scholarly journals Multi-objective optimization of SKD11 Steel Milling Process by Reference Ideal Method

2021 ◽  
Vol 15 ◽  
pp. 1-16
Author(s):  
Do Duc Trung
Keyword(s):  
Surface Roughness ◽  
Cutting Force ◽  
Cutting Speed ◽  
Milling Process ◽  
Multi Objective Optimization ◽  
Small Surface ◽  
Multi Objective ◽  
Input Parameters ◽  
Machining Productivity ◽  
Ideal Method

For all machining cutting methods, surface roughness is a parameter that greatly affects the working ability and life of machine elements. Cutting force is a parameter that not only affects the quality of the machining surface but also affects the durability of cutter and the level of energy consumed during machining. Besides, material removal rate (MRR) is a parameter that reflects machining productivity. Workpiece surface machining with small surface roughness, small cutting force and large MRR is desirable of most machining methods. This article presents a study of multi-objective optimization of milling process using a face milling cutter. The experimental material used in this study is SKD11 steel. Taguchi method has been applied to design an orthogonal experimental matrix with 27 experiments (L27). In which, five parameters have been selected as the input parameters of the experimental process including insert material, tool nose radius, cutting speed, feed rate and cutting depth. Reference Ideal Method (RIM) is applied to determine the value of input parameters to ensure minimum surface roughness, minimum cutting force and maximum MRR. Influence of the input parameters on output parameters is also discussed in this study.

scholarly journals Study on multi-objective optimization of X12M steel milling process by reference ideal method

2021 ◽  
pp. 89-104
Author(s):  
Khanh Nguyen Lam
Keyword(s):  
Surface Roughness ◽  
Cutting Force ◽  
Milling Process ◽  
Face Milling ◽  
Multi Objective Optimization ◽  
Milling Cutter ◽  
Multi Objective ◽  
Input Parameters ◽  
Machining Productivity ◽  
Ideal Method

For all machining cutting methods, surface roughness is a parameter that greatly affects the working ability and life of machine elements. Cutting force is a parameter that not only affects the quality of the machining surface but also affects the durability of cutter and the level of energy consumed during machining. Besides, material removal rate (MRR) is a parameter that reflects machining productivity. Workpiece surface machining with small surface roughness, small cutting force and large MRR is desirable of most machining methods. Milling is a popular machining method in the machine building industry. This is considered to be one of the most productive machining methods, capable of machining many different types of surfaces. With the development of the cutting tool and machine tool manufacturing industries, this method is increasingly guaranteed with high precision, sometimes used as the final finishing method. Milling using a face milling cutter is more productive than using a cylindrical cutter because there are multiple cutter s involved at the same time. This article presents a study of multi-objective optimization of milling process using a face milling cutter. The experimental material used in this study is X12M steel. Taguchi method has been applied to design an orthogonal experimental matrix with 27 experiments (L27). In which, five parameters have been selected as the input parameters of the experimental process including insert material, tool nose radius, cutting speed, feed rate and cutting depth. The Reference Ideal Method (RIM) is applied to determine the value of input parameters to ensure minimum surface roughness, minimum cutting force and maximum MRR. Influence of the input parameters on output parameters is also discussed in this study

scholarly journals Combining Taguchi method and DEAR method for multi-objective optimization of grinding process

2021 ◽  
Vol 309 ◽  
pp. 01220
Author(s):  
Do Duc Trung ◽  
Nguyen Huu Quang ◽  
Dang Quoc Cuong ◽  
Nguyen Hong Linh ◽  
Nguyen Van. Tuan ◽  
...  
Keyword(s):  
Surface Roughness ◽  
Taguchi Method ◽  
Removal Rate ◽  
Cutting Speed ◽  
Grinding Process ◽  
Multi Objective Optimization ◽  
Pareto Chart ◽  
Multi Objective ◽  
Input Parameters ◽  
Experimental Process

In this paper, a study on multi-objective optimization of the cylindrical grinding process is presented. The experimental material used in this study is X12M steel. The two output parameters of the grinding process considered in this study are surface roughness and material removal rate (MRR). The cutting mode parameters including cutting speed, feed rate, and cutting depth have been selected as input parameters of the experimental process. Experimental matrix by Taguchi method has been used to design a matrix with 27 experiments. Analysis of experimental results by Pareto chart has determined the effect of input parameters on output parameters. The Data Envelopment Analysis-based Ranking (DEAR) method has been applied to determine the values of input parameters to simultaneously ensure the two criteria of minimum surface roughness and maximum MRR. Finally, the development direction for further studies has also been recommended in this study.

scholarly journals Combination of taguchi method and moora method for multi-objective optimization of SCM400 steel milling process

2021 ◽  
Vol 309 ◽  
pp. 01092
Author(s):  
Do Duc Trung ◽  
Nguyen Huu Quang ◽  
Pham Duc Lam ◽  
Nguyen Hong Linh ◽  
Le Quang Lam ◽  
...  
Keyword(s):  
Taguchi Method ◽  
Removal Rate ◽  
Milling Process ◽  
Cnc Milling ◽  
Multi Objective Optimization ◽  
Pareto Chart ◽  
Multi Objective ◽  
Depth Analysis ◽  
Input Parameters ◽  
Moora Method

Abstract. In this article, a study on multi-objective optimization of the milling process is presented. CNC milling machine, cutting tool as TiAlN, experimental material as SCM400 steel and coolant as Caltex Aquatex 3180 oil have been used in the experiment. The objective of this study is to simultaneously ensure the minimum surface roughness and the maximum material removal rate (MRR). Taguchi method has been applied to design an experimental matrix with five input parameters, including coolant flow, coolant pressure, cutting velocity, feed rate, and cutting depth. Analysis of experimental results by Pareto chart has determined the effect of input parameters on output parameters. Moora method has been applied to determine the values of input parameters to simultaneously ensure the two criteria as mentioned above. Finally, the direction for further research has also been recommended in this study

scholarly journals Optimization Study on Turning Process by Using Taguchi-copras Method

2021 ◽  
Vol 309 ◽  
pp. 01010
Author(s):  
Do Duc Trung ◽  
Nguyen Huu Quang ◽  
Tran Quoc Hoang ◽  
Cao The Anh ◽  
Nguyen Hong Linh ◽  
...  
Keyword(s):  
Surface Roughness ◽  
Removal Rate ◽  
Multi Objective Optimization ◽  
Turning Process ◽  
Nose Radius ◽  
Multi Objective ◽  
Optimization Study ◽  
Input Parameters ◽  
Cutting Velocity ◽  
Copras Method

In this article, a multi-objective optimization of turning process study is presented. Two output parameters of the turning process taken into consideration are surface roughness and Material Removal Rate (MRR). Taguchi method has been applied to design the experimental matrix with four input parameters including nose radius, cutting velocity, feed rate and cutting depth. Copras method has been employed to solve the multi-objective optimization problem. Finally, the optimal values of the input parameters have been determined to simultaneously ensure the two criteria of the minimum surface roughness and the maximum MRR.

High-pressure jet-assisted turning of AISI 304: Experimental and multi-objective optimization approach

2017 ◽  
Vol 232 (6) ◽  
pp. 734-750 ◽  
Author(s):  
Sayed E Mirmohammadsadeghi ◽  
H Amirabadi
Keyword(s):  
Genetic Algorithm ◽  
Surface Roughness ◽  
High Pressure ◽  
Cutting Force ◽  
Process Parameters ◽  
Optimization Approach ◽  
Multi Objective Optimization ◽  
Aisi 304 ◽  
Multi Objective ◽  
304 Austenitic Stainless Steel

High-pressure jet-assisted turning is an effective method to decrease the cutting force and surface roughness. Efficiency of this process is related to application of proper jet pressure proportional to other process parameters. In this research, experiments were conducted for high-pressure jet-assisted turning in finishing AISI 304 austenitic stainless steel, based on response surface method. Against the expectations, the maximum jet pressure could not lead to the most efficient results, which means that applying high-pressure jet-assisted turning without considering optimal process parameters will diminish the improving effects of high-pressure jet assistance. For this purpose, two artificial neural networks were trained by genetic algorithm to model the surface roughness and cutting force based on the process parameters. Ultimately, nondominated sorting genetic algorithm was implemented for multi-objective optimization of process. Results demonstrated that the employed method provides an effective approach that indicates optimized range of process parameters.

scholarly journals Parameter Selection to Ensure Multi-Criteria Optimization of the Taguchi Method Combined with the Data Envelopment Analysis-based Ranking Method when Milling SCM440 Steel

2021 ◽  
Vol 11 (5) ◽  
pp. 7551-7557
Author(s):  
N. V. Cuong ◽  
N. L. Khanh
Keyword(s):  
Surface Roughness ◽  
Data Envelopment Analysis ◽  
Taguchi Method ◽  
Removal Rate ◽  
Cutting Speed ◽  
Machining Process ◽  
Data Envelopment ◽  
Nose Radius ◽  
Small Surface ◽  
Input Parameters

SCM440 steel is a commonly used material for making plastic injection molds and components such as gears, transmission shafts, rolling pins, etc. Surface roughness has a direct influence on the workability and durability of the parts and/or components, while the Material Removal Rate (MRR) is a parameter that is used to evaluate the productivity of the machining process. Furnished products with small surface roughness and large MRR is the desired result by all milling processes. In this paper, the determination of the values of input parameters is studied in order to ensure that during the process of milling SCM440 steel, it will have the smallest surface roughness and the largest MRR. There are five parameters that are required to be determined, namely the cutting insert material, the tool nose radius, the cutting speed, the feed rate, and the cutting depth. The Taguchi method was applied to design the experimental matrix with a total of 27 experiments. Result analysis determined the influence of the input parameters on surface roughness and MRR. The Data Envelopment Analysis-based Ranking (DEAR) method was applied to determine the optimal value of the input parameters, which were used to conduct the milling experiments to re-evaluate their suitability.

An experimental investigation of micro-milling brass considering run out by carbide micro-end mills

2017 ◽  
Vol 232 (20) ◽  
pp. 3675-3684 ◽  
Author(s):  
Xiubing Jing ◽  
Yanling Tian ◽  
Yanjie Yuan
Keyword(s):  
Surface Roughness ◽  
Cutting Force ◽  
Cutting Speed ◽  
Chip Thickness ◽  
Cutting Parameters ◽  
Milling Process ◽  
Micro Milling ◽  
Method Of Calculation ◽  
Micro End Mill ◽  
End Mills

This paper presented the effect of run out on the experimental characteristic of micro-milling brass using carbide micro-end mills. A method of calculation and measurement for the run out of tool-holder-spindle assembly in micro-end mill was developed. A series of micro-milling process experiments were carried out under varying cutting parameters. The effect of run out on cutting forces, effect of cutting parameters on surface roughness, and size effect were analyzed. It was seen that the cutting force signature was seriously affected by run out in the micro-milling process. When the feed per tooth is less than the run out, the cutting force signals showed that only one cutter flute engaged in cutting process due to the effect of run out. It was also seen that the cutting force signature showed erratic variations due to the effect of tool–workpiece and the run out of tool tip at higher spindle speed. Surface roughness was affected by both cutting speed and feed per tooth. For lower cutting speed, there was increase in the surface roughness with the decrease in the cutting speed due to the effect of built-up edge. For higher cutting speed, there was increase in the surface roughness with the increase in the cutting speed due to dominance of the shearing effects. When the feed per tooth was less than the minimum chip thickness, due to the indentation and ploughing-dominated process, nonlinear increase of specific shear energy can be obtained. At lower feed per tooth, the specific energy increases with increased cutting speed. These results are used to provide strategies to optimize cutting parameters and achieve better surface quality in micro-milling brass process.

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