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Nowadays, surface grinding is one of the most common of metal finishing methods. The efficiency of this process is affected by the so-called process parameters such as dressing feed rate (S), rough dressing depth (ar), rough dressing times (nr), fine dressing depth (af), fine dressing times (nf), and non-feeding dressing (nnon). etc. In this paper, the optimization of dressing parameters in surface grinding SKD11 tool steel is studied. The aim of the study is to find the most appropriate value set of dressing parameters to maximize the material removal rate (MRR). In order to solve the problem, the Taguchi method is used. Based on an orthogonal array L16(44x22), sixteen experiments have been conducted. By analyzing the experimental results, an optimal solution of such optimization problem has been solved, presenting the most appropriate dressing parameters as follows: ar = 0.015 mm, nr = 2 times, af = 0.005 mm, nf = 0 times, nnon = 0 times, S = 1.6 m/min. The discovered technology mode has been applied to the real machining process and the outcome shows out a much better result in comparison with default setting modes, that the difference between the model values and the real values of the roughness average is controlled within 3.87% of the ranges.

This study aims to propose a method to calculate optimum exchanged grinding wheel diameter to minimize grinding cost in grinding surface process for stainless steel. The interactions of the grinding cost and optimum exchanged grinding wheel diameter have been analyzed and presented in mathematical formulae. To obtain the minimal grinding cost, the optimal exchanged grinding wheel diameter has been determined by investigating six two-level grinding process parameters including initial grinding wheel diameter, total dressing depth, radial grinding wheel wear per dress, wheel life, machine tool hour and grinding wheel cost. Based on 26 experiments conducted in computational program, the optimal exchanged grinding wheel diameter is presented as a function of these grinding parameters. This developed model has been verified and proven by experimental results. The proposed method of calculation of the optimum exchanged grinding wheel diameter can be applied in practice to reduce the grinding cost.

This paper presents a multi response optimization for dressing parameters for surface grinding SKD11 steel using HaiDuong grinding wheel by grey relational analysis (GRA) in the Taguchi method. The input parameters including feed rate (S), depth of rough dressing (ar), rough dressing times (nr), depth of fine dressing (af), fine dressing times (nf) and non-feeding dressing (nnon) to flatness tolerance (Fl) were investigated and optimized to obtain the smallest flatness tolerance and the highest material removal rate (MRR). The experimental results showed that optimum caculation model with dressing process for surface grinding SKD11 steel using Haiduong grinding wheel is suitable.

Nowadays, surface grinding plays an important role in industry due to the growing demand for increasingly accurate parts with a low production cost. The efficiency of this process is affected by the process parameters such as dressing feed rate (S), rough dressing depth (ar), rough dressing times (nr), fine dressing depth (af), fine dressing times (nf), and non-feeding dressing (nnon). etc. In this paper, the optimization of dressing parameters in surface grinding SKD11 tool steel is presented. The aim of the study is to find the most appropriate value set of dressing parameters to minimize the normal cutting force (Fy). In order to solve the problem, the Taguchi method is employed. Based on an orthogonal array L16(44 × 22), sixteen experiments have been conducted. By analyzing the experimental results, an optimal solution of the optimization problem has been solved, presenting the most appropriate dressing parameters as follows: ar = 0.015 mm, nr = 1 times, af = 0 mm, nf = 0 times, nnon = 0 times, S = 1.8 m/min. The discovered technology mode has been applied into the actual machining process and the outcome shows a much better result in comparison with the default setting modes with the difference between the model values and the real values of the mean normal cutting force controlled within 3.01% of the ranges.

This paper presents an optimization of exchanged grinding wheel diameter for surface grinding alloy tool steel 9CrSi based on the cost analysis for surface grinding. The optimum exchanged grinding wheel diameter was determined by minimizing the cost function. An experiment design was set up, and a computational program was built to perform the experiment in order to calculate the optimum exchanged grinding wheel diameter. The influence of grinding process parameters such as the initial grinding wheel diameter, the total dressing depth, and the radial grinding wheel wear per dress and the wheel life on the optimum exchanged grinding wheel diameter was investigated. In addition, the effect of the cost components such as the machine tool hourly rate and the grinding wheel cost on the optimum diameter of exchanged grinding wheel was also given. From the results, an explicit equation was obtained to determine the optimum exchanged grinding wheel diameter. The calculation value of the optimum exchanged grinding wheel diameter from the formula was also verified by the experiment.

This paper introduces a study on optimum determination of exchanged grinding wheel diameter when external grinding of stainless steel. In this study, the influences of grinding process parameters including the initial grinding wheel diameter, the total dressing depth, the radial grinding wheel wear per dress and the wheel life on the exchanged grinding wheel diameter were investigated. Also, the effect of cost parameters including the grinding wheel cost and the machine tool hourly rate were investigated. To estimate the influence of these parameters on the optimum exchanged grinding wheel diameter, a simulation experiment was designed and it was performed by a computer program. Based on the results of the experiment, a formula for calculation of the optimum exchanged diameter was introduced

The objectives of this research are to determine the optimum values of grinding wheel parameters. An optimization problem with manufacturing time as the objective function was solved. The initial wheel diameter, the wheel life, the radial grinding wheel wear per dress and the total depth of dressing cut were considered as the input factors in the present study. Moreover, their effects on the optimum replaced wheel diameter were explored based on the implementation of a simulation experiment. The obtained results showed that the optimum replaced wheel diameter can be calculated by employing the proposed regression equation.

This paper introduces an optimization study on determination of optimum replaced grinding wheel diameter in internal grinding process. In this study, the minimum manufacturing time was chosen as the objective of optimization problem. Also, several grinding parameters containing the initial grinding wheel diameter, the radial grinding wheel wear per dress, the total depth of dressing cut and the wheel life were taken into the investigation. In addition, to evaluate the influences of these input factors on the optimum replaced wheel diameter, a simulation experiment was conducted. Lastly, a regression model was presented for determination of the optimum replaced wheel diameter.

This paper introduces an optimization study on the determination of the optimum replaced grinding wheel diameter for getting minimum manufacturing time in external grinding stainless steel. In the study, several input grinding parameters including the initial grinding wheel diameter, the total depth of dressing cut, the wheel life and the radial grinding wheel wear per dress. Also, to evaluate the effects of the input parameters on the optimum replaced wheel diameter, a simulation experiment was planned and conducted. Lastly, a regression model to calculate the optimum replaced wheel diameter was suggested.

Grinding cost is an essential factor in a grinding process. In external cylindrical grinding, there exist different input technology parameters which have significant influences on the grinding costs. This paper presents a study on optimization of exchanged grinding wheel diameter to minimize the grinding cost in the external grinding stainless steel. The work is concerned with the influences of seven input grinding process parameters including the initial grinding wheel diameter, the grinding wheel width, the wheel life, the radial grinding wheel wear per dress, the total depth of dressing cut, the machine tool hourly rate, and the grinding wheel cost on the optimum exchanged grinding wheel diameter in the external grinding process based on the optimization of grinding cost. In addition, the effect of the interactions between the input grinding parameters was also evaluated. Finally, the regression equation for computing the optimum exchanged grinding wheel diameter was introduced. The proposed model can be further applied effectively for the external grinding process.

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 L16(44×22). 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.