Optimization of Grinding Parameters for Minimum Grinding Time When Grinding Tablet Punches by CBN Wheel on CNC Milling Machine

Pi, Vu Ngoc; Nguyen, Quoc-Tuan; Tran, Thi-Hong; Le, Hong-Ky; Nguyen, Anh-Tuan; Luu, Anh-Tung; Nguyen, Van-Tung; Le, Xuan-Hung

doi:10.3390/app9050957

Cited by 33 publications

(15 citation statements)

References 13 publications

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“…After that, determine g ij by (13). The final Q i values are then found by (14). Several calculated results and alternative ranking when using the MAIRCA method are presented in Table 7 using the Entropy and MEREC methods for calculating the weights of criteria.…”

Section: 2 Results Of Mcdm When Using the Mairca Methodsmentioning

confidence: 99%

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Application of topsis, mairca and EAMR methods for multi-criteria decision making in cubic boron nitride grinding

Huy¹,

Hien

Danh

et al. 2022

EEJET

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Determining the best cutting mode is a common problem for machining processes as well as for CBN (Cubic Boron Nitride) grinding on Computer Numerical Control (CNC) machines. It is even more important when it is necessary to choose a solution that meets many goals, which are in conflict. This paper presents the results of a multi-criteria decision-making (MCDM) study on CBN grinding of cylindrical-shaped parts on CNC milling machines. Three MCDM methods, including TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution), MAIRCA (Multi-Attributive Ideal-Real Comparative Analysis), and EAMR (Evaluation by an Area-based Method of Ranking) were applied in this work. Besides, MEREC (Method based on the Removal Effects of Criteria) and Entropy methods were used to determine the weights of the criteria. In addition, the Taguchi method with L18 orthogonal array (6^1+3^3) design was used for the design of an experiment, which has four input factors including the depth of dressing cut, the spindle speed, the feed rate, and the wheel diameter. Two criteria, including the surface roughness (SR) and the material removal speed (MRS) were selected as the response outputs. The reason for choosing these two criteria is because SR and MRS are two very important output factors of a mechanical machining process as well as of the CBN grinding process on a CNC milling machine. In particular, these two criteria are always in conflict with each other. Small SR requirements will require small values of the feed speed and the depth of cut. This will lead to the reduction of MRS. From the results of this study, the use of different methods for MCDM was evaluated. In addition, rankings of alternatives have been given according to MCDM methods. Furthermore, the best alternative to guarantee both the minimum SR and the maximum MRS has been found

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Section: 2 Results Of Mcdm When Using the Mairca Methodsmentioning

confidence: 99%

“…because these parts require high precision grinding and long wheel life. Recently, CBN grinding has been applied to process cylindrical-shaped parts on CNC milling machines [14]. As previously stated, many studies on MCDM for machining processes have been conducted to date.…”

Section: Literature Review and Problem Statementmentioning

confidence: 99%

Application of topsis, mairca and EAMR methods for multi-criteria decision making in cubic boron nitride grinding

Huy¹,

Hien

Danh

et al. 2022

EEJET

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“…Because increasing the cutting parameters increases MRR and cutting power at the same time, there are uncertainties in the selection process of suitable parameter combinations [5]. Therefore, there is always a need for an effective optimization method to determine the optimum combination of parameters [6][7][8]. This is important in terms of the sustainability assessment, which covers the consumed energy, machining costs, and eco-friendly manufacturing [9][10][11].…”

Section: Introductionmentioning

confidence: 99%

Parametric Optimization for Cutting Forces and Material Removal Rate in the Turning of AISI 5140

et al. 2021

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The present paper deals with the optimization of the three components of cutting forces and the Material Removal Rate (MRR) in the turning of AISI 5140 steel. The Harmonic Artificial Bee Colony Algorithm (H-ABC), which is an improved nature-inspired method, was compared with the Harmonic Bee Algorithm (HBA) and popular methods such as Taguchi’s S/N ratio and the Response Surface Methodology (RSM) in order to achieve the optimum parameters in machining applications. The experiments were performed under dry cutting conditions using three cutting speeds, three feed rates, and two depths of cuts. Quadratic regression equations were identified as the objective function for HBA to represent the relationship between the cutting parameters and responses, i.e., the cutting forces and MRR. According to the results, the RSM (72.1%) and H-ABC (64%) algorithms provide better composite desirability compared to the other techniques, namely Taguchi (43.4%) and HBA (47.2%). While the optimum parameters found by the H-ABC algorithm are better when considering cutting forces, RSM has a higher success rate for MRR. It is worth remarking that H-ABC provides an effective solution in comparison with the frequently used methods, which is promising for the optimization of the parameters in the turning of new-generation materials in the industry. There is a contradictory situation in maximizing the MRR and minimizing the cutting power simultaneously, because the affecting parameters have a reverse effect on these two response parameters. Comparing different types of methods provides a perspective in the selection of the optimum parameter design for industrial applications of the turning processes. This study stands as the first paper representing the comparative optimization approach for cutting forces and MRR.

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“…These works have implemented optimization problems with different grinding methods such as external cylindrical grinding [4,8,9], surface grinding [10][11][12][13][14][15], and internal grinding [16]. These optimization problems have addressed not only traditional grinding machines [3][4][5][6][7][8][9][10][11][12][13][14][15][16] but also CNC milling machines [17]. They have established different objective functions.…”

Section: Introductionmentioning

confidence: 99%

Optimization of Replaced Grinding Wheel Diameter for Surface Grinding Based on a Cost Analysis

Tran

Luu

Nguyen

et al. 2019

Metals

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Based on a cost analysis, a method of identifying and predicting optimum replaced grinding wheel diameter (De.op) in a surface grinding operation for 9CrSi steel material was developed in this study. The De.op value was determined by minimizing the cost function. An experimental design was set up, and a computational program was developed to perform the experiment in order to calculate the De.op value. Furthermore, the impact of the grinding process parameters such as the initial grinding wheel diameter, the grinding wheel width, the total dressing depth, the Rockwell hardness of the workpiece, the radial grinding wheel wear per dress, and the wheel life on the De.op value were investigated. Moreover, the impacts of the cost components such as the machine tool hourly rate and the grinding wheel cost on the De.op value were given. Based on that, a mathematical model was proposed to determine the De.op value. The predicted De.op value was also verified by an experiment. The obtained result shows that the difference between the experimental De.op value and the predicted De.op value is within 1.7%, indicating that the mathematical model proposed in the study is reliable.

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Optimization of Grinding Parameters for Minimum Grinding Time When Grinding Tablet Punches by CBN Wheel on CNC Milling Machine

Cited by 33 publications

References 13 publications

Application of topsis, mairca and EAMR methods for multi-criteria decision making in cubic boron nitride grinding

Application of topsis, mairca and EAMR methods for multi-criteria decision making in cubic boron nitride grinding

Parametric Optimization for Cutting Forces and Material Removal Rate in the Turning of AISI 5140

Optimization of Replaced Grinding Wheel Diameter for Surface Grinding Based on a Cost Analysis

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