Surface roughness analysis of greater cutting depths during hard turning

Solving the Issue of Discriminant Roughness of Heterogeneous Surfaces Using Elements of Artificial Intelligence

“…Machining methods have also been evolving, ranging from downright primitive to the traditional methods used to date, along with methods for classifying surface quality determination [ 1 , 2 ]. The roughness began to be prescribed in the blueprint and was given by standards that became documents approving the rules of product reproducibility.…”

“…The “measurement” of surface roughness by sight and touch was no longer sufficient because it could not be measured accurately and precisely enough. With the advent of new technologies and modern measuring instruments, it was possible to measure the surface roughness and determine its parameters more accurately [ 1 , 2 ]. These technical possibilities were reflected in the standardization process [ 2 ].…”

“…Setting up rules for assessing different products or production processes is the main goal of the International Organization for Standardization. Standardization in surface quality assessment is mainly dealt with in ISO 4287 and ISO 4288 [ 2 ].…”

“…The novelty of this article lies in the possibility of comparing the roughness of surfaces created by two different machining methods by using a neural network. The surface quality expressed by Rz and Ra’s roughness parameters is examined depending on the sample material and the machining technology that was used [ 1 , 2 ]. The next part deals with the use of neural networks to evaluate measured data.…”

“…The next part deals with the use of neural networks to evaluate measured data. In the last part, the measured data were statistically evaluated [ 2 , 8 ]. Based on the conclusions of this analysis, the possibilities of using neural networks to determine the material of a given sample with known roughness parameters were evaluated [ 8 ].…”