Open AccessOptimization of dressing parameters of grinding wheel for 9CrSi tool steel using the taguchi method with grey relational analysis
Author(s) -
Luu Anh Tung,
Vu Ngoc Pi,
Vu Thi Kim Lien,
Tran Thi Hong,
Lê Xuân Hưng,
Banh Tien Long
Publication year - 2019
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/635/1/012030
Subject(s) - flatness (cosmology) , taguchi methods , grey relational analysis , orthogonal array , surface roughness , grinding , surface finish , mathematics , materials science , composite material , statistics , physics , cosmology , quantum mechanics
This study aims to optimize the dressing parameters of grinding wheel for 9CrSi tool steel to minimize roughness average and flatness tolerance using Taguchi method and Grey Relational Analysis (GRA). These objectives are minimized by optimizing four four-level and two two-level dressing parameters in sixteen experiments based on an orthogonal array L 16 (4 4 ×2 2 ). Taguchi method and GRA are combined to solve the multi-objective optimization problem and determine optimal dressing parameter level combination. Results show that, the optimal dressing parameters to obtain the minimal roughness average and flatness tolerance are coarse dressing depth of 0.025 mm, coarse dressing times of 3 times, fine dressing depth of 0.005 mm, fine dressing times of 2 times, non-feeding dressing of 3 times and dressing feed rate of 1.6 m/min, respectively. Experiments with the optimized dressing parameters have been done to verify the predict model. Results of the roughness average and flatness tolerance from the experiments match with those values of the models and satisfy practical requirements.