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.

scholarly journals Optimization Of Machining Process Parameters In Turning And Drilling By using Design Of Experiments With Aluminum 6061-O Alloy And Austenitic Stainless Steel

2019 ◽  
Vol 8 (11) ◽  
pp. 625-633
Keyword(s):  
Surface Roughness ◽  
Stainless Steel ◽  
Design Of Experiments ◽  
Process Parameters ◽  
Removal Rate ◽  
Cutting Speed ◽  
Machining Process ◽  
Depth Of Cut ◽  
Drilling Operation ◽  
Input Parameters

Optimization is required everywhere particularly in the industrial sector. As a part of that machining emphasized in this paper to optimize the parameters involved in the turning and drilling operation on CNC machines using the Aluminum and Stainless steel alloys. The task is initiated with design of experiments and hence the cost of operation is also reduced. During the experimental process the input parameters involved for turning were considered as cutting speed, feed and depth of cut. And for the drilling operation the input process parameters considered were speed of drill, feed. The output parameters emphasized were surface roughness and dimensional accuracy. By the investigation using the experiments, it in turn leads to an optimized environment for the operation that was carried out. Taguchi technique is a widely used and efficient technique for correlating the process parameters for an efficient and effective operation. Then the process L9 and L16 orthogonal arrays were chosen and signal to noise ratios were computed. At the end the input parameters speed, feed, depth of cut, depth of drill and outcome parameters surface roughness, material removal rate and time of operation were optimized.

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 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.

scholarly journals Development of surface roughness model in turning process of 3X13 steel using TiAlN coated carbide insert

2021 ◽  
pp. 113-124
Author(s):  
Nhu-Tung Nguyen ◽  
Do Duc Trung
Keyword(s):  
Surface Roughness ◽  
Machining Process ◽  
Quadratic Model ◽  
Depth Of Cut ◽  
Turning Process ◽  
Nose Radius ◽  
Machining Processes ◽  
Roughness Model ◽  
Input Parameters ◽  
Coated Carbide

Surface roughness that is one of the most important parameters is used to evaluate the quality of a machining process. Improving the accuracy of the surface roughness model will contribute to ensure an accurate assessment of the machining quality. This study aims to improve the accuracy of the surface roughness model in a machnining process. In this study, Johnson and Box-Cox transformations were successfully applied to improve the accuracy of surface roughness model when turning 3X13 steel using TiAlN insert. Four input parameters that were used in experimental process were cutting velocity, feed rate, depth of cut, and insert-nose radius. The experimental matrix was designed using Central Composite Design (CCD) with 29 experiments. By analyzing the experimental data, the influence of input parameters on surface roughness was investigated. A quadratic model was built to explain the relationship of surface roughness and the input parameters. Box-Cox and Johnson transformations were applied to develop two new models of surface roughness. The accuracy of three surface roughness models showed that the surface roughness model using Johnson transformation had the highest accuracy. The second one model of surface roughness is the model using Box-Cox transformation. And surface roughness model without transformation had the smallest accuracy. Using the Johnson transformation, the determination coefficient of surface roughness model increased from 80.43 % to 84.09 %, and mean absolute error reduced from 19.94 % to 16.64 %. Johnson and Box-Cox transformations could be applied to improve the acuaracy of the surface roughness prediction in turning process of 3X13 steel and can be extended with other materials and other machining processes

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.

Effects of Process Parameters on Material Removal Rate and Surface Roughness in Wedm of H-13 Die Tool Steel

2018 ◽  
Vol 28 ◽  
pp. 55-66 ◽  
Author(s):  
Kuldeep Singh ◽  
Khushdeep Goyal ◽  
Deepak Kumar Goyal
Keyword(s):  
Surface Roughness ◽  
Taguchi Method ◽  
Tool Steel ◽  
Process Parameters ◽  
Material Removal Rate ◽  
Material Removal ◽  
Removal Rate ◽  
Machining Process ◽  
Pulse On Time ◽  
Pulse Off Time

In research work variation of cutting performance with pulse on time, pulse off time, wire type, and peak current were experimentally investigated in wire electric discharge machining (WEDM) process. Soft brass wire and zinc coated diffused wire with 0.25 mm diameter and Die tool steel H-13 with 155 mm× 70 mm×14 mm dimensions were used as tool and work materials in the experiments. Surface roughness and material removal rate (MRR) were considered as performance output in this study. Taguchi method was used for designing the experiments and optimal combination of WEDM parameters for proper machining of Die tool steel (H-13) to achieve better surface finish and material removal rate. In addition the most significant cutting parameter is determined by using analysis of variance (ANOVA). Keywords Machining, Process Parameters, Material removal rate, Surface roughness, Taguchi method

Machining Apprenticeship Based on Experimental Training Practice

2011 ◽  
Vol 692 ◽  
pp. 83-92
Author(s):  
Pedro Jose Arrazola ◽  
A. Villar ◽  
R. Fernández ◽  
J. Aperribay
Keyword(s):  
Surface Roughness ◽  
Power Consumption ◽  
Feed Rate ◽  
Cutting Forces ◽  
Theoretical Calculations ◽  
Cutting Speed ◽  
Machining Process ◽  
Depth Of Cut ◽  
Practical Training ◽  
Input Parameters

This article describes a practical machining training aiming that the students acquire the theoretical-practical knowledge of chip formation process. The training takes place after theoretical lessons of machining processes. Thus, this practice allows strengthening the knowledge gained during the lessons. The practical training lasts for five hours, and the student assisted by the teacher analyses the influence of some machining entry parameters (cutting speed, feed rate...) on exit parameters like: (I) cutting forces and power consumption, (II) surface roughness, and (III) chip typology. The practical session is carried out on an experimental set-up (Lathe CNC Danobar 65) equipped with sensors and devices to measure forces (sensor Kistler 9121) and power consumption. In addition, a portable rugosimeter (Hommelwerke) is employed to perform surface roughness measurements. No especial devices are needed for the chip typology analysis. In the case of cutting forces and power consumption, the following input parameters influences are analysed: feed rate, depth of cut and cutting speed. In the case of surface roughness analysis, the following input parameters influences are analysed: feed rate and nose radius of the cutting insert. Finally, regarding chip typology feed rate and depth of cut are examined. The experimental results are compared with model predictions (theoretical calculations) for the three issues studied. The students have to compare both results: theoretical an empirical and they need to explain the reasons when discrepancies appear. Results obtained during the last years demonstrate the student acquires better knowledge of the machining process, and at the same time realises of the process complexity.

Experimental investigation of machinability characteristics in Al-TiB2 metal matrix composite (MMC) based on the Taguchi method with fuzzy logics

2016 ◽  
Vol 12 (1) ◽  
pp. 177-193 ◽  
Author(s):  
M.P. Jenarthanan ◽  
A. Ram Prakash ◽  
R. Jeyapaul
Keyword(s):  
Mathematical Model ◽  
Surface Roughness ◽  
Taguchi Method ◽  
Metal Matrix ◽  
Removal Rate ◽  
Cutting Speed ◽  
Depth Of Cut ◽  
Fuzzy Logics ◽  
Content Type ◽  
Five Factors

Purpose – The purpose of this paper is to develop a mathematical model for metal removal rate and surface roughness through Taguchi method and analyse the influence of the individual input machining parameters (cutting speed, feed rate, helix angle, depth of cut and wt% on the responses in milling of aluminium-titanium diboride metal matrix composite (MMC) with solid carbide end mill cutter coated with nano-crystals. Design/methodology/approach – Taguchi OA is used to optimise the material removal rate (MRR) and Surface Roughness by developing a mathematical model. End Milling is used to create slots by combining various input parameters. Five factors, three-level Taguchi method is employed to carry out the experimental investigation. Fuzzy logic is used to find the optimal cutting factors for surface roughness (Ra) and MRR. The factors considered were weight percentage of TiB2, cutting speed, depth of cut and feed rate. The plan for the experiments and analysis was based on the Taguchi L27 orthogonal array with five factors and three levels. MINITAB 17 software is used for regression, S/N ratio and analysis of variance. MATLAB 7.10.0 is used to perform the fuzzy logics systems. Findings – Using fuzzy logics, multi-response performance index is generated, with which the authors can identify the correct combination of input parameters to get higher MRR and lower surface roughness value with the chosen range with 95 per cent confidence intervals. Using such a model, remarkable savings in time and cost can be obtained. Originality/value – Machinability characteristics in Al-TiB2 MMC based on the Taguchi method with fuzzy logic has not been analysed previously.

scholarly journals On Coolant Flow Rate-Cutting Speed Trade-Off for Sustainability in Cryogenic Milling of Ti–6Al–4V

Materials ◽  
2021 ◽  
Vol 14 (12) ◽  
pp. 3429
Author(s):  
Asif Iqbal ◽  
Guolong Zhao ◽  
Hazwani Suhaimi ◽  
Malik Muhammad Nauman ◽  
Ning He ◽  
...  
Keyword(s):  
Surface Roughness ◽  
Mass Flow ◽  
Flow Rate ◽  
Heat Dissipation ◽  
Removal Rate ◽  
Cutting Speed ◽  
Machining Process ◽  
Carbon Dioxide Gas ◽  
Mass Flow Rates ◽  
Tool Damage

Application of cryogenic fluids for efficient heat dissipation is gradually becoming part and parcel of titanium machining. Not much research is done to establish the minimum quantity of a cryogenic fluid required to sustain a machining process with respect to a given material removal rate. This article presents an experimental investigation for quantifying the sustainability of milling a commonly used titanium alloy (Ti–6Al–4V) by varying mass flow rates of two kinds of cryogenic coolants at various levels of cutting speed. The three cooling options tested are dry (no coolant), evaporative cryogenic coolant (liquid nitrogen), and throttle cryogenic coolant (compressed carbon dioxide gas). The milling sustainability is quantified in terms of the following metrics: tool damage, fluid cost, specific cutting energy, work surface roughness, and productivity. Dry milling carried out the at the highest level of cutting speed yielded the worst results regarding tool damage and surface roughness. Likewise, the evaporative coolant applied with the highest flow rate and at the lowest cutting speed was the worst performer with respect to energy consumption. From a holistic perspective, the throttle cryogenic coolant applied at the highest levels of mass flow rate and cutting speed stood out to be the most sustainable option.

Investigation of Surface Roughness in Hardened GCr15 Steel Turning with Mixed Ceramic Insert

2012 ◽  
Vol 602-604 ◽  
pp. 1600-1603
Author(s):  
Bo Di Cui
Keyword(s):  
Surface Roughness ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Machining Process ◽  
Dominant Factor ◽  
Nose Radius ◽  
Gcr15 Steel ◽  
Finish Hard Turning ◽  
Artificial Neural Network Ann ◽  
Mixed Ceramic

An experimental investigation was conducted to determine the effects of cutting conditions on surface roughness in finish hard turning of GCr15 steel with mixed ceramic inserts based on design of experiment. The influence of cutting speed, feed rate and nose radius on surface roughness was assessed using analysis of variance (ANOVA). The result indicated that the feed is the dominant factor on surface roughness followed by nose radius. Due to the complexity of machining process, artificial neural network (ANN) was employed to develop the predictive model of surface roughness. Simulations were done to describe the relationship between surface roughness and cutting parameters based on the proposed model.

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