中国有色金属学报(英文版)
Transactions of Nonferrous Metals Society of China
| Vol. 24 No. 9 September 2014 |
（1. Department of Mechanical Engineering, Faculty of Engineering,
Erode Builder Educational Trust’s Group of Institutions,
Nathakadaiyur, Kangayam – 638108, Tirupur District, Tamil Nadu, India;
2. Department of Mechanical Engineering, Coimbatore Institute of Technology,
Coimbatore – 641014, Tamil Nadu, India;
3. Department of Mechanical Engineering, V V College of Engineering, Tisaiyanvilai – 627657, Tamil Nadu, India）
Abstract:The dry sliding wear behavior of AA6061 matrix composite reinforced with aluminium nitride particles (AlN) produced by stir casting process was investigated. A regression model was developed to predict the wear rate of the prepared composite. A four-factor, five-level central composite rotatable design matrix was used to minimize the number of experimental runs. The factors considered in this study were sliding velocity, sliding distance, normal load and mass fraction of AlN reinforcement in the matrix. The developed regression model was validated by statistical software SYSTAT 12 and statistical tools such as analysis of variance (ANOVA) and student’s t test. It was found that the developed regression model could be effectively used to predict the wear rate at 95% confidence level. The influence of these factors on wear rate of AA6061/AlNp composite was analyzed using the developed regression model and predicted trends were discussed with the aid of worn surface morphologies. The regression model indicated that the wear rate of cast AA6061/AlNp composite decreased with an increase in the mass fraction of AlN and increased with an increase of the sliding velocity, sliding distance and normal load acting on the composite specimen.
Key words: aluminium matrix composite; particle-reinforcement; wear; regression model
