Enhancing die corner accuracy using path modification strategy in wire electrical discharge machining of Monel 400

2016 ◽  
Vol 232 (2) ◽  
pp. 207-216 ◽  
Author(s):  
G Selvakumar ◽  
KG Thiruppathi Kuttalingam ◽  
M Selvaraj ◽  
J Manohar
Keyword(s):  
Electrical Discharge ◽  
Electrical Discharge Machining ◽  
Machining Process ◽  
Wire Electrical Discharge Machining ◽  
Scanning Electron Micrographs ◽  
Controllable Factors ◽  
Monel 400 ◽  
Pulse On Time ◽  
Pulse Off Time ◽  
Path Modification

In this study, path modification strategy is used to improve the accuracy of the die corner produced in wire electrical discharge machining process. Based on Taguchi’s L18 array, experiments are performed on Monel 400 alloy. The influence of the machine-controllable factors such as wire tension, open-circuit voltage, pulse-on time, pulse-off time and additional travel and uncontrollable factors namely corner angles and flushing nozzle height on the performance measures such as surface roughness, cutting speed, and corner error are studied. The outcome of this study reveals that the path modification value in terms of additional travel of 0.5 mm improves the corner accuracy of the profile by 35% as compared to the profile machined without adopting path modification strategy. The analyses of scanning electron micrographs are carried out. Finally, an optimal technological guideline is reported for ready industrial use.

Parameter optimization and experimental study on wire electrical discharge machining of porous Ni40Ti60 alloy

2015 ◽  
Vol 231 (6) ◽  
pp. 956-970 ◽  
Author(s):  
Neeraj Sharma ◽  
Tilak Raj ◽  
Kamal Kumar Jangra
Keyword(s):  
Process Parameters ◽  
Electrical Discharge ◽  
Electrical Discharge Machining ◽  
Machining Process ◽  
Wire Electrical Discharge Machining ◽  
Influence Of Process Parameters ◽  
Work Surface ◽  
Pulse On Time ◽  
Pulse Off Time ◽  
Response Variables

NiTi is a shape memory alloy, mostly employed in cardiovascular stents, orthopedic implants, orthodontic wires, micro-electromechanical systems and so on. The effective and net shape machining of NiTi is very critical for excellent response of this material in medical and other applications. The present experimental work on wire electrical discharge machining process identifies the influence of process parameters that affect the cutting rate, dimensional shift and surface roughness while machining of porous nickel–titanium (Ni40Ti60) alloy. Porous Ni40Ti60 alloy was produced in-house using powder metallurgy technique. Response surface methodology–based central composite rotatable design has been used for the planning of experiments on wire electrical discharge machining. Empirical relations have been developed between the process parameters (pulse on-time, pulse off-time, servo voltage and peak current) and response variables. Desirability approach has been used for optimizing the three response variables simultaneously. Confirmation experiments were also performed at the optimized settings and reflect a close agreement between the predicted and experimental values (percentage error varies from −6.13% to +6.85%). Using wire electrical discharge machining, NiTi alloy can be machined easily and successfully in single-cutting operation, but after the first cut in wire electrical discharge machining, a surface projection appears on work surface which is the unmachined material on work surface.

scholarly journals Parametric Optimization and Effect of Nano-Graphene Mixed Dielectric Fluid on Performance of Wire Electrical Discharge Machining Process of Ni55.8Ti Shape Memory Alloy

Materials ◽  
2021 ◽  
Vol 14 (10) ◽  
pp. 2533
Author(s):  
Rakesh Chaudhari ◽  
Jay Vora ◽  
L.N.López de Lacalle ◽  
Sakshum Khanna ◽  
Vivek K. Patel ◽  
...  
Keyword(s):  
Shape Memory Alloys ◽  
Shape Memory ◽  
Electrical Discharge ◽  
Electrical Discharge Machining ◽  
Machining Process ◽  
Dielectric Fluid ◽  
Wire Electrical Discharge Machining ◽  
Nano Graphene ◽  
Pulse On Time ◽  
Pulse Off Time

In the current scenario of manufacturing competitiveness, it is a requirement that new technologies are implemented in order to overcome the challenges of achieving component accuracy, high quality, acceptable surface finish, an increase in the production rate, and enhanced product life with a reduced environmental impact. Along with these conventional challenges, the machining of newly developed smart materials, such as shape memory alloys, also require inputs of intelligent machining strategies. Wire electrical discharge machining (WEDM) is one of the non-traditional machining methods which is independent of the mechanical properties of the work sample and is best suited for machining nitinol shape memory alloys. Nano powder-mixed dielectric fluid for the WEDM process is one of the ways of improving the process capabilities. In the current study, Taguchi’s L16 orthogonal array was implemented to perform the experiments. Current, pulse-on time, pulse-off time, and nano-graphene powder concentration were selected as input process parameters, with material removal rate (MRR) and surface roughness (SR) as output machining characteristics for investigations. The heat transfer search (HTS) algorithm was implemented for obtaining optimal combinations of input parameters for MRR and SR. Single objective optimization showed a maximum MRR of 1.55 mm3/s, and minimum SR of 2.68 µm. The Pareto curve was generated which gives the optimal non-dominant solutions.

scholarly journals Multi-response optimization in wire electrical discharge machining (WEDM) of D2 steel using utility approach

2021 ◽  
Vol 8 ◽  
pp. 16
Author(s):  
Ipsita Nayak ◽  
Jaydev Rana
Keyword(s):  
Electrical Discharge ◽  
Electrical Discharge Machining ◽  
Cutting Performance ◽  
Machining Process ◽  
Wire Electrical Discharge Machining ◽  
Response Optimization ◽  
Pulse On Time ◽  
Pulse Off Time ◽  
Machining Parameter ◽  
Utility Approach

Wire electrical discharge machining (WEDM) is a popular non-conventional machining process used particularly for making extrusion dies, blanking punches, and tools especially requiring tight dimensional tolerances. Because of the process limitation, the rate of cutting and maintenance of close dimensional tolerance is a challenging task. Given the above facts, the present work has been focused on achieving the maximum possible cutting rate (VC) maintaining good dimensional accuracy and corner radius (RC). In the present research work, a multi-response optimization method (i.e. Taguchi based Utility approach) has been used to obtain an optimum set of input parameters such as pulse on time (TON), pulse off time (TOFF), servo voltage (SV), and wire feed rate (WF) resulting into a best overall cutting performance. Analysis of variance (ANOVA) is also used to find out the significant effect of each machining parameter on the cutting performance. The analysis reported in this paper will be helpful for industry personnel to select the best set of process parameters for achieving a good result without the use of any software or statistical analysis.

scholarly journals A Fuzzy Modelling for Selection of Machining Parameters in Wire Electrical Discharge Machining of D2 Steel

2020 ◽  
Vol 8 (5) ◽  
pp. 3045-3052
Keyword(s):  
Electrical Discharge ◽  
Electrical Discharge Machining ◽  
Removal Rate ◽  
Fuzzy Model ◽  
Machining Process ◽  
Wire Electrical Discharge Machining ◽  
Machining Parameters ◽  
Pulse On Time ◽  
Pulse Off Time ◽  
Selection Of

Wire Electrical Discharge Machining (WEDM) is a widely used non-traditional machining process used for machining of hard and difficult-to-machine materials. Proper selection of machining parameters in WEDM is required for better output performance, such as Material Removal Rate (MRR), Wire Wear Rate (WWR) and Surface Roughness (SR) etc. In the present paper, Pulse ON time, Pulse OFF time, Peak Current, Spark Voltage, Wire Feed and Wire Tension were taken as the input parameters to optimize MRR, WWR and SR. A set of 27 experiments were performed as per Taguchi Design. A Fuzzy model has been proposed to select the optimum values of machining parameters. The proposed fuzzy model was found to predict the experimental values with more than 90 percent accuracy.

Surface Roughness at Wire Electrical Discharge Machining

2015 ◽  
Vol 760 ◽  
pp. 551-556 ◽  
Author(s):  
Oana Dodun ◽  
Laurenţiu Slătineanu ◽  
Margareta Coteaţă ◽  
Vasile Merticaru ◽  
Gheorghe Nagîţ
Keyword(s):  
Surface Roughness ◽  
Empirical Model ◽  
Electrical Discharge ◽  
Electrical Discharge Machining ◽  
Roughness Parameter ◽  
Wire Electrical Discharge Machining ◽  
Power Type ◽  
Surface Roughness Parameter ◽  
Pulse On Time ◽  
Pulse Off Time

Wire electrical discharge machining is a machining method by which parts having various contours could be detached from plate workpieces. The method uses the electrical discharges developed between the workpiece and the wire tool electrode found in an axial motion, when in the work zone a dielectric fluid is recirculated. In order to highlight the influence exerted by some input process factors on the surface roughness parameter Ra in case of a workpiece made of an alloyed steel, a factorial experiment with six independent variables at two variation levels was designed and materialized. As input factors, one used the workpiece thickness, pulse on time, pulse off-time, wire axial tensile force, current intensity average amplitude defined by setting button position and travelling wire electrode speed. By mathematical processing of the experimental results, empirical models were established. Om the base of a power type empirical model, graphical representations aiming to highlight the influence of some input factors on the surface roughness parameter Ra were achieved. The power type empirical model facilitated establishing of order of factors able to exert influence on the surface roughness parameter Ra at wire electrical discharge machining.

scholarly journals Multi-Objective Optimization of Wire Electrical Discharge Machining of AL 2124/SIC Composite

2019 ◽  
Vol 9 (1) ◽  
pp. 2155-2163
Keyword(s):  
Electrical Discharge ◽  
Electrical Discharge Machining ◽  
Removal Rate ◽  
High Strength ◽  
Wire Electrical Discharge Machining ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Predicted Values ◽  
Pulse On Time ◽  
Pulse Off Time

The growing demand for the use of high strength to weight alloys in industries for manufacturing complex structures challenges the machinability of such advanced materials. In the present investigation, the machinability of SiC particle reinforced Al 2124 composite was studied on Wire electrical discharge machining (WEDM). The process parameters namely pulse on-time (Ton), pulse off time (Toff), peak current (IP), and servo voltage (SV) were optimized by utilizing the central composite design layout. The output responses such as kerf and material removal rate (MRR) were studied in detail. The single and multi-objective optimization was studied for a combination effect using Derringer’s desirability approach and Genetic Algorithm (GA). The experimental and predicted values for each response were validated at the optimized condition. The experimental results were found in line with the predicted values. Multi objective optimization of kerf and MRR by GA showing better result compared to RSM.

Influence of Pulse-on-Time on the Performance of Wire Electrical Discharge Machining of Ti-6Al-4V Using Zinc Coated Brass Wire

2014 ◽  
Vol 592-594 ◽  
pp. 416-420 ◽  
Author(s):  
Singaravelu D. Lenin ◽  
A. Uthirapathi ◽  
Ramana Reddy P.S. Venkata ◽  
Muthukannan Durai Selvam
Keyword(s):  
Surface Roughness ◽  
Electrical Discharge ◽  
Metal Removal ◽  
Electrical Discharge Machining ◽  
Kerf Width ◽  
Dielectric Fluid ◽  
Wire Electrical Discharge Machining ◽  
Pulse On Time ◽  
Pulse Off Time ◽  
Brass Wire

The present paper describes the influence of pulse-on-time on performance features such as Metal Removal Rate (MRR), Kerf width, Surface Roughness (SR) on cutting Titanium alloy (Ti-6Al-4V) in wire electrical discharge machining (WEDM) using zinc coated brass wire. The deionised water is used as dielectric fluid. The process parameters such as wire tension, wire speed, flushing pressure, discharge current, sparking voltage and pulse off time have kept constant at appropriate values throughout the experiment and the pulse on time is varied at nine different intervals. It was found that pulse-on-time is the most significant factor which greatly influences MRR, kerf width, and SR. It was also observed that taper at the end of cutting zone which is unavoidable occurrence for the machined part. This is due to the erosion of wire material. The surface roughness increases with increase in pulse on time also with higher rate of MRR.

Influence of Process Parameters on Characteristics of Electrical Discharge Machining of PH17-4 Stainless Steel

2015 ◽  
Vol 14 (03) ◽  
pp. 189-202 ◽  
Author(s):  
V. Vikram Reddy ◽  
P. Madar Valli ◽  
A. Kumar ◽  
Ch. Sridhar Reddy
Keyword(s):  
Material Removal Rate ◽  
Electrical Discharge ◽  
Material Removal ◽  
Electrical Discharge Machining ◽  
Removal Rate ◽  
Surface Hardness ◽  
Machining Process ◽  
Pulse On Time ◽  
Pulse Off Time ◽  
Off Time

In the present work, an investigation has been made into the electrical discharge machining process during machining of precipitation hardening stainless steel PH17-4. Taguchi method is used to formulate the experimental layout, to analyze the effect of each process parameter on machining characteristics and to predict the optimal choice for each electrical discharge machining process parameters namely, peak current, pulse on time and pulse off time that give up optimal process performance characteristics such as material removal rate, surface roughness, tool wear rate and surface hardness. To identify the significance of parameters on measured response, the analysis of variance has been done. It is found that parameters peak current and pulse on time have the significant affect on material removal rate, surface roughness, tool wear rate and surface hardness. However, parameter pulse off time has significant affect on material removal rate. Confirmation tests are conducted at their respective optimum parametric settings to verify the predicted optimal values of performance characteristics.

Surface Roughness Optimization of Wire Electrical Discharge Machining Using ABC Algorithm

2015 ◽  
Vol 766-767 ◽  
pp. 902-907
Author(s):  
Bibin K. Tharian ◽  
B. Kuriachen ◽  
Josephkunju Paul ◽  
Paul V. Elson
Keyword(s):  
Surface Roughness ◽  
Process Parameters ◽  
Electrical Discharge ◽  
Electrical Discharge Machining ◽  
Wire Electrical Discharge Machining ◽  
Wire Tension ◽  
Pulse On Time ◽  
Pulse Off Time ◽  
Off Time ◽  
Wire Feed

Wire electrical discharge machining is one of the important non-traditional machining processes for machining difficult to machine materials. It involves the removal of material by the discrete electric discharges produced between the inter electrode gap of continuously moving wire electrode and the work piece. The ability to produce intricate profiles on materials irrespective of the mechanical properties made this process to be widely used in industries. The present study investigates the relationship of various process parameters in WEDM of AISI 202 stainless steel with brass electrode.The experiments were planned according to Taguchi’s L18 orthogonal array and experimental models were developed. The important process parameters identified for the present study were pulse on time, peak current, pulse off time, wire feed, wire tension, dielectric flushing pressure, servo feed and gap voltage. The surface roughness of the machined surface was measured as the process performance measure. Analysis of variance test has also been carried out to check the adequacy of the developed models and to identify the level of significance of each process parameters. In addition to the developed models, ABC optimization has been performed to identify the optimum parameter combination for minimum surface roughness and the obtained optimal process parameters are peak current 11 A, pulse on time 100 μs, pulse off time 49 μs, wire feed 4 m/min, wire tension 10 N, flushing pressure 12 kg/cm2, servo feed 2100 mm/min and set gap voltage 30 V. Finally the results were verified with the experimental results and found that they are in good agreement.

scholarly journals Surface Roughness Prediction for Steel 304 In Edm Using Response Graph Modeling

2018 ◽  
Vol 14 (4) ◽  
pp. 115-124 ◽  
Author(s):  
Shukry H. Aghdeab ◽  
Nareen Hafidh Obaeed ◽  
Marwa Qasim Ibraheem
Keyword(s):  
Surface Roughness ◽  
Electrical Discharge ◽  
Electrical Discharge Machining ◽  
Machining Process ◽  
Applied Current ◽  
Graph Modeling ◽  
Pulse On Time ◽  
Pulse Off Time ◽  
The Impact ◽  
Off Time

Electrical Discharge Machining (EDM) is a non-traditional cutting technique for metals removing which is relied upon the basic fact that negligible tool force is produced during the machining process. Also, electrical discharge machining is used in manufacturing very hard materials that are electrically conductive. Regarding the electrical discharge machining procedure, the most significant factor of the cutting parameter is the surface roughness (Ra). Conventional try and error method is time consuming as well as high cost. The purpose of the present research is to develop a mathematical model using response graph modeling (RGM). The impact of various parameters such as (current, pulsation on time and pulsation off time) are studied on the surface roughness in the present research. 27 samples were run by using CNC-EDM machine which used for cutting steel 304 with dielectric solution of gas oil by supplied DC current values (10, 20, and 30A). Voltage of (140V) uses to cut 1.7mm thickness of the steel and use the copper electrode. The result from this work is useful to be implemented in industry to reduce the time and cost of Ra prediction. It is observed from response table and response graph that the applied current and pulse on time have the most influence parameters of surface roughness while pulse off time has less influence parameter on it. The supreme and least surface roughness, which is achieved from all the 27 experiments is (4.02 and 2.12µm), respectively. The qualitative assessment reveals that the surface roughness increases as the applied current and pulse on time increases

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