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The findings of a study on the application of the MCDM technique to select the best input parameters in wire-cut electrical discharge machining (wire-cut EDM) 90CrSi tool steel are presented in this paper. The TOPSIS method was used in the study to solve the MCDM problem, and the Entropy method was used to compute the weights of the criteria. In this work, six input parameters including the cutting voltage VM, the pulse on time ton, the pulse off time toff, the servo voltage SV, the wire feed WF, the feed speed SPD, and the workpiece cutting radius R were investigated. Also, a 27-2 design experiment was performed and a total of 32 experimental runs were conducted. The MCDM problem was solved. According to the findings of this study, the best experimental setup is experiment No. 7 with the following input parameters: VM=9 (V), Ton=12 (s), Toff=13 (s), SV=25 (V), WF=8 (mm/min), SPD=4.5 (mm/min), and R=9 (mm).

This paper presents an optimization of dressing conditions for SKD-11 steel grinding using HaiDuong grinding wheel made in Vietnam. Taguchi method was used to design experiment and calculate the optimized dressing conditions. Effects of the six input parameters including feed rate (S), depth of rough dressing cut (aedr), rough dressing times (nr), depth of finish dressing cut (aedf), finish dressing times (nf) and non-feeding dressing (nnon) with 4 levels on the machined surface roughness were investigated for optimization process. To find out the influence degree of each input parameter on output results, S/N ratio was analysized. Experimental results show that the average surface roughness after 3 times of the repeated experiments was 0.208 μm and deviation was 11.23% comparing with the predicted values.

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 is to determine effects of the dressing parameters to the flatness tolerance (Fl) when grinding SKD11 steel using HaiDuong grinding wheel and also propose the suitable dressing parameters to obtain the smallest flatness tolerance. In this paper, the effects of the six input parameters including feed rate (S), depth of rough dressing cut (ar), rough dressing times (nr), depth of finish dressing cut (af), finish dressing times (nf) and non-feeding dressing (nnon) to the flatness tolerance were investigated. To find out the influence of each input parameter on output results, the S/N ratio was analysized. Evaluated experimental results show that, the average flatness tolerance was 4.05μm and deviation of this value was 11.38% compared with the predicted value.

This article describes an optimization of dressing parameters to improve the wheel life in surface grinding of hardened SKD 11 steel by using the Taguchi method. Dressing parameters including dressing feed rate, coarse dressing depth, coarse dressing times, fine dressing depth, fine dressing times, and non-feeding dressing were investigated to determine their influence on the wheel life. The DOE method developed by G. Taguchi was selected to design the experiments. An analysis of the signal-to-noise (S/N) response and ANOVA were conducted to obtain the optimal values of dressing parameters for maximizing the wheel life. In the results section, the coarse dressing times and the coarse dressing depth are determined to be the most influential factors which give a statistically significant effect on wheel life. Also, a predictive value of the average wheel life is given with a 3.6% deviation from the verification experiment.

This work is done to determine the effects of the input factors of powder mixed electrical discharge machining (PMEDM) process on the material removal rate (MRR). In the study, the workpiece is cylindrical parts made from 90CrSi alloy steel. Also, five factors containing the pulse on time Ton, the powder concentration Cp, the pulse off time Toff, the pulse current IP, and the server voltage SV were discovered to find their impact on MRR. In addition, the Taguchi method and ANOVA analysis were used to design experiment and analyze the results. In addition, an optimal model of the MRR was introduced. Also, the model has been well verified by comparison with testing, and so it can be used for further studies in the PMEDM process.

This paper introduces an experimental study on the influence of electrical discharge machining (EDM) cylindrical shaped parts made of 90CrSi tool steel. In this work, some experiments were designed and analysed based on Taguchi method. Also, four input parameters including the pulse on time, the pulse off time, the current, and the server voltage were investigated. The influence of these parameters on the surface roughness were estimated by analysing variance. In addition, the optimum input parameters were found for getting the minimum surface roughness.

This paper introduces an optimization study on electrode wear when electrical discharge machining (EDM) cylindrical shaped parts made from 90CrSi. In the study, the experiments were performed and analyzed by using Taguchi method. The input parameters of the experiments were the pulse on time, the pulse off time, the current, and the server voltage. The effect of input parameters on the electrode wear were evaluated by analyzing variance. Also, the optimum values of the input parameter were proposed for getting the minimum electrode wear.

This paper aims to investigate the effect of process parameters on the surface roughness in suface grinding 90CrSi tool steel. In this paper, many process parameters including the coolant concentration, the coolant flow, the cross feed, the table speed and the depth of cut were taken into account. Based on conducting and analysing 25 experiments which were created by using full factorial design, the influence of the process parameters on the surface roughness was evaluated. Also, a predicted model to calculate the surface roughness was proposed.

This paper introduces a study on multi-criteria optimization of the dressing parameters in surface grinding for 90CrSi tool steel. The aim of the study is to minimize the surface roughness, the normal shear force and maximize the grinding wheel life by using Taguchi method and Grey Relational Analysis (GRA). This multi-objective optimization is obtained by optimizing four four-level and two two-level dressing parameters in sixteen experiments based on an orthogonal array L16(44×22). From the results of the study, the optimum dressing parameters were proposed. Also, to evaluate the optimum dressing model, an experiment was performed. The results of the comparison between the predicted model and the experiment show that the proposed model has been proven and it can be used for further applying of surface grinding.

This paper presents a study on analysis of influences of the surface roughness in Electrical Discharge Machining 90CrSi tablet shape punches with the use of copper electrode. In this paper, 9 experimental runs were designed and conducted by using Taguchi method. In addition, 4 process parameters including the gap voltage, the pulse current, the pulse on time and the pulse off time were investigated. The influences of these input parameters on the surface roughness were evaluated by analysing variance. Also, from the experimental results, optimum values of the input parameters for getting the minimum surface roughness were proposed.

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.

To overcome the limits of the electrical discharge machining (EDM) process, the nanoscale fine powder is added to the dielectric in a new machining method called powder mixed electrical discharge machining (PMEDM). In this research, the Taguchi approach has been applied to determine the effects of PMEDM parameters such as the powder concentration, the pulse-on-time, the pulse-off-time, the pulse current, and the server voltage to material removal rate (MRR) in hardened 90CrSi steel processing. L18 orthogonal array, signal to noise (S/N) ratio, and ANOVA were employed to plan and analyze the experiment. The pulse current was determined to be the factor that had the strongest impact on MRR. Moreover, an optimal EDM condition was found to improve MRR. The powder concentration of 3.5 g/l, the pulse-on-time of 6 µs, the pulse-off-time of 30 µs, the pulse current of 12 A, and the server voltage of 5 V resulted in maximum MRR.

The aim of this study is to optimize output responses as minimum surface roughness and maximum material removal rate (MRR) of Electrical Discharge Machining (EDM) process when machining hardened 90CrSi steel. Thank to this process the combination of machining parameters obtained by minimizing problems is found. The machining parameters for EDM process under consideration include concentration of powder, pulse – on - time, pulse - off - time, current, and voltage. The experiments are set up based on the L18 orthogonal array of Taguchi method, and analysis has been carried out using Grey Relational Analysis (GRA) to find the optimal set of machining parameters. ANOVA is also used to determine which parameters have the significant effects on the output responses. Finally, the experiments are performed to validate the optimal set of machining parameters. The results show that Current has the strongest influence (32,63%), and Pulse off time has the smallest effects (1,04%) on the grey grade value. The confirmation experiment and ANOVA show the reliability of the proposed model which can be considered as an effective method to predict the surface roughness and material removal rate.

The dressing plays an important role in wheel preparation in the grinding process. In this study, Grey Relational Analysis (GRA) based Taguchi method is applied to optimize the dressing parameters for minimizing the surface roughness and maximizing the material removal rate (MRR) in surface grinding of hardened SKD 11 steel. The Taguchi technique L16 is used to organize experiments that include six input parameters of the dressing process. There are two two-level parameters and four 4-level parameters including dressing feed rate, rough dressing depth, rough dressing times, fine dressing depth, fine dressing times, and non-feeding dressing. As shown in the result, the optimal dressing process for the minimum surface roughness and maximum MRR consists of 2 times of the rough dressing with a depth of 0.015 mm/stroke, a feed rate of 1.6 mm/min, 3 times non-feeding dressing, and no fine dressing was performed. Also, the dressing feed rate has the strongest impact on multiple performance characteristics (with 43.24% contribution), followed by the rough dressing depth (with 26.20% contribution). A verification experiment has demonstrated the appropriateness of the predictive model to the measurement data.

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

This study has been done to optimize the dressing parameters in internal cylindrical grinding process for 9CrSi tool steel to minimize surface roughness and maximize material removal rate (MRR) using Taguchi method and Grey Relational Analysis (GRA). This multi-objective optimization is obtained by optimizing five three-level and one six-level dressing parameters in eightteen experiments based on an orthogonal array L18(35×16). The results show that the optimal dressing parameters to obtain the minimal roughness average and maximal MRR are the coarse dressing depth of 0.02 mm, the coarse dressing times of 1 time, the fine dressing depth of 0.005 mm, the fine dressing times of 3 times, the non-feeding dressing of 5 times and the dressing feed rate of 1.4 m/min, respectively. The differences of the roughness average and MRR from the experiments and the predict model are small. Thus, the proposed method has been proven and it can be further applied in other studies.

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 presents a study on the determination of the optimum gear ratios of a two-stage worm gearbox. To find the optimum gear ratios, an optimization problem was performed. Also, the reasonable gearbox structure was chosen as the objective function of the optimization problem. In addition, the effects of the input factors including the total gearbox ratio, the electric motor speed, and the output torque were investigated. Besides, a simulation experiment was designed and performed by computer programs to evaluate the influences of these input factors on the optimum gear ratios. Moreover, some models to calculate the optimum gear ratios of a two-stage worm gearbox were suggested. As these equations are explicit, the determination of the optimum gear ratios is accurate and uncomplicated.

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.

The paper presents a study on determining optimum gear ratios of mechanical driven systems using a two-stage helical gearbox with second stage double gear sets and a chain drive. In the study, an optimization problem with the objective function as the minimum system length was solved. In addition, the effects of the input parameters including the total gearbox ratio, the wheel face width coefficient, the allowable contact stress and the output torque on the optimal transmission ratios were evaluated by conducting a simulation experiment. Moreover, several equations to find the optimum gear ratios were proposed.

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.

A study on the calculation of the optimum gear ratios of mechanical driven systems using a worm-helical gearbox and a chain drive was presented. To find the optimum gear ratios, an optimization problem in which the height of the system was selected as the objective function was conducted. Also, the influences of the input parameters including the total gear ratio of the system, the calculated coefficient of the worm diameter coefficient, the coefficient of wheel face width and the allowable contact stress of helical gear unit, and the output torque were examined. To weigh the effect of these parameters on the optimum gear ratios, a simulation experiment was performed by computer programming. Additionally, equations to calculate the optimum gear ratios were introduced. Using these equations, the optimum gear ratios can be found easily and accurately because the equations are all in the explicit form.

In this paper, a study on calculating optimum gear ratios of mechanical driven systems using a chain drive and a two-step helical gearbox with the first step double gear sets is introduced. To determine the optimum ratios, an optimization problem was conducted with the selection of system cross section area as the objective function. Also, several input parameters consisting of the total system ratio, the wheel face width coefficients of the both helical gear sets, the allowable contact stress and the output torque were investigated. Furthermore, a simulation experiment was run to study the impacts of these parameters on the optimum ratios. The results show that the optimum ratios can be obtained with high accuracy by using recommended models.

The present work is concerned with determining optimum gear ratios of mechanical driven systems using a two-stage helical gearbox with second stage double gear sets and a chain drive. During the research process, the construction of an optimization problem has been implemented. The minimal system cross section area was selected as the objective function. Afterwards, a simulation experiment was conducted with the aim of exploring the dependence of the optimal transmission ratios on the input factors including the total gearbox ratio, the wheel face width coefficient, the allowable contact stress and the output torque. The recommended equations can be applied to obtain the optimal gear ratios.

This paper presents a new study on the optimum determination of gear ratios of a two-stage helical gearbox. In this study, in order to find the optimum gear ratios of the gearbox, the acreage of the cross section of the gearbox was chosen as the objective function of the optimization problem. Besides, the effects of input parameters including the total gearbox ratio, the wheel face width coefficient, the output torque and the allowable contact stress were considered. To evaluate the effect of these factors on the optimum gear ratios, an “experiment” was designed and a computer program was built to perform the “experiment”. From the results of the study, models for calculation of the optimum gear ratios of a two-stage helical gearbox were proposed. Using these models, the gear ratios can be determined accurately and simply.