Analysis and prediction of the impact of technological parameters on cutting force components in rough milling of AZ31 magnesium alloy

• Autorzy: Kulisz M. , Zagórski I. , Weremczuk A. , Rusinek R. , Korpysa J.

Identyfikatory

DOI

10.1007/s43452-021-00319-y

• Języki publikacji: EN

Abstrakty

EN

This paper presents the results of experimental study of the AZ31 magnesium alloy milling process. Dry milling was carried out under high-speed machining conditions. First, a stability lobe diagram was determined using CutPro software. Next, experimental studies were carried out to verify the stability lobe diagram. The tests were carried out for different feed per tooth and cutting speed values using two types of tools. During the experimental investigations, cutting forces in three directions were recorded. The obtained time series were subjected to general analysis and analysis using composite multiscale entropy. Modelling and prediction were performed using Statistica Neural Network software, in which two types of neural networks were applied: multi-layered perceptron and radial basis function. It was observed that milling with high cutting speed values allows for component values of cutting force to be lowered as a result of the transition into the high-speed machining conditions range. In most cases, the highest values for the analysed parameters were recorded for the component Fx, whereas the lowest were recorded for Fy. Additionally, the paper shows that a prediction (with the use of artificial neural networks) of the components of cutting force can be made, both for the amplitudes of components of cutting force Famp and for root mean square Frms.

Słowa kluczowe

EN

high-speed dry milling; cutting forces; magnesium alloys; entropy; neural networks

PL

siła skrawania; sieć neuronowa; entropia; stop magnezu

• Wydawca: Springer ; Wrocław University of Science and Technology
• Czasopismo: Archives of Civil and Mechanical Engineering
• Rocznik: 2022
• Tom: Vol. 22, no. 1
• Strony: art. no. e1, 2022
• Opis fizyczny: Bibliogr. 32 poz., rys., wykr.

Twórcy

autor

Kulisz M.

• Department of Organisation of Enterprise, Management Faculty, Lublin University of Technology, Lublin, Poland

• https://orcid.org/0000-0002-8111-2316

autor

Zagórski I.

• Department of Production Engineering, Mechanical Engineering Faculty, Lublin University of Technology, Lublin, Poland

• https://orcid.org/0000-0001-6016-7011

autor

Weremczuk A.

• Department of Applied Mechanics, Mechanical Engineering Faculty, Lublin University of Technology, Lublin, Poland

• https://orcid.org/0000-0002-0121-7100

autor

Rusinek R.

• Department of Applied Mechanics, Mechanical Engineering Faculty, Lublin University of Technology, Lublin, Poland

• https://orcid.org/0000-0002-2808-2007

autor

Korpysa J.

• Department of Production Engineering, Mechanical Engineering Faculty, Lublin University of Technology, Lublin, Poland

• https://orcid.org/0000-0002-5833-7074

Bibliografia

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Uwagi

PL

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)