Tribological Performance Analysis of Polymer Composite Bearing Materials

Abstract

The present thesis explains the detailed study of the coefficient of friction and wear for polymer composite materials. Seven polymer combinations are developed depending the various properties of the filler materials with the polytetraflueroethylene as base materials. The filler combinations used are Molybdenum Disulphide, Bronze, Glass Fiber particles. All experimentation was consisting of three different materials for which property evaluations are to be done. The tribological analysis was performed using the ASTM G99 standard with the statistical approach. The analysis was carried out by combining the Taguchi method and the Grey Relational Analysis named as Taguchi Grey Relational approach. Furthermore the results are optimized using the Artificial Neural Network analysis method, where specialized program was developed to optimize the results using the different solvers with the efficacy criterion of coefficient of determination and the regression coefficient. Moreover the experimental samples are tested using the Scanning Electron Microscopy and the Energy Dispersive Spectroscopy images. Finally the results of all the combinations are studied and the polymer composite material combination is recommended. The thesis ends with the conclusions and relevant references used for the research work. newline