Analysis and optimization of the delamination factor in the drilling of wood-thermo plastic composites: An approach based on artificial intelligence

Abstract

The building industry has recently experienced a surge in the use of wood plastic composite (WPC) materials, which are lightweight, easy to work with, and visually appealing. This study aims to analyze and optimize drilling parameters to minimize delamination at the entrance and exit of the hole, leading to defect-free products. To analyze delamination, three input parameters for the drilling process are selected to measure the delamination factor (F_d) at both the entrance and exit of the hole. The experimental data are validated using the developed regression and fuzzy models. Results show that feed rate (FR) and spindle speed (SS) are the primary factors in reducing delamination. Desirability-based optimization suggests an optimal SS of 3000 rpm, a FR of 75 mm/min, and a drill diameter of 6 mm, with output responses of F_d, 1.04454 (entry), and 1.42694 (exit). Additionally, metaheuristic algorithms such as particle swarm and hippopotamus optimization algorithms are employed to determine the optimal drilling conditions. This paper highlights the importance of optimizing drilling parameters when creating holes in WPC panels for various construction uses.