MODELING AND OPTIMIZING SURFACE ROUGHNESS IN TURNING 40X STEEL BASED ON GENETIC PROGRAMMING AND GREY WOLF OPTIMIZATION ALGORITHMS

  • Duong Xuan Bien
  • Do Manh Tung
  • Nguyen Van Nam
  • Le Van Tan
  • Do Tien Lap
  • Ta Huu Vinh
  • Le Thanh Binh
Keywords: Self-rotary turning tool, regression model, surface roughness, genetic programming, GWO.

Abstract

This paper presents the results of establishing a predictive model and
optimizing the surface roughness (SR) value when turning 40X steel using genetic
programming (GP) algorithm and grey wolf optimization (GWO) algorithm. The
regression equation is built by GP algorithm on the basis of 63 practical experiments
with cutting parameters including rotary tool tilt angle, depth of cut, feedrate and
cutting speed. The GWO algorithm is used to find the most suitable cutting
parameters corresponding to the minimum SR value. Furthermore, the influence of
these parameters on the SR value is also considered. The research results allow to
evaluate the effectiveness of the algorithms used as well as the basis for improving
the surface quality in dry turning with selt-driven rotary tool in some specific
application cases.

điểm /   đánh giá
Published
2024-08-01
Issue
Tập 60.Số 05 (2024)
Section
RESEARCH AND DEVELOPMENT