Wear behavior of AA 5083/SiC nano-particle metal matrix composite: Statistical analysis

Amir Hussain Idrisi, Abdel Hamid Ismail Mourad, Dinu Thomas Thekkuden, John Victor Christy

Research output: Contribution to journalConference articlepeer-review

21 Citations (Scopus)

Abstract

This paper reports study on statistical analysis of the wear characteristics of AA5083/SiC nanocomposite. The aluminum matrix composites with different wt % (0%, 1% and 2%) of SiC nanoparticles were fabricated by using stir casting route. The developed composites were used in the manufacturing of spur gears on which the study was conducted. A specially designed test rig was used in testing the wear performance of the gears. The wear was investigated under different conditions of applied load (10N, 20N, and 30N) and operation time (30 mins, 60 mins, 90 mins, and 120mins). The analysis carried out at room temperature under constant speed of 1450 rpm. The wear parameters were optimized by using Taguchi's method. During this statistical approach, L27 Orthogonal array was selected for the analysis of output. Furthermore, analysis of variance (ANOVA) was used to investigate the influence of applied load, operation time and SiC wt. % on wear behaviour. The wear resistance was analyzed by selecting "smaller is better" characteristics as the objective of the model. From this research, it is observed that experiment time and SiC wt % have the most significant effect on the wear performance followed by the applied load.

Original languageEnglish
Article number012087
JournalIOP Conference Series: Materials Science and Engineering
Volume324
Issue number1
DOIs
Publication statusPublished - Apr 6 2018
Event2017 5th International Conference on Mechanical Engineering, Materials Science and Civil Engineering, ICMEMSCE 2017 - Kuala Lumpur, Malaysia
Duration: Dec 15 2017Dec 16 2017

Keywords

  • 5083 Al Alloy
  • ANOVA
  • Metal matrix composite
  • SiC nano reinforcement
  • Taguchi method
  • wear test

ASJC Scopus subject areas

  • Materials Science(all)
  • Engineering(all)

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