Optimization of Wood Particleboard Drilling Operating Parameters by Means of the Artificial Neural Network Modeling Technique and Response Surface Methodology

Drilling is one of the oldest and most important methods processing wood wood-based materials. Knowing optimum value factors that affect drilling process could lead both to high-quality furniture low-energy consumption during manufacturing process. In this work, artificial neural network modeling technique response surface methodology were employed reveal selected factors, namely, drill tip angle, tooth bite, type delamination factor at inlet outlet, thrust force, torque. The data set was used in work develop validate ANN models collected from literature. results showed developed reasonably predict analyzed responses. By using these methodology, values revealed. Moreover, influences on particleboards analyzed.