THE PREDICTION AND OPTIMIZATION OF SURFACE ROUGHNESS IN GRINDING OF S50C CARBON STEEL USING MINIMUM QUANTITY LUBRICATION OF VIETNAMESE PEANUT OIL

Thuy Nguyen; Van Thien Nguyen; Van Canh Nguyen; Tien Dung Hoang; Ngoc Hoanh Dao; Hien Do Minh

doi:10.5937/jaes0-30580

Thuy Nguyen https://orcid.org/0000-0001-9121-2970
Van Thien Nguyen https://orcid.org/0000-0001-9489-7717
Van Canh Nguyen Dept of Manufacturing Technology, Faculty of Mechanical Engineering, Hanoi University of Industry
Tien Dung Hoang https://orcid.org/0000-0003-3543-7539
Ngoc Hoanh Dao https://orcid.org/0000-0002-7208-646X
Hien Do Minh https://orcid.org/0000-0003-3543-7539

DOI: https://doi.org/10.5937/jaes0-30580

Keywords: optimization, regression optimizer, minimum quantitiy lubricant, multi-response optimization, grinding

Abstract

This experimental research aimed to build the regression model of grinding S50C carbon steel based on a Regression Optimizer. The workpiece specimens were JIS S50C carbon steel that was hardened at 52HRC. Taguchi L27 orthogonal array was performed with 5 3-levels-factors. The studied factors were combining cutting parameters, such as cutting speed, feed rate, depth of cut, and lubricant parameters, including air coolant flow rate Q and air pressure P. The results show that cutting parameters includes workpiece velocity V_w, feed rate f, and depth of cut t, influence the most on surface roughness R_a, Root Mean Square Roughness R_q, and Mean Roughness Depth R_z,. By contrast, the influence of lubrication parameters is fuzzy. Therefore, this present work focused on predicting and optimizing R_a, R_z, R_q in surface grinding of JSI S50C carbon steel using MQL of peanut oil.

In this work, combining of grinding parameters and lubrication parameters were considered as input factors. The regression models of R_a, R_z, and R_q were obtained using Minitab 19 by Regression Optimizer tool, and then the multi-object optimization problem was solved.

The present findings have shown that Vietnamese vegetable peanut oil could be considered as the lubricant in the grinding process. The optimum grinding and lubricant parameters as following: the workpiece velocity V_w of 5 m/min, feed rate f of 3mm/stroke, depth of cut of 0.005mm and oil flow rate, air pressure of 91.94 ml/h, 1 MPa, respectively. Corresponding to the surface roughness R_a, Root Mean Square Roughness R_q, and Mean Roughness Depth R_z of 0.6512mm, 4.592mm, 0.8570mm, respectively.

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