scholarly journals Experimental Analysis on the Influence and Optimization of μ-RUM Parameters in Machining Alumina Bioceramic

Materials ◽  
2019 ◽  
Vol 12 (4) ◽  
pp. 616 ◽  
Author(s):  
Basem M. A. Abdo ◽  
Saqib Anwar ◽  
Abdulaziz M. El-Tamimi ◽  
Emad Abouel Nasr
Keyword(s):  
Surface Roughness ◽  
Surface Morphology ◽  
Vibration Frequency ◽  
High Hardness ◽  
Dimensional Accuracy ◽  
Depth Of Cut ◽  
Multi Objective Optimization ◽  
Edge Chipping ◽  
Multi Objective ◽  
Input Parameters

Fabrication of precise micro-features in bioceramic materials is still a challenging task. This is because of the inherent properties of bioceramics, such as low fracture toughness, high hardness, and brittleness. This paper places an emphasis on investigating the multi-objective optimization of fabrication of microchannels in alumina (Al2O3) bioceramics by using rotary ultrasonic machining (RUM). The influence of five major input parameters, namely vibration frequency, vibration amplitude, spindle speed, depth of cut, and feed rate on the surface quality, edge chipping, and dimensional accuracy of the milled microchannels was analyzed. Surface morphology and microstructure of the machined microchannels were also evaluated and analyzed. Unlike in previous studies, the effect of vibration frequency on the surface morphology and roughness is discussed in detail. A set of designed experiments based on central composite design (CCD) method was carried out. Main effect plots and surface plots were analyzed to detect the significance of RUM input parameters on the outputs. Later, a multi-objective genetic algorithm (MOGA) was employed to determine the optimal parametric conditions for minimizing the surface roughness, edge chipping, and dimensional errors of the machined microchannels. The optimized values of the surface roughness (Ra and Rt), side edge chipping (SEC), bed edge chipping (BEC), depth error (DE), and width error (WE) achieved through the multi-objective optimization were 0.27 μm, 2.7 μm, 8.7 μm, 8 μm, 5%, and 5.2%, respectively.

Multi Objective Optimization of Cutting Parameters in Machining Cellulose Based Hybrid Composites

2015 ◽  
Vol 761 ◽  
pp. 287-292
Author(s):  
Raja Izamshah ◽  
Zainudin Zuraidah ◽  
Mohd Shahir Kasim ◽  
M. Hadzley ◽  
M. Amran
Keyword(s):  
Surface Roughness ◽  
Feed Rate ◽  
Hybrid Composites ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Multi Objective Optimization ◽  
Machining Performance ◽  
Machined Surface ◽  
Multi Objective ◽  
Optimization Of Cutting Parameters

Cellulose based hybrid composites are gaining popularity in the growing green communities. With extensive studies and increasing applications for future advancement, the need for an accurate and reliable guidance in machining this type of composites has increased enormously. Smooth and defect free machined surface are always the ultimate objectives. The present work deals with the study of machining parameters (i.e. spindle speed, feed rate and depth of cut) and their effects on machining performance (i.e. surface roughness and delamination) to establish an optimized setup of machining parameters in achieving multi objective machining performance. Cellulose based hybrid composites consist of jute (a bast fiber) and glass fiber embedded in polyester resins. Response Surface Methodology (RSM) using Box-Behnken Design (BBD) was chosen as the design of experiment approach for this study. Based on that experimental approach, 17 experimental runs were conducted. Mathematical model for each response was developed based on the experimental data. Adequacy of the models were analyzed statistically using Analysis of Variance (ANOVA) in determining the significant input variables and possible interactions. The multi objective optimization was performed through numerical optimization, and the predicted results were validated. The agreement between the experimental and selected solution was found to be strong, between 95% to 96%, thus validating the solution as the optimal machining condition. The findings suggest that feed rate was the main factor affecting surface roughness and delamination .

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 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.

Multi-objective optimization of dimensional accuracy, surface roughness and hardness of hybrid investment cast components

2017 ◽  
Vol 23 (5) ◽  
pp. 845-857 ◽  
Author(s):  
Parlad Kumar Garg ◽  
Rupinder Singh ◽  
IPS Ahuja
Keyword(s):  
Surface Roughness ◽  
Process Parameters ◽  
Surface Finish ◽  
Dimensional Accuracy ◽  
Multi Objective Optimization ◽  
Content Type ◽  
Multi Objective ◽  
Fused Deposition ◽  
Taguchi Design Of Experiments ◽  
Investment Cast

Purpose The purpose of this paper is to optimize the process parameters to obtain the best dimensional accuracy, surface finish and hardness of the castings produced by using fused deposition modeling (FDM)-based patterns in investment casting (IC). Design/methodology/approach In this paper, hip implants have been prepared by using plastic patterns in IC process. Taguchi design of experiments has been used to study the effect of six different input process parameters on the dimensional deviation, surface roughness and hardness of the implants. Analysis of variance has been used to find the effect of each input factor on the output. Multi-objective optimization has been done to find the combined best values of output. Findings The results proved that the FDM patterns can be used successfully in IC. A wax coating on the FDM patterns improves the surface finish and dimensional accuracy. The improved dimensional accuracy, surface finish and hardness have been achieved simultaneously through multi-objective optimization. Research limitations/implications A thin layer of wax is used on the plastic patterns. The effect of thickness of the layer has not been considered. Further research is needed to study the effect of the thickness of the wax layer. Practical implications The results obtained by the study would be helpful in making decisions regarding machining and/or coating on the parts produced by this process. Originality/value In this paper, multi-objective optimization of dimensional accuracy, surface roughness and hardness of hybrid investment cast components has been performed.

scholarly journals Predictive Modelling and Multi-Objective Optimization of Surface Integrity Parameters in Sustainable Machining Processes of Magnesium Alloy

Materials ◽  
2021 ◽  
Vol 14 (13) ◽  
pp. 3547
Author(s):  
Mohd Danish ◽  
Saeed Rubaiee ◽  
Hassan Ijaz
Keyword(s):  
Surface Roughness ◽  
Magnesium Alloy ◽  
Magnesium Alloys ◽  
Surface Integrity ◽  
Removal Rate ◽  
Cryogenic Cooling ◽  
Depth Of Cut ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Cooling Conditions

Magnesium alloys are widely used in numerous engineering applications owing to their superior structural characteristics. However, the machining of magnesium alloy is challenging because of its poor machinability characteristics. Therefore, this paper investigates the machining of magnesium alloys under different sustainable cooling conditions. The machining was performed by varying cutting velocity, feed rate, and depth of cut under dry and cryogenic cooling conditions. The primary focus of the paper is to develop a predictive model for surface roughness under different machining environments. The models developed were found to be in excellent agreement with experimental results, with only 0.3 to 1.6% error. Multi-objective optimization were also performed so that the best surface finish together with high material removal rate could be achieved. Furthermore, the various parameters of surface integrity (i.e., surface roughness, micro-hardness, micro-structures, crystallite size, and lattice strain) were also investigated.

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

Investigation of material removal rate and surface roughness using multi-objective optimization for micro-milling of inconel 718

2019 ◽  
Vol 71 (6) ◽  
pp. 787-794 ◽  
Author(s):  
Xiaohong Lu ◽  
FuRui Wang ◽  
Liang Xue ◽  
Yixuan Feng ◽  
Steven Y. Liang
Keyword(s):  
Surface Roughness ◽  
Inconel 718 ◽  
Cutting Parameters ◽  
Spindle Speed ◽  
Micro Milling ◽  
Depth Of Cut ◽  
Multi Objective Optimization ◽  
Content Type ◽  
Cutting Parameter ◽  
Multi Objective

Purpose The purpose of this study is to realize the multi-objective optimization for MRR and surface roughness in micro-milling of Inconel 718. Design/methodology/approach Taguchi method has been applied to conduct experiments, and the cutting parameters are spindle speed, feed per tooth and depth of cut. The first-order models used to predict surface roughness and MRR for micro-milling of Inconel 718 have been developed by regression analysis. Genetic algorithm has been utilized to implement multi-objective optimization between surface roughness and MRR for micro-milling of Inconel 718. Findings This paper implemented the multi-objective optimization between surface roughness and MRR for micro-milling of Inconel 718. And some conclusions can be summarized. Depth of cut is the major cutting parameter influencing surface roughness. Feed per tooth is the major cutting parameter influencing MRR. A number of cutting parameters have been obtained along with the set of pareto optimal solu-tions of MRR and surface roughness in micro-milling of Inconel 718. Originality/value There are a lot of cutting parameters affecting surface roughness and MRR in micro-milling, such as tool diameter, depth of cut, feed per tooth, spindle speed and workpiece material, etc. However, to the best our knowledge, there are no published literatures about the multi-objective optimization of surface roughness and MRR in micro-milling of Inconel 718.

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.

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