Multi-objective optimization of material removal rate and surface roughness in wire electrical discharge turning

2012 ◽  
Vol 67 (9-12) ◽  
pp. 2021-2032 ◽  
Author(s):  
S. Aravind Krishnan ◽  
G. L. Samuel
Keyword(s):  
Surface Roughness ◽  
Material Removal Rate ◽  
Electrical Discharge ◽  
Material Removal ◽  
Removal Rate ◽  
Multi Objective Optimization ◽  
Multi Objective

scholarly journals Improving the process performance of magnetic abrasive finishing of SS304 material using multi-objective artificial bee colony algorithm

2020 ◽  
Vol 41 (1) ◽  
pp. 34-49
Author(s):  
Sandip B. Gunjal ◽  
Padmakar J. Pawar
Keyword(s):  
Surface Roughness ◽  
Material Removal Rate ◽  
Material Removal ◽  
Artificial Bee Colony Algorithm ◽  
Artificial Bee Colony ◽  
Removal Rate ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Bee Colony ◽  
Abrasive Finishing

Magnetic abrasive finishing is a super finishing process in which the magnetic field is applied in the finishing area and the material is removed from the workpiece by magnetic abrasive particles in the form of microchips. The performance of this process is decided by its two important quality characteristics, material removal rate and surface roughness. Significant process variables affecting these two characteristics are rotational speed of tool, working gap, weight of abrasive, and feed rate. However, material removal rate and surface roughness being conflicting in nature, a compromise has to be made between these two objective to improve the overall performance of the process. Hence, a multi-objective optimization using an artificial bee colony algorithm coupled with response surface methodology for mathematical modeling is attempted in this work. The set of Pareto-optimal solutions obtained by multi-objective optimization offers a ready reference to process planners to decide appropriate process parameters for a particular scenario.

scholarly journals COMBINATION OF TAGUCHI METHOD, MOORA AND COPRAS TECHNIQUES IN MULTI-OBJECTIVE OPTIMIZATION OF SURFACE GRINDING PROCESS

2020 ◽  
pp. 1-9
Author(s):  
Do Duc Trung
Keyword(s):  
Surface Roughness ◽  
Material Removal Rate ◽  
Material Removal ◽  
Optimization Problem ◽  
Removal Rate ◽  
Optimization Techniques ◽  
Surface Grinding ◽  
Grinding Process ◽  
Multi Objective Optimization ◽  
Multi Objective

This study presentes a combination method of several optimization techniques and Taguchi method to solve the multi-objective optimization problem for surface grinding process of SKD11 steel. The optimization techniques that were used in this study were Multi-Objective Optimization on basis of Ratio Analysis (MOORA) and Complex Proportional Assessment (COPRAS). In surface grinding process, two parameters that were chosen as the evaluation creterias were surface roughness (Ra) and material removal rate (MRR). The orthogonal Taguchi L16 matrix was chosen to design the experimental matrix with two input parameters namely workpiece velocity and depth of cut.  The two optimization techniques that mentioned above were applied to solve the multi-objective optimization problem in the grinding process. Using two above techniques, the optimized results of the cutting parameters were the same. The optimal workpiece velocity and cutting depth were 20 m/min and 0.02 mm. Corresponding to these optimal values of the workpiece velocity and cutting depth, the surface roughness and material removal rate were 1.16 µm and 86.67 mm3/s. These proposed techniques and method can be used to improve the quality and effectiveness of grinding processes by reducing the surface roughness and increasing the material removal rate.

scholarly journals Investigation an assisting electrode powder mixed electrical discharge machining of nonconductive ceramic

2021 ◽  
Author(s):  
Dragan Rodic ◽  
Marin Gostimirovic ◽  
Milenko Sekulic ◽  
Borislav Savkovic ◽  
Branko Strbac
Keyword(s):  
Surface Roughness ◽  
Tool Wear ◽  
Material Removal Rate ◽  
Electrical Discharge ◽  
Material Removal ◽  
Metal Removal ◽  
Electrical Discharge Machining ◽  
Removal Rate ◽  
Positive Effects ◽  
Assisting Electrode

Abstract It is well known that electrical discharge machining can be used in the processing of nonconductive materials. In order to improve the efficiency of machining modern engineering materials, existing electrical discharge machines are constantly being researched and improved or developed. The current machining of non-conductive materials is limited due to the relatively low material removal rate and high surface roughness. A possible technological improvement of electrical discharge machining can be achieved by innovations of existing processes. In this paper, a new approach for machining zirconium oxide is presented. It combines electrical discharge machining with assisting electrode and powder-mixed dielectric. The assisting electrode is used to enable electrical discharge machining of nonconductive material, while the powder-mixed dielectric is used to increase the material removal rate, reduce surface roughness, and decrease relative tool wear. The response surface method was used to generate classical mathematical models, analyzing the output performances of surface roughness, material removal rate and relative tool wear. Verification of the obtained models was performed based on a set of new experimental data. By combining these latest techniques, positive effects on machining performances are obtained. It was found that the surface roughness was reduced by 18%, the metal removal rate was increased by about 12% and the relative tool wear was reduced by up to 6% compared to electrical discharge machining with supported electrode without powder.

Sign in / Sign up

Export Citation Format

Share Document