An intelligence-based optimization of the internal burnishing operation for surface roughness and vicker hardness

  • Can Xuan Khanh

    Department of Manufacturing Technology, Le Quy Don Technical University, No 236 Hoang Quoc Viet Street, Ha Noi, Viet Nam
  • Le Xuan Ba

    CoBarny Limited Mechanical 25, Phu Minh Commune, Soc Son District, Ha Noi, Viet Nam
  • Nguyen Truong An

    Department of Manufacturing Technology, Le Quy Don Technical University, No 236 Hoang Quoc Viet Street, Ha Noi, Viet Nam
  • Trinh Quang Hung

    Department of Manufacturing Technology, Le Quy Don Technical University, No 236 Hoang Quoc Viet Street, Ha Noi, Viet Nam
  • Nguyen Trung Thanh

    Department of Manufacturing Technology, Le Quy Don Technical University, No 236 Hoang Quoc Viet Street, Ha Noi, Viet Nam
Email: trungthanhk21@mta.edu.vn
Từ khóa: Internal burnishing, Surface roughness, Vickers hardness, Minimum quantity lubrication, Optimization.

Tóm tắt

Boosting machining quality is a prominent solution to save production costs for burnishing operations. In this work, a machining condition-based optimization has been performed to decrease surface roughness (SR) and enhance Vickers hardness (VH) of the minimum quantity lubrication-assisted burnishing operation (MQLABO). The burnishing factors are the spindle speed (S), depth of penetration (D), and the air pressure (P). The burnishing trails of the hardened material labeled 40X have been conducted on a milling machine. The adaptive neuro-based-fuzzy inference system (ANFIS) was used to construct the correlations between the process inputs and MQLABO responses. The non-dominated sorting genetic algorithm-II (NSGA-II) is utilized to determine the optimal parameters. The scientific outcomes revealed that the optimal values of the S, D, and P are 800 RPM, 0.09 mm, and 4.0 Bar, respectively. The SR is decreased by 53.8%, while the VH is enhanced by 3.1%, respectively, as coBarred to the initial values.

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22/12/2020
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26/01/2021
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