Verification of On-Line Computer Control of EDM by Data Dependent Systems

1987 ◽  
Vol 109 (2) ◽  
pp. 117-121 ◽  
Author(s):  
S. M. Pandit ◽  
T. M. Mueller
Keyword(s):  
Tool Wear ◽  
Metal Removal ◽  
Removal Rate ◽  
Computer Control ◽  
Electro Discharge Machining ◽  
Manual Adjustment ◽  
Machine Manufacturer ◽  
On Line ◽  
Edm Process ◽  
Line Analysis

A new method of computer control of electro-discharge machining based on Data Dependent Systems (DDS) methodology has been recently proposed. The control is based on a parameter which effectively represents the resistance of arc and is isolated by the DDS model from the random current and voltage signals in spite of the large noise. This paper presents an experimental verification to show that this parameter indeed represents the arc resistance which cannot be measured by any other means and that the parameter is quite sensitive to the change from beneficial sparking condition to the harmful arcing condition. Off-line analysis of the EDM process under different conditions is presented with this parameter as the response variable. Development of the control strategy using the results of this analysis is illustrated. Implementation of the strategy by means of a Motorola microcomputer is described. A comparison of metal removal rate (MRR), surface roughness, and tool wear for the computer control and the optimal manual adjustment recommended by the EDM machine manufacturer is presented. It shows that the computer control yields an increase in the MRR of 47 percent and 19 percent, while the ratio of tool wear to MRR reduces by 26 percent and 16 percent, respectively, in finishing and roughing conditions.

scholarly journals Recent Advances and Perceptive Insights into Powder-Mixed Dielectric Fluid of EDM

Micromachines ◽  
2020 ◽  
Vol 11 (8) ◽  
pp. 754 ◽  
Author(s):  
Asarudheen Abdudeen ◽  
Jaber E. Abu Qudeiri ◽  
Ansar Kareem ◽  
Thanveer Ahammed ◽  
Aiman Ziout
Keyword(s):  
Tool Wear ◽  
Metal Removal ◽  
Electrical Discharge Machining ◽  
Removal Rate ◽  
Dielectric Fluid ◽  
Dielectric Fluids ◽  
Advanced Machining ◽  
Low Efficiency ◽  
Edm Process ◽  
Powder Mixed Edm

Electrical discharge machining (EDM) is an advanced machining method which removes metal by a series of recurring electrical discharges between an electrode and a conductive workpiece, submerged in a dielectric fluid. Even though EDM techniques are widely used to cut hard materials, low efficiency and high tool wear remain remarkable challenges in this process. Various studies, such as mixing different powders to dielectric fluids, are progressing to improve their efficiency. This paper reviews advances in the powder-mixed EDM process. Furthermore, studies about various powders used for the process and its comparison are carried out. This review looks at the objectives of achieving a more efficient metal removal rate, reduction in tool wear, and improved surface quality of the powder-mixed EDM process. Moreover, this paper helps researchers select suitable powders which are exhibiting better results and identifying different aspects of powder-mixed dielectric fluid of EDM.

Effect of SiC-Cu Electrode on Material Removal Rate, Tool Wear and Surface Roughness in EDM Process

2020 ◽  
Vol 38 (9A) ◽  
pp. 1406-1413
Author(s):  
Yousif Q. Laibia ◽  
Saad K. Shather
Keyword(s):  
Surface Roughness ◽  
Tool Wear ◽  
Material Removal Rate ◽  
Material Removal ◽  
Electrical Discharge Machining ◽  
Removal Rate ◽  
304 Stainless Steel ◽  
Tool Electrode ◽  
Pulse Time ◽  
Edm Process

Electrical discharge machining (EDM) is one of the most common non-traditional processes for the manufacture of high precision parts and complex shapes. The EDM process depends on the heat energy between the work material and the tool electrode. This study focused on the material removal rate (MRR), the surface roughness, and tool wear in a 304 stainless steel EDM. The composite electrode consisted of copper (Cu) and silicon carbide (SiC). The current effects imposed on the working material, as well as the pulses that change over time during the experiment. When the current used is (8, 5, 3, 2, 1.5) A, the pulse time used is (12, 25) μs and the size of the space used is (1) mm. Optimum surface roughness under a current of 1.5 A and the pulse time of 25 μs with a maximum MRR of 8 A and the pulse duration of 25 μs.

Multiresponse Optimization of Al Alloy-SiC Composite Machining Parameters for Minimum Tool Wear and Maximum Metal Removal Rate

2013 ◽  
Vol 135 (2) ◽  
Author(s):  
Rajesh Kumar Bhushan
Keyword(s):  
Tool Wear ◽  
Metal Removal ◽  
Removal Rate ◽  
Cutting Speed ◽  
Depth Of Cut ◽  
Al Alloy ◽  
Machining Parameters ◽  
Metal Removal Rate ◽  
Nose Radius ◽  
Multiresponse Optimization

Optimization in turning means determination of the optimal set of the machining parameters to satisfy the objectives within the operational constraints. These objectives may be the minimum tool wear, the maximum metal removal rate (MRR), or any weighted combination of both. The main machining parameters which are considered as variables of the optimization are the cutting speed, feed rate, depth of cut, and nose radius. The optimum set of these four input parameters is determined for a particular job-tool combination of 7075Al alloy-15 wt. % SiC (20–40 μm) composite and tungsten carbide tool during a single-pass turning which minimizes the tool wear and maximizes the metal removal rate. The regression models, developed for the minimum tool wear and the maximum MRR were used for finding the multiresponse optimization solutions. To obtain a trade-off between the tool wear and MRR the, a method for simultaneous optimization of the multiple responses based on an overall desirability function was used. The research deals with the optimization of multiple surface roughness parameters along with MRR in search of an optimal parametric combination (favorable process environment) capable of producing desired surface quality of the turned product in a relatively lesser time (enhancement in productivity). The multi-objective optimization resulted in a cutting speed of 210 m/min, a feed of 0.16 mm/rev, a depth of cut of 0.42 mm, and a nose radius of 0.40 mm. These machining conditions are expected to respond with the minimum tool wear and maximum the MRR, which correspond to a satisfactory overall desirability.

scholarly journals Multi response Particle Swarm Optimization of Wire Electro Discharge Machining parameters of Nitinol alloys

2020 ◽  
Author(s):  
Mohammed Yunus ◽  
Mohammad S. Alsoufi
Keyword(s):  
Particle Swarm Optimization ◽  
Metal Removal ◽  
Removal Rate ◽  
Particle Swarm ◽  
Optimization Method ◽  
Machining Parameters ◽  
Swarm Optimization ◽  
Electro Discharge Machining ◽  
Process Factors ◽  
Wedm Process

Abstract The conventional process of Machining of Nitinol alloy leads to extensive wear on the tool and deprived surface quality. Wire electro discharge machining (WEDM) is widely accepted for machining this alloy involving various input factors, namely, P, (pulse-on-duration), Q, (pulse-off-duration), C, (maximum-current), and V, (voltage). The factor’s effect on MRR (metal removal rate) and SR (surface roughness) responses and multi-response optimization of the WEDM process by employing PSO (particle swarm optimization) method are studied. The relationship model between factors and response characteristics were generated by ANOVA and optimized by response surface methodology has shown more significant factors (A and C). Though the effect of WEDM process factors on SR and MRR are contradictory when studied individually. MRPSO method was employed to get the best optimum condition for minimizing SR and maximizing MRR. MRPSO results improved the responses for vast combination of optimal setting of factors to meet the product requirements.

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.

EDM Process Parameters Optimization for Al-TiO2 Nano Composite

2015 ◽  
Vol 2 (2) ◽  
pp. 17-30 ◽  
Author(s):  
Arvind Kumar Dixit ◽  
Richa Awasthi
Keyword(s):  
Discharge Current ◽  
Titanium Aluminide ◽  
Metal Removal ◽  
Removal Rate ◽  
Stir Casting ◽  
Parameters Optimization ◽  
Parameter Design ◽  
Nano Composite ◽  
Pulse On Time ◽  
Edm Process

Titanium aluminide reinforced aluminium based metal matrix nano composite was prepared by stir casting route. Experiments were conducted with Cu electrode using L9 orthogonal array based on the Taguchi method. Discharge current (Lv), Pulse on time (Ton) and Flushing pressure (FP) are selected to calculate Metal removal rate (MRR), Tool wear rate (TWR) and Surface roughness (SR) based on Taguchi's parameter design. Moreover, the signal-to-noise ratios associated with the observed values in the experiments were determined using MINITAB software for MRR, TWR and SR. PCR – TOPSIS method is used to optimize Taguchi's multi response. Optimum parameter setting is found at Discharge current (Lv) 10 A, Pulse on time (Ton) 150 µs and Flushing pressure (FP) 1 kg/cm2.

scholarly journals An overview of conventional and non-conventional techniques for machining of titanium alloys

2020 ◽  
Vol 7 ◽  
pp. 34 ◽  
Author(s):  
Samuel Ranti Oke ◽  
Gabriel Seun Ogunwande ◽  
Moshood Onifade ◽  
Emmanuel Aikulola ◽  
Esther Dolapo Adewale ◽  
...  
Keyword(s):  
Surface Roughness ◽  
Wear Rate ◽  
Tool Wear ◽  
Titanium Alloys ◽  
Metal Removal ◽  
Removal Rate ◽  
High Volume ◽  
Future Research ◽  
Tool Wear Rate ◽  
The Common

Machining is one of the major contributors to the high cost of titanium-based components. This is as a result of severe tool wear and high volume of waste generated from the workpiece. Research efforts seeking to reduce the cost of titanium alloys have explored the possibility of either eliminating machining as a processing step or optimising parameters for machining titanium alloys. Since the former is still at the infant stage, this article provides a review on the common machining techniques that were used for processing titanium-based components. These techniques are classified into two major categories based on the type of contact between the titanium workpiece and the tool. The two categories were dubbed conventional and non-conventional machining techniques. Most of the parameters that are associated with these techniques and their corresponding machinability indicators were presented. The common machinability indicators that are covered in this review include surface roughness, cutting forces, tool wear rate, chip formation and material removal rate. However, surface roughness, tool wear rate and metal removal rate were emphasised. The critical or optimum combination of parameters for achieving improved machinability was also highlighted. Some recommendations on future research directions are made.

Magnetic Field Assisted Electric Discharge Machining of Cryo-Treated Monel 400 Alloy

2015 ◽  
Vol 787 ◽  
pp. 371-375
Author(s):  
Rahul R. Jadhav ◽  
Vijaykumar S. Jatti ◽  
T.P. Singh
Keyword(s):  
Magnetic Field ◽  
External Magnetic Field ◽  
Tool Wear ◽  
Electrical Discharge Machining ◽  
Removal Rate ◽  
Cryogenic Treatment ◽  
Engineering Properties ◽  
Work Piece ◽  
Unconventional Machining ◽  
Edm Process

Monel alloys are pioneering materials which have exceptional engineering properties such as corrosion resistance, high toughness and show good response to cryogenic treatment. It finds uses in ship building, nuclear aerospace, missile and valve industries. These materials shows strain hardening effect which results in tool wear and in some cases tool breakage when machined by conventional methodshence, unconventional machining such as electrical discharge machining (EDM)discoverspurpose for machining of such materials. Researchers have recognized relation between electrical input process parameters of EDM process and output parameters of EDM process. But researchers have not investigated the influence of external magnetic field and cryo-treatment of work piece on EDM performance measures namely material removal rate (MRR) and tool wear rate (TWR). In vision of this the objective of present work was to study the effect of gap current, external magnetic field and cryogenic treatment of work part on MRR and TWR. Experiments were carried out by creating a 3 mm square hole on Monel400 alloys. Based on experimental results it was found that as gap current increases the MRR and TWR increases for untreated work part. For treated work part MRR increases and TWR decreases with increasein gap current. MRR and TWR increases with constant gap current for untreated work part, as magnetic field increases. For treated work part MRR increases and TWR decreases with increase in magnetic field at constant gap current.

Multi Response Optimization by Using the Hybrid Technique in Electro Discharge Machining of AISI 304

2016 ◽  
Vol 26 ◽  
pp. 68-75 ◽  
Author(s):  
Munmun Bhaumik ◽  
Kali Pada Maity
Keyword(s):  
Wear Rate ◽  
Tool Wear ◽  
Material Removal Rate ◽  
Material Removal ◽  
Removal Rate ◽  
Tool Wear Rate ◽  
Aisi 304 ◽  
Relational Analysis ◽  
Electro Discharge Machining ◽  
Grey Relational

Electro discharge machining (EDM) is most popular non-conventional electro-thermal machining process where electrical energy is used to generate a spark and thermal energy used to remove material from the workpiece. The primary goal of EDM is getting more material removal rate (MRR) with lower tool wear rate (TWR). For this investigation, machining parameters like peak current, pulse on time, gap voltage and duty cycle are considered as process parameter, and material removal rate (MRR) and tool wear rate (TWR) are considered as response. AISI 304 stainless steel and tungsten carbide are used as work material and tool material respectively. Taguchi L27 orthogonal array has been applied for designing the experiment. A hybrid optimization technique like desirability in combination with grey relational analysis (GRA) has been performed to get the optimum level of the control parameter for getting higher MRR and lower TWR. Analysis of variance (ANOVA) is performed for the statistical analysis. These results show that peak current is the most significant parameter for MRR and TWR. The optimal parameter setting for maximum MRR and minimum TWR has obtained by desirability coupled with Grey relational analysis.

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