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.
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