Abstract Machine learning (ML) methods has recently contributed very well in the
advancement of the prediction models used for energy consumption. Such models highly …

The cutting power consumption of milling has direct influence on the economic benefits of
manufacturing particle boards. The influence of the milling parameters on the cutting power …

This study aims to determine the optimal CNC (Computer Numerical Control) machining
conditions using an artificial neural network. For this purpose, Fagus orientalis, Castanea …

The optimum adjustment the CNC (Computer Numerical Control) processing parameters is
extremely important, especially in finishing processes such as coating, painting, and …

Many factors (material properties, drill bit type and size, drill bit wear, drilling parameters
used, and machine-tool characteristics) affect the efficiency of the drilling process, which …

In addition to traditional chip methods, performance lasers are often used in the field of wood
processing. When cutting wood with CO2 lasers, it is primarily the area of optimization of …

Although artificial neural networks (ANN) have been used frequently in engineering
applications, it has been determined that they are not preferred much, especially in …

Elastic strain is one of the most important parameters associated with drying stresses. The
research presented in this paper attempts to develop an artificial neural network based …

Drilling is one of the oldest and most important methods of processing wood and wood-
based materials. Knowing the optimum value of factors that affect the drilling process could …

Most of the parts of furniture made of medium density fiberboards (MDF) require at least one
hole to be assembled. The drilling technological parameters influence the quality of holes …