Prediction of Waviness Values in Skew Rolling Using Machine Learning Methods

• Autorzy: Lis Konrad , Pater Zbigniew , Tomczak Janusz , Bulzak Tomasz Adam , Kusiak Tomasz

Identyfikatory

DOI

10.12913/22998624/172338

• Języki publikacji: EN

Abstrakty

EN

Skew rolling with three rolls is used for producing axisymmetric parts. In this method, the tools are spaced every 120° on the circumference of the workpiece. They are also set askew relative to the rolling axis. Cross sectional reduction is made effective by moving the tapered rolls closer to or away from the center line of the workpiece. Experiments were conducted with variable initial conditions of the rolling process to examine surface topography of rolled parts. Obtained experimental results were then analyzed using machine learning methods in order to determine the most effective regression model with the highest coefficient of determination R2 for waviness prediction.

Słowa kluczowe

EN

skew rolling; waviness; CNC rolling mill; stepped axles and shafts; machine learning

• Wydawca: Lublin University of Technology ; Polish Society of Ecological Engineering (PTIE), Branch of PTIE in Lublin
• Czasopismo: Advances in Science and Technology. Research Journal
• Rocznik: 2023
• Tom: Vol. 17, no 5
• Strony: 350--359
• Opis fizyczny: Bibliogr. 17 po., fig., tab.

Twórcy

autor

Lis Konrad

• Faculty of Mechanical Engineering, Lublin University of Technology, ul. Nadbystrzycka 36, 20–618 Lublin, Poland

• https://orcid.org/0000-0002-6461-4226

autor

Pater Zbigniew

• Faculty of Mechanical Engineering, Lublin University of Technology, ul. Nadbystrzycka 36, 20–618 Lublin, Poland

• https://orcid.org/0000-0001-5504-157X

autor

Tomczak Janusz

• Faculty of Mechanical Engineering, Lublin University of Technology, ul. Nadbystrzycka 36, 20–618 Lublin, Poland

• https://orcid.org/0000-0003-3781-1432

autor

Bulzak Tomasz Adam

• Faculty of Mechanical Engineering, Lublin University of Technology, ul. Nadbystrzycka 36, 20–618 Lublin, Poland

• https://orcid.org/0000-0002-0525-8321

autor

Kusiak Tomasz

• Faculty of Mechanical Engineering, Lublin University of Technology, ul. Nadbystrzycka 36, 20–618 Lublin, Poland

• https://orcid.org/0000-0001-9127-678X

Bibliografia

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Uwagi

Opracowanie reOpracowanie rekordu ze środków MNiSW, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2024).