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Investigation of the Impact of Face Milling Parameters on the Roughness of the Machined Surface for 1.4301 Steel

Bembenek Michał, Dzienniak Damian, Dzindziora Agnieszka, Sułowski Maciej, Ropyak Liubomyr

Advances in Science and Technology. Research Journal

2023

Vol. 17, no 4

299--312

The objective of this research was to analyze how different milling parameters impact the roughness of the surface produced during the machining process. Kinematic parameters, such as cutting speed and feed per tooth, as well as geometric parameters, such as axial and radial depth of machining, were considered in various configurations to determine which one had the greatest impact on the surface quality of 1.4301 stainless steel (also known as AISI 304, among other designations). This type of steel is commonly used in a number of industries, such as construction, automotive, food, chemical, decoration, oil, and petrochemical, owing to its favorable properties. It is also relatively cheap. The analyzed roughness parameters included Ra, Rq, Rz, Rt, which, considered collectively, provide a comprehensive picture of the overall surface quality. Based on the results, feed per tooth is the one parameter that was to a large degree responsible for the overall quality roughness of the surface of the analyzed samples. The remaining tested parameters also had an impact on the surface quality, which resulted in a dynamic increase or decrease in roughness (extremes), but not to the same degree as in the case of feed per tooth. At one point, for a relatively low axial depth of cut, a sudden increase in the resulting roughness was recorded.

Experimental modeling of the milling process of aluminum alloys used in the aerospace industry

Țîțu Aurel Mihail, Pop Alina Bianca, Nabiałek Marcin, Dragomir Camelia Cristina, Sandu Andrei Victor

Bulletin of the Polish Academy of Sciences. Technical Sciences

2021

Vol. 69, nr 5

art. no. e138565

This research presents an experimental study carried out for the modeling and optimization of some technological parameters for the machining of metallic materials. Certain controllable factors were analyzed such as cutting speed, depth of cut, and feed per tooth. A dedicated research methodology was used to obtain a model which subsequently led to a process optimization by performing a required number of experiments utilizing the Minitab software application. The methodology was followed, and the optimal value of the surface roughness was obtained by the milling process for an aluminum alloy type 7136-T76511. A SECO cutting tool was used, which is standard in aluminum machining by milling. Experiments led to defining a cutting regime that was optimal and which shows that the cutting speed has a significant influence on the quality of the machined surface and the depth of cut and feed per tooth has a relatively small impact on the chosen ranges of process parameters.