4.7 Article

Surface and subsurface analysis of TC18 titanium alloy subject to longitudinal-torsional ultrasonic vibration-assisted end milling

Journal

JOURNAL OF ALLOYS AND COMPOUNDS
Volume 929, Issue -, Pages -

Publisher

ELSEVIER SCIENCE SA
DOI: 10.1016/j.jallcom.2022.167259

Keywords

TC18 titanium alloy; Longitudinal -torsional ultrasonic vibration; assisted milling; Surface morphology; Plastic deformation layer

Funding

  1. Research Fund for High-Level Talents of Pingdingshan University
  2. National Project Cultivation Fund of Pingdingshan University
  3. Key Research Project of Institutions of Higher Education in Henan Province
  4. Henan Province Science and Technology Equipment Key Project
  5. [PXY-BSQD-202014]
  6. [PXY-PYJJ-202105]
  7. [21A430029]
  8. [212102210349]

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Longitudinal-torsional ultrasonic vibration-assisted milling is an effective method for improving the quality of machined surfaces. This study investigated the effects of ultrasonic amplitude, feed rate, and cutting speed on surface morphology, roughness, residual stress, and subsurface microstructure in the end milling of TC18 titanium alloy. The results showed that the milling process with longitudinal-torsional ultrasonic vibration assistance resulted in more distinct surface microtextures at larger amplitude, smaller feed rate, and higher cutting speed. Compared to conventional milling, the ultrasonic vibration-assisted milling generated higher roughness, surface residual stress, and deeper plastic deformation layer in the subsurface. The research provides insights into surface machining of titanium alloy and quality control of machined surface.
Longitudinal-torsional ultrasonic vibration-assisted milling is a machining method that can effectively improve the quality of the machined surface. When this method is used for the end milling of TC18 titanium alloy, however, the law of influence on the machined surface and subsurface remains unclear. In this study, we examined the effects of the ultrasonic amplitude, feed rate, and cutting speed on the machined surface morphology, roughness, surface residual stress, and subsurface microstructure in the longitudinal-torsional ultrasonic vibration-assisted end-milling process. According to the results, longitudinal-torsional ultrasonic vibration-assisted end milling can help form more obvious surface microtextures with a more distinct surface texture regularity at large amplitude, small feed rate, and high cutting speed. Compared with conventional milling, longitudinal-torsional ultrasonic vibration-assisted milling generates a larger roughness and surface residual stress and a deeper plastic deformation layer of the subsurface in the case of an obvious highly perturbed layer. In addition, the surface residual stress becomes greater and the plastic deformation layer gets deeper at a larger amplitude. When the amplitude was 5 pm, the surface residual stress was - 450.625 MPa and the depth of the deformation layer was 5.4 pm. The stress and depth in-creased by 21.55 % and 134.78 %, respectively, compared with those of conventional milling. The increase in the feed rate enhanced the roughness, decreased the surface residual stress, and did not significantly alter the depth of the plastic deformation layer. When the feed rate was 0.01 mm/z, the roughness was 0.383 pm and the surface residual stress was - 479.1 MPa. The feed rate and roughness increased by 42.63 % and 20.62 %, respectively, compared with those of conventional milling. With the increase in the cutting speed, the roughness increased, and the surface residual stress and the depth of the plastic deformation layer de-creased. When the cutting speed was 15 m/min, the roughness was 0.31 pm, the surface residual stress value was - 454.7 MPa, and the depth of the plastic deformation layer was 5.7 pm. These three parameters increased by 17.8 %, 18.79 %, and 92.5 %, respectively, compared with those of conventional milling. This research has certain application prospect in surface machining of titanium alloy and quality control of machined surface.(c) 2022 Elsevier B.V. All rights reserved.

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