Determination of modulus of rupture and modulus of elasticity on flakeboard with fuzzy logic classifier

In this study, a model based on fuzzy logic classifier was created in order to determine the values of modulus of elasticity (MOE) and modulus of rupture (MOR) of flakeboards. MOR and MOE are the most important mechanical features of wood-composite panels. The most appropriate mixture ratios to be used in production of wood based boards were determined experimentally. These experiments are very expensive for the manufacturers and require time. For this purpose, MOE and MOR values were measured depending on flakes mixture ratios of manufactured boards. Using these values, input and output values and rule base of fuzzy logic classifier were created. With the fuzzy logic classifier model prepared in Matlab Simulink, MOR and MOE values for flakes mixture ratios were predicted. It was observed that the fuzzy logic classifier predicted MOR and MOE values with 95–97% accuracy. With this system, for the manufacture of wood-composite materials, the most appropriate chip mixture amount required by the manufacturer could be determined.