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Analysis of workpiece surface quality is one of the major issues in manufacturing engineering. Turning operation is a famous machining operation that is widely used in machining of materials. In this research, we investigate the surface finish of machined workpiece from turning operation. For this purpose, we employ fractal theory to study the complex structure of machined workpiece’s surface in different conditions. The applied parameters include the variations of cutting depth, feed rate and spindle speed in wet and dry machining conditions. Based on the obtained results, we found the correlation between the increment of fractal dimension of machined surface and the increment of cutting depth, feed rate and spindle speed in wet machining condition. The obtained results will be discussed in relation with the complexity of machined surface. The employed method of analysis in this research can be widely applied to the analysis of the effect of different machining parameters and conditions on the surface quality of machined workpiece in case of different machining operations.

Acquiring the desired surface quality is one of the major efforts in machining of materials. Milling operation is a widely used machining operation to shape the material in different forms. Machining parameters and conditions are two major factors that affect the surface quality of machined workpiece in milling operation. In this paper, we analyze the surface finish of machined workpiece under the variations of machining parameters and conditions (wet and dry conditions) in milling operation. For our analysis, we use fractal dimension as the indicator of complexity of structure. Based on the obtained results, in the case of wet machining condition, by increasing the depth of cut, feed rate and spindle speed in separate experiments, the fractal dimension of machined surface increases. However, the obtained results in the case of dry machining condition are not consistent with the variations of different machining parameters. The obtained results will be discussed in terms of complex structure of machined surface. The method of analysis employed in this research can be investigated with other machining operations to check how the machining parameters and conditions affect the surface quality of machined surface.

Drilling is a famous and widely used machining operation to make holes in the workpiece. The size and surface quality of drilled hole are two factors that should be considered mainly. In this research, we examine the effect of different machining parameters and conditions on the surface quality of generated hole in drilling operation. For this purpose, we employ fractal theory and investigate how the variations of depth of cut and spindle speed affect the complexity of surface texture of drilled holes in wet and dry machining conditions. Based on the obtained results, the increment of depth of cut and spindle speed in case of wet and dry machining causes lower complexity on the generated surface from drilling. In addition, the generated surface from dry machining is more complex than the generated surface from wet machining. The obtained method in this research can be applied to other machining operations in order to investigate the effect of machining parameters and conditions on the surface quality of machined workpiece.

Obtaining the optimum surface finish is one of the key factors in machining operations. For this purpose, engineers apply a set of machining parameters to obtain the desired surface quality. On the other hand, tool faces wear during machining operation that itself affects the surface quality of machined surface. Therefore, tool wear and surface finish of machined workpiece should be related to each other. In this research, we employ fractal analysis in order to investigate the correlation between variations of complex structure of machined surface and tool wear in turning operation. In fact, we changed the machining parameters between different experiments and investigated how the machined surface is correlated with the tool wear. Based on the obtained results, we can see the correlation between the complexity of machined surface and tool wear by increasing the depth of cut, spindle speed and feed rate in different experiments. The method of analysis employed in this research can be widely applied to other machining operations in order to find the correlation between the surface quality of machined surface and tool wear.

Tool wear is an important issue that happens in all machining operations when the tool exerts forces on the workpiece. Therefore, engineers should choose the optimum values for machining parameters and conditions to reduce the amount of tool wear and increase its life. Machine vibration is one of the factors that highly affects tool wear. Since both tool wear and machine vibration signal have complex structures, in this research we employ fractal theory to find out their relation. In this paper, we analyze the relation between tool wear and machine vibration signal in different experiments where the depth of cut, feed rate and spindle speed change. The obtained results showed that tool wear and machine vibration signal are related to each other in case of variations of depth of cut and feed rate in different experiments, where both fractal structures get more complex by the increment of these machining parameters. The obtained method of analysis in this research can be potentially applied to other machining operations in order to link the machine vibration to the structure of tool wear.

Surface finish is one of the most important issues that is discussed in machining of materials. In fact, reaching the required surface finish is the key scale in analysis of the quality of machined workpiece. Chip formation is an important factor that highly affects the surface finish of machined workpiece. In this research, we analyze the relationship between surface finish and chip formation by fractal analysis of their surfaces. Since both patterns have complex structures, we calculate their fractal dimension in case of different experiments in which machining parameters change. The result of analysis indicates that the variations of fractal dimension of machined surface show a reverse pattern compared to the fractal dimension of chip surface in case of variations of depth of cut and feed rate. However, in case of variations of spindle speed, the variations of fractal dimension of machined surface show a similar pattern with the fractal dimension of chip surface. Therefore, it can be said that the complexity of machined surface is linked to the complexity of chip surface. The method of analysis used in this research can be further applied to other manufacturing operations.

Tool wear is one of the unwanted phenomena in machining operations where tool has direct contact with the workpiece. Tool wear is an important issue in milling operation that is caused due to different parameters such as machine vibration. Tool wear shows complex structure, and machine vibration is a chaotic signal that also is complex. In this research, we analyze the correlation between tool wear and machine vibration using fractal theory. We run the experiments in which machining parameters, namely depth of cut, feed rate and spindle speed change, and accordingly analyze the variations of fractal dimension of tool wear versus the fractal dimension of machine vibration signal. Based on the obtained results, variations of complexity of tool wear are reversely correlated with the variations of complexity of vibration signal. Fractal analysis could potentially be applied to other machining operations in order to investigate the relation between tool wear and machine vibration.

Surface finish of machined workpiece is one of the factors to evaluate the performance of machining operations. There are different factors such as machining parameters that affect the surface finish of machined workpiece. Tool wear is an unwanted machining issue that highly affects the surface finish of machined workpiece. In a similar way, different parameters (e.g. cutting speed, feed rate and depth of cut) also affect tool wear. In this research, we investigated how the complex structure of machined workpiece is related to the complex structure of tool wear. For this purpose, we benefited from the fractal analysis. The experiments were conducted based on the variations of machining parameters (depth of cut, feed rate and spindle speed), and accordingly the fractal dimension of machined surface was analyzed versus the fractal dimension of tool wear. Based on the obtained results, the complexity of machined surface is related to the complexity of tool wear. Fractal analysis could be applied to other machining operations to analyze the complex structures of machined surface and tool and potentially make a relationship between them.

Analysis of surface quality of machined workpiece is an important issue in machining of materials. For this purpose, scientists analyze how the texture of machined surface changes due to different conditions. Machine vibration is one of the factors that highly affects the surface quality of machined surface. In this research, we analyze the relation between machine vibration and surface quality of machined workpiece. For this purpose, we employ fractal theory and analyze how the complex structure of machined surface changes with the complex structure of machine vibration signal in case of variations of machining parameters, namely, depth of cut, feed rate and spindle speed, in milling operation. Based on the results, variations of surface quality of machined workpiece are related with the variations of complexity of machine vibration signal. The method of analysis employed in this research can be applied to other machining operations in order to find the relation between machine vibration and surface quality of machined workpiece.