Please use this identifier to cite or link to this item:
Full metadata record
|dc.identifier.citation||Journal of Reinforced Plastics and Composites, (Accepted Version)||en|
|dc.description||Copyright for the published version belongs to Sage||en|
|dc.description.abstract||Red mud is an industrial waste generated during the production of alumina by Bayer's process. Using this red mud as the filler, particulate reinforced polyester composites have been prepared and their dry sliding wear behavior has been studied experimentally. For this a standard pin-on-disc test set-up and Taguchi's orthogonal arrays were used. Taguchi's experimental design method eliminates the need for repeated experiments and thus saves time, materials, and cost. It identifies the significant control factors and their interactions predominantly influencing the wear rate. From the experimental findings, an optimal combination of control factors was obtained on the basis of which a predictive model was proposed. This model was validated by performing a confirmation experiment with an arbitrarily chosen set of factor combinations. Finally, the optimal factor settings for minimum wear rate under specified experimental conditions have been determined using a genetic algorithm.||en|
|dc.title||Analysis of Dry Sliding Wear Behavior of Red Mud Filled Polyester Composites using the Taguchi Method||en|
|Appears in Collections:||Journal Articles|
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.