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

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EN
Abstrakty
EN
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.
Twórcy
  • Department of Manufacturing Systems, Faculty of Mechanical Engineering and Robotics, AGH University of Science and Technology, 30-059 Kraków, Poland
  • Department of Manufacturing Systems, Faculty of Mechanical Engineering and Robotics, AGH University of Science and Technology, 30-059 Kraków, Poland
  • Department of Manufacturing Systems, Faculty of Mechanical Engineering and Robotics, AGH University of Science and Technology, 30-059 Kraków, Poland
  • Department of Metal Science and Powder Metallurgy, Faculty of Metal Engineering and Industrial Computer Science, AGH University of Science and Technology, 30-059 Kraków, Poland
  • Department of Computerized Engineering, Ivano-Frankivsk National Technical University of Oil and Gas, Ivano-Frankivsk, 76019, Ukraine
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Uwagi
Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-312832fe-b513-4535-b0ab-59a08fbcf768
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