Modeling the Resistance of the Veneer Adhesion Strength on Some Wood Based Panels by Artificial Neural Networks

In this study, the use of artificial neural networks (ann), which are one of the artificial intelligence methods used in many areas obtaining the values closer to the actual data results, in quality control tests of furniture and decoration elements is intended. first of all to provide example data for training inputs on experimental study was made. with this purpose the average adhesion strength of wood veneer and laminate on surface of 18 mm particleboard, medium density fiberboard (mdf) and ply-wood material in different amount (100, 150, 200 g/m²) which were glued with isocyanate were determined. afterwards, interval values of glue amount factor which are 125 g/m² and 175 g/m², were modeled by ann. a result of obtained data it was determined that using ann for the quality control of furniture and decoration elements, as a non-destructive analysis to be an alternative method.