MACHINABILITY STUDIES ON FIBER REINFORCED COMPOSITE MATERIALS

Abstract

This research work was undergone with an aim of introducing natural reinforcements in polymeric composites as a replacement for synthetic materials The introduction of natural fibers enhances the bio degradability of composites and does not cause any harm to the environment The work involves development of new composite samples mechanical characterization of developed samples selection of best samples and machinability studies on the selected samples Ten hybrid fiber reinforced composites were developed by using two types of natural reinforcements namely vetiver and jute and a synthetic reinforcement namely E glass in vinyl ester matrix resin The vetiver fibers were given chemical treatment and followed by heat treatment in order to enhance its surface bonding ability with the resin Composite samples were developed by using hand layup method during which a resin to fiber ratio of sixty six is to thirty four by weight was maintained In order to study the influence of chemical treatment composite samples were developed with and without pre treatment to fibers The developed samples were cut according to ASTM standards and were tested for their mechanical properties like tensile flexural compressive and impact strengths A detailed investigation on the performance of samples during each test was done and the influence of the fibers and its chemical treatment on the properties were analyzed Based on the mechanical properties of the samples three best samples had been identified In order to visualize the defects like cavities and fiber pull outs microstructural images have been captured on the fractured surface of the tested sample The microstructural images of pretreated samples showed qualitative enhancements in defects when compared to untreated samples The three best performing samples selected were used for machinability studies A set of twenty eight drilling experiments have been conducted on the samples under varying input conditions based on D optimal method The input factors were selected as a combination of nu