Prediction of drilling characteristics of crab carapace- coir-polymer composites using artificial neural network

This study examines the drilling characteristics of crab carapace-impregnated coir polyester composite material. The chemical structure of the crab carapace offers better mechanical properties; however, optimizing drilling performance in a full factorial design under various drilling conditions, with the parameters of drill bit diameter, feed rate, and spindle speed. A reduction in feed rate combined with a small drill diameter and high spindle speed creates the optimal conditions to minimize the delamination value of 1.05 while maintaining structural strength and producing a strong thrust of 100 N and torque effects of 5.0 N-m on the composite material. The ANN was used to predict the drilling parameters, and the ANN model provides a precise prediction of drilling parameters within the defined boundaries for improved operation efficiency of this composite material, with average absolute percentage error of less than 3%. The ANN-based methodology shows efficient modeling capabilities for drilling operations in complex structured composite materials.