Hiroshima, Tohru
    Ito, Akihito
    Tsuchiya, Youtaro
    2009 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND BIOMIMETICS (ROBIO 2009), VOLS 1-4, 2009, : 1750 - +
  • [37] Machinability study and multi-response optimization of cutting force, Surface roughness and tool wear on CNC turned Inconel 617 superalloy using Al2O3 Nanofluids in Coconut oil
    Venkatesan, K.
    Mathew, Arun Tom
    Devendiran, S.
    Ghazaly, Nouby M.
    Sanjith, S.
    Raghul, R.
    DIGITAL MANUFACTURING TRANSFORMING INDUSTRY TOWARDS SUSTAINABLE GROWTH, 2019, 30 : 396 - 403
  • [38] 3(2) Designing and optimization of aceclofenac transdermal films using response surface methodology: investigating the effect of hydrophilic and hydrophobic matrix on ex vivo and in vivo permeation characteristics
    Yadav P.
    Rastogi V.
    Porwal M.
    Upadhyay P.
    Verma A.
    Journal of Pharmaceutical Investigation, 2017, 47 (6) : 541 - 558