Wear Resistivity of Al7075/6wt.%SiC Composite by Using Grey-Fuzzy Optimization Technique

被引:0
作者
Abhijit Bhowmik
Ajay Biswas
机构
[1] National Institute of Technology Agartala,Department of Mechanical Engineering
来源
Silicon | 2022年 / 14卷
关键词
Aluminium; SiC; Wear; Grey relational analysis; Fuzzy interface system;
D O I
暂无
中图分类号
学科分类号
摘要
The application of SiC particulate reinforcement impact greatly for making aluminium matrix composite because of its superb heat conductivity, oxidation stability and high resistance to mechanical erosion. Present work based on dry sliding wear analysis of Al7075/6wt.%SiC composite fabricated by liquid state stir casting method. To acquire a productive wear rate, three major process parameters viz. load, sliding speed and covering sliding distance were compared at four different levels. ANOVA analysis showed that the probability rate of the load is less than 0.05 that revealed their significant factor. From the study, the highest GRG and GFG values are found 0.914 and 0.854, respectively, for the optimal operating parameters of 10 Newton load, 2 m/s sliding speed and 500-m sliding distance. Finally, it is revealed that the grey-fuzzy technique effectively authenticates the decision making of wear performance characteristics rather than a plain grey relational grade.
引用
收藏
页码:3843 / 3856
页数:13
相关论文
共 43 条
  • [31] Multi response optimization of machining parameters of drilling Al/SiC metal matrix composite using grey relational analysis in the Taguchi method
    A. Noorul Haq
    P. Marimuthu
    R. Jeyapaul
    The International Journal of Advanced Manufacturing Technology, 2008, 37 : 250 - 255
  • [32] Dry Sliding Wear Characteristics of SiC and Al2O3 Nanoparticulate Aluminium Matrix Composite Using Taguchi Technique
    Kiran Kumar Ekka
    S. R. Chauhan
    Arabian Journal for Science and Engineering, 2015, 40 : 571 - 581
  • [33] Dry Sliding Wear Characteristics of SiC and Al2O3 Nanoparticulate Aluminium Matrix Composite Using Taguchi Technique
    Ekka, Kiran Kumar
    Chauhan, S. R.
    Varun
    ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING, 2015, 40 (02) : 571 - 581
  • [34] Optimization and Characterization of Centrifugal-Cast Functionally Graded Al-SiC Composite Using Response Surface Methodology and Grey Relational Analysis
    Saleh, Bassiouny
    Fathi, Reham
    Abdalla, Modawy Adam Ali
    Radhika, N.
    Ma, Aibin
    Jiang, Jinghua
    COATINGS, 2023, 13 (05)
  • [35] OPTIMIZATION OF THE PROCESS PARAMETERS FOR DRY-SLIDING WEAR OF AN Al 2219-SiCp COMPOSITE USING THE TAGUCHI-BASED GREY RELATIONAL ANALYSIS
    Ganesh, Radhakrishnan
    Chandrasekaran, Kesavan
    Ameen, Mohammed
    Kumar, Raja Pavan
    MATERIALI IN TEHNOLOGIJE, 2014, 48 (03): : 361 - 366
  • [36] Optimization of dry sliding wear performance of functionally graded Al6061 / 20% SiC metal matrix composite using Taguchi method
    Singh, S. Prathap
    Geethan, K. Arun Vasantha
    Elilraja, D.
    Prabhuram, T.
    Durairaj, J. Immanuel
    MATERIALS TODAY-PROCEEDINGS, 2020, 22 : 2824 - 2831
  • [37] Optimization of SiC Abrasive Parameters on Machining of Ti-6Al-4V Alloy in AJM Using Taguchi-Grey Relational Method
    Saravanan, K.
    Xavier, Francis J.
    Sudeshkumar, M. P.
    Maridurai, T.
    Suyamburajan, Vijayananth
    Jayaseelan, V
    SILICON, 2022, 14 (03) : 997 - 1004
  • [38] A comparative Study on the Wear Behavior of Al2O3 and SiC Coated Ti-6Al-4V Alloy Developed Using Plasma Spraying Technique
    G. Perumal
    M. Geetha
    R. Asokamani
    N. Alagumurthi
    Transactions of the Indian Institute of Metals, 2013, 66 : 109 - 115
  • [39] A comparative Study on the Wear Behavior of Al2O3 and SiC Coated Ti-6Al-4V Alloy Developed Using Plasma Spraying Technique
    Perumal, G.
    Geetha, M.
    Asokamani, R.
    Alagumurthi, N.
    TRANSACTIONS OF THE INDIAN INSTITUTE OF METALS, 2013, 66 (02) : 109 - 115
  • [40] An application of fuzzy logic with grey relational technique in grinding process using nano Al2O3 grinding wheel on Ti-6Al-4V alloy
    Stephen D.S.
    Sethuramalingam P.
    International Journal of Machining and Machinability of Materials, 2021, 23 (01) : 21 - 46