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European Journal of Applied Sciences – Vol. 12, No. 6

Publication Date: December 25, 2024

DOI:10.14738/aivp.126.17894.

Binh, V. D., Trang, N. V., & Huong, T. T. T. (2024). Using MOORA Method for Finding Best Dressing Parameters for Surface

Grinding Hardox 500. European Journal of Applied Sciences, Vol - 12(6). 169-176.

Services for Science and Education – United Kingdom

Using MOORA Method for Finding Best Dressing Parameters for

Surface Grinding Hardox 500

Vu Duc Binh

Viet Tri University of Industry,

Hanoi, Vietnam

Nguyen Van Trang

Thai Nguyen University of Technology,

Thai Nguyen, Vietnam

Truong Thi Thu Huong

Thai Nguyen University of Technology,

Thai Nguyen, Vietnam

ABSTRACT

This study reports the findings on the use of the multi-criteria decision-making

(MCDM) method to determine the optimal dressing mode for surface grinding of

Hardox 500. The research examined the MCDM issue utilizing the Multi-Objective

Optimization based on Ratio Analysis (MOORA) method, with criterion weights

determined through the Entropy method. Furthermore, surface roughness (RS)

and material removal rate (MRR) were identified as the two criteria for this study.

Additionally, five dressing variables were investigated: non-feeding dressing nn,

fine dressing depth df, fine dressing times nf, rough dressing depth dr, and rough

dressing times nr. Additionally, 16 experimental runs were designed and

conducted using the L16 (44 x 21) design type. The issue related to MCDM has been

assessed. The investigation's findings indicate that option No. 5, defined by the

input parameters dr = 0.02 (mm), nr = 1, nf = 1, df = 0.01 (mm), and nn = 2,

represents the optimal dressing mode.

Keywords: Surface grinding, Hardox 500, MOORA method, ENTROPY method, Surface

Roughness, Material Removal Rate.

INTRODUCTION

So far, different studies have been performed to explore the grinding process. E. Irazu et al. [1]

carried an examination into the impact of grinding wheel wear on cutting forces, analyzing

grinding wheel topography to find a measure that quantifies grinding wheel wear non- destructively. It was reported that, following a brief conditioning phase, cutting forces rise in

an essentially linear manner with the machined length. During this second phase, the force

ratio tends toward a constant value, and the primary wear process is the formation of flat

surfaces on the diamond grains. In these circumstances, the 3D surface roughness metrics Sa,

Sq, Spk, and Sku have demonstrated efficacy in monitoring wheel wear. Le X.H. et al. [2]

performed a study on the optimal computation of the exchanged diameter of grinding wheels

in the internal grinding of stainless steel. This study examined the impact of grinding process

parameters, including initial diameter, total depth of dressing cut, wheel life, radial grinding

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European Journal of Applied Sciences (EJAS) Vol. 12, Issue 6, December-2024

wheel wear per dress, and the ratio of length to diameter of workpieces, on the exchanged

grinding wheel diameter. The impact of cost considerations, including the hourly rate of

machine tools and the expense of grinding wheels, was also examined. A proposed model for

determining the optimal swapped grinding wheel diameter was presented based on the

study's findings. Tran T.H. et al. [3] conducted a study to examine the influence of process

factors on the surface roughness in surface grinding of 90CrSi tool steel. This study

considered process characteristics such as coolant concentration, coolant flow, cross feed,

table speed, and depth of cut. The impact of the process parameters on surface roughness was

assessed. A predictive methodology for calculating surface roughness was proposed. L.M.

Kozuro et al. [4] suggested a dressing process for external grinding that can obtaining a

surface roughness of Ra=0.32-1.25 (μm). This technique includes a longitudinal feed rate of

0.4 m/min, four dressing passes with a dressing depth of 0.03 mm, and four non-feeding

dressing runs. Hoang X.T. et al. [5] presented a study on the computation of the optimal

exchanged grinding wheel diameter in the external grinding of 9CrSi tool steel. This study

examined the impact of grinding process factors, including starting grinding wheel diameter,

total dressing depth, radial grinding wheel wear per dress, and wheel life on the exchanged

grinding wheel diameter. Additionally, the influence of cost factors such as the machine tool

hourly rate and the grinding wheel expense was examined. A model has been given to figure

out the optimal replaced grinding wheel diameter based on the data. Le X.H. et al. [6]

accomplished a study on the optimization of dressing parameters in internal cylindrical

grinding to achieve the maximum material removal rate. This study examined the effects of

dressing parameters, including dressing feed rate, coarse dressing depth, coarse dressing

frequency, fine dressing depth, fine dressing frequency, and dressing count without depth of

cut, on the material removal rate. Tran T.H. et al. [7] performed a study to identify the optimal

dressing parameters for achieving the minimal flatness tolerance in the grinding of SKD11

steel with a HaiDuong grinding wheel. This research examines the impact of six input

parameters—feed rate (S), depth of rough dressing cut (ar), rough dressing frequency (nr),

depth of finish dressing cut (af), finish dressing frequency (nf), and non-feeding dressing

(nnon)—on flatness tolerance. Nguyen H.Q. et al. [8] carried out a study addressing the MCDM

problem in the dressing process for internal grinding. This study employed four Multiple

Criteria Decision Making (MCDM) methodologies: TOPSIS, MARCOS, EAMR, and MAIRCA, to

tackle the MCDM issue and fulfill the dual aims of lowering SR and maximizing MRR. The ideal

solution for the multi-criteria issue in the internal grinding dressing process has been

presented based on the data obtained. S. Zhang et al. [9] proposed a novel approach for

preparing diamond grinding wheels utilizing abrasive waterjet (AWJ) technology to mitigate

workpiece damage and wheel clogging associated with grinding challenging materials using

traditional diamond grinding wheels. The primary process parameters were established

according to the theoretical model for treating diamond grinding wheels utilizing AWJ.

Response surface methodology (RSM) and backpropagation artificial neural networks (BP- ANN) were utilized to develop regression models correlating process factors with

microgroove features. A comparative analysis was conducted to assess the predictive efficacy

of both RSM and BP-ANN. The findings demonstrated that both BP-ANN and RSM are effective

methodologies for forecasting microgroove attributes. Tran T.H. et al. [10] performed a study

to determine the optimal exchanged grinding wheel diameter to reduce grinding costs in the

surface grinding process for stainless steel. The relationship between grinding costs and the

optimal swapped grinding wheel diameter has been investigated and expressed in

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171

Binh, V. D., Trang, N. V., & Huong, T. T. T. (2024). Using MOORA Method for Finding Best Dressing Parameters for Surface Grinding Hardox 500.

European Journal of Applied Sciences, Vol - 12(6). 169-176.

URL: http://dx.doi.org/10.14738/aivp.126.17894

mathematical formulas. The optimal exchanged grinding wheel diameter, necessary for

minimizing grinding costs, has been established as a function of various parameters, including

the initial grinding wheel diameter, total dressing depth, radial grinding wheel wear per

dress, wheel life, machine tool hours, and grinding wheel cost. Nguyen T.T. et al. [11]

evaluated the impact of dressing regime factors on roundness tolerance in the external

grinding of SKD11 steel. This study assessed the impact of rough dressing depth, dressing feed

rate, fine dressing depth, rough dressing frequency, fine dressing frequency, and non-feeding

dressing frequency on roundness tolerance. The recommended optimum dressing parameters

are as follows: fine dressing times (nf) of 3, non-feeding dressing times (no) of 3, fine dressing

depth (af) of 0.01 mm, rough dressing times (nr) of 3, rough dressing depth (ar) of 0.03 mm,

and dressing feed rate (Sd) of 1.0 m/min. Tran T.H. et al. [12] performed an optimization

analysis to ascertain the ideal swapped grinding wheel diameter for external grinding. This

study examined seven input grinding parameters: starting grinding wheel diameter, grinding

wheel width, wheel life, radial grinding wheel wear per dressing, total depth of dressing cut,

machine tool hourly rate, and grinding wheel cost. The impact of grinding parameters on the

optimal exchanged grinding wheel diameter for the external cylindrical grinding process was

analyzed in conjunction with the screening trials. The impact of the interactions among the

input grinding parameters was also assessed. The regression equation for determining the

optimal swapped grinding wheel diameter was presented. Tran T.H. et al. [13] undertook a

study to find the ideal dressing conditions for grinding SKD11 tool steel using a HaiDuong

grinding wheel. This study examined the impacts of six input parameters: feed rate, depth of

rough dressing cut, rough dressing duration, depth of finish dressing cut, finish dressing

duration, and non-feeding dressing. Tran N.G. et al. [14] reported the findings of a multi- objective optimization study on internal cylindrical grinding of SKD11 steel aimed at

minimizing surface roughness. This study examined six dressing parameters: coarse dressing

depth, number of coarse dressings, fine dressing depth, number of fine dressings, non-feeding

dressing, and dressing feed speed. The findings indicate that the ideal surface roughness is

0.111 μm, achieved with optimal dressing parameters: fine dressing depth at level 2, number

of fine dressings at level 3, number of non-feeding dressings at level 4, number of coarse

dressings at level 3, coarse dressing depth at level 2, and dressing feed rate at level 1. Hoang

X.T. et al. [15] proposed an optimization for external grinding of 9XC steel to achieve lowest

surface roughness.

This study examined three dressing modes: coarse dressing, fine dressing, and non-feeding

dressing. The subsequent optimal dressing parameters were recommended: The coarse

dressing depth is 0.07 mm, the fine dressing depth is 0.02 mm, and the number of non-feeding

dressing cycles is 3. Le X.H. et al. [16] executed an investigation to optimize dressing

parameters to achieve minimal surface roughness in internal grinding of SKD11 steel via the

Taguchi method. The utilized input parameters include coarse dressing depth, quantity of

coarse dressings, fine dressing depth, quantity of fine dressings, non-feeding dressing, and

dressing feed velocity. The quantity of coarse dressing exerts the most significant influence on

Ra (88.28%). The difference between the experimental roughness average and the predicted

value is negligible. Hoang A.L. et al. [17] handled a study to determine the most effective

dressing method for the external grinding of SKD11 tool steel. They applied the MABAC

(multi-attributive border approximation area comparison) technique for this objective. The

aim of the research is to determine the ideal dressing technique that concurrently attains the