Sebahattin Tiryaki

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In this study, an artificial neural network (ANN) model was developed for predicting an optimum bonding strength of heat treated woods. The MATLAB Neural Network Toolbox was used for the training and optimization of the ANN model. The ANN model having the best prediction performance was detected by trying various networks. Then, the ANN results were(More)
One of the biggest challenges in machining processes of wood is to detect the optimum values of process parameters for reducing the final production cost. In the present study, the effects of various process parameters on surface roughness and power consumption in abrasive machining process of wood using experimental data collected from the literature were(More)
This paper presents a study of the Taguchi design method for obtaining lower surface roughness values in terms of process parameters in wood machining. The process parameters considered were feed rate, cutting depth, number of knives, annual ring (earlywood–latewood) and grit number of abrasive. The settings of the process parameters were determined by(More)
This study explores the possibility of using wood exposed to insect and fungi degradation for the particleboard industry. For this purpose, some physical and mechanical properties of particleboard produced with Pinus sylvestries L. wood degraded by insect (Ips sexdentatus Boerner) and then fungi (Fomes fomentarius) were determined. The results showed that(More)
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