Abstract
The demand for precision machining process and sophisticated fabrication methods is increased due to the wide application of glass fiber reinforced polymer (GFRP) composites in various industries such as aerospace, defense, automobile, construction and railways etc. Identification of optimum drilling process parameters for GFRP composites has become mandatory because drilling operation of GFRP composites is significantly dissimilar from conventional drilling operation of metals. In this present work, three drilling parameters such as drill bit point angle, feed rate, and spindle speed were optimized using teaching learning based optimization (TLBO) algorithm for GFRP composite with 30% fiber volume fraction. The optimization study was carried out based on four output responses namely, thrust force, torque, delamination factor, and surface roughness of drilled surface and reported in this article. TLBO results were validated with experimental results.
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