Literature DB >> 34300892

Study of Friction and Wear Effects in Aluminum Parts Manufactured via Single Point Incremental Forming Process Using Petroleum and Vegetable Oil-Based Lubricants.

José M Diabb Zavala1, Oscar Martínez-Romero2, Alex Elías-Zúñiga2, Héctor Manuel Leija Gutiérrez3, Alejandro Estrada-de la Vega2, Jaime Taha-Tijerina4,5.   

Abstract

This paper focuses on studying how mineral oil, sunflower, soybean, and corn lubricants influence friction and wear effects during the manufacturing of aluminum parts via the single point incremental forming (SPIF) process. To identify how friction, surface roughness, and wear change during the SPIF of aluminum parts, Stribeck curves were plotted as a function of the SPIF process parameters such as vertical step size, wall angle, and tool tip semi-spherical diameter. Furthermore, lubricant effects on the surface of the formed parts are examined by energy dispersive spectroscopy (EDS) and scanning electron microscope (SEM) images, the Alicona optical 3D measurement system, and Fourier-transform infrared spectroscopy (FTIR). Results show that during the SPIF process of the metallic specimens, soybean and corn oils attained the highest friction, along forces, roughness, and wear values. Based on the surface roughness measurements, it can be observed that soybean oil produces the worst surface roughness finish in the direction perpendicular to the tool passes (Ra =1.45 μm) considering a vertical step size of 0.25 mm with a 5 mm tool tip diameter. These findings are confirmed through plotting SPIFed Stribeck curves for the soybean and corn oils that show small hydrodynamic span regime changes for an increasing sample step-size forming process. This article elucidates the effects caused by mineral and vegetable oils on the surface of aluminum parts produced as a function of Single Point Incremental Sheet Forming process parameters.

Entities:  

Keywords:  SPIFed Stribeck curve; friction and wear effects; mineral and vegetable oils; single point incremental forming process; surface roughness

Year:  2021        PMID: 34300892     DOI: 10.3390/ma14143973

Source DB:  PubMed          Journal:  Materials (Basel)        ISSN: 1996-1944            Impact factor:   3.623


  4 in total

1.  Comparative Analysis of Machine Learning Methods for Predicting Robotized Incremental Metal Sheet Forming Force.

Authors:  Vytautas Ostasevicius; Ieva Paleviciute; Agne Paulauskaite-Taraseviciene; Vytautas Jurenas; Darius Eidukynas; Laura Kizauskiene
Journal:  Sensors (Basel)       Date:  2021-12-21       Impact factor: 3.576

2.  Parametric Effects of Single Point Incremental Forming on Hardness of AA1100 Aluminium Alloy Sheets.

Authors:  Sherwan Mohammed Najm; Imre Paniti; Tomasz Trzepieciński; Sami Ali Nama; Zsolt János Viharos; Adam Jacso
Journal:  Materials (Basel)       Date:  2021-11-27       Impact factor: 3.623

3.  Polynomial Multiple Regression Analysis of the Lubrication Effectiveness of Deep Drawing Quality Steel Sheets by Eco-Friendly Vegetable Oils.

Authors:  Tomasz Trzepieciński
Journal:  Materials (Basel)       Date:  2022-02-02       Impact factor: 3.623

4.  Investigation of the Robotized Incremental Metal-Sheet Forming Process with Ultrasonic Excitation.

Authors:  Vytautas Ostasevicius; Agne Paulauskaite-Taraseviciene; Ieva Paleviciute; Vytautas Jurenas; Paulius Griskevicius; Darius Eidukynas; Laura Kizauskiene
Journal:  Materials (Basel)       Date:  2022-01-28       Impact factor: 3.623

  4 in total

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