MICROSTRUCTURAL ANALYSIS OF TITANIUM ALLOY GEAR USING WEDM PROCESS

2018 ◽  
Vol 25 (06) ◽  
pp. 1850112
Author(s):  
K. D. MOHAPATRA ◽  
S. K. SAHOO
Keyword(s):  
Titanium Alloy ◽  
Microstructural Analysis ◽  
Machining Process ◽  
Material Surface ◽  
Work Piece ◽  
The Wire ◽  
Pulse On Time ◽  
Pulse Off Time ◽  
Wedm Process ◽  
Brass Wire

The present paper deals with the microstructural analysis of Titanium alloy gears (Ti-6Al-4V) by wire EDM process machined by both brass and combii wire electrodes. The objective of the present paper is to investigate the surface characteristics of both the wires and to analyze the effects on the material surface. Two types of wires i.e. brass wire and combii wires were selected for the analysis and the experiment was carried out using a full factorial design having 81 sets of combinations. Pulse on time, pulse off time, wire feed rate and servo voltage were taken as the input parameters and kerf width, material removal rate, surface roughness and wire wear rate were taken as the response parameters for the experiment. The output responses were optimized by using MOORA-based GA methodology. Microstructural analysis was carried out at the optimized settings obtained by two types of wires to investigate the surface defects and analysis present in the work-piece and the wire. The microstructural analysis for the brass wire was investigated depicting the formation of micro cracks, dendrites, spherical globules, melted debris, recast layer and wire rupture on the wire surface after the machining operation. Similarly the microstructural analysis for the combii wire was analyzed out depicting the formation of wire rupture, melted debris, spherical globules, cracks and wire burr formed on the wire after the machining process. The optical image confirms that brass wire has more rupture than the combii wire due to the spark efficiency of brass wire being more than the combii wire. The EDS of material and the wires have been analyzed depicting the presence of element and weight % in the sample. From the performance analysis and the present experiment attained, it was concluded that the combii wire is more desirable to produce high quality gears than the brass wires at the obtained optimized settings of the response.

Performance Analysis on Eco-friendly Machining of Ti6Al4V using Powder Mixed with Different Dielectrics in WEDM

2020 ◽  
Vol 17 (3) ◽  
pp. 8128-8139
Author(s):  
S. Chakraborty ◽  
S. Mitra ◽  
D. Bose
Keyword(s):  
Metal Removal ◽  
Removal Rate ◽  
Machining Process ◽  
Process Efficiency ◽  
Machining Parameters ◽  
Dielectric Fluids ◽  
High Emission ◽  
Pulse On Time ◽  
Pulse Off Time ◽  
Wedm Process

The recent scenario of modern manufacturing is tremendously improved in the sense of precision machining and abstaining from environmental pollution and hazard issues. In the present work, Ti6Al4V is machined through wire EDM (WEDM) process with powder mixed dielectric and analyzed the influence of input parameters and inherent hazard issues. WEDM has different parameters such as peak current, pulse on time, pulse off time, gap voltage, wire speed, wire tension and so on, as well as dielectrics with powder mixed. These are playing an essential role in WEDM performances to improve the process efficiency by developing the surface texture, microhardness, and metal removal rate. Even though the parameter’s influencing, the study of environmental effect in the WEDM process is very essential during the machining process due to the high emission of toxic vapour by the high discharge energy. In the present study, three different dielectric fluids were used, including deionised water, kerosene, and surfactant added deionised water and analysed the data by taking one factor at a time (OFAT) approach. From this study, it is established that dielectric types and powder significantly improve performances with proper set of machining parameters and find out the risk factor associated with the PMWEDM process.

Machining Characteristics Estimation in WEDM Process While Machining Titanium Grade-2 Material Using ANN

2020 ◽  
Author(s):  
Prathik Jain Sudhir ◽  
Ravindra Holalu Venkatadas ◽  
Ugrasen Gonchikar
Keyword(s):  
Process Parameters ◽  
Machining Process ◽  
Electrode Wear ◽  
Training Set ◽  
Hard Materials ◽  
Titanium Grade ◽  
Pulse On Time ◽  
Pulse Off Time ◽  
Wedm Process ◽  
Machining Characteristics

Abstract Wire Electrical Discharge Machining (WEDM) provides an effective solution for machining hard materials with intricate shapes. WEDM is a specialized thermal machining process is capable to accurately machining parts of hard materials with complex shapes. However, selection of process parameters for obtaining higher machining efficiency or accuracy in wire EDM is still not fully solved, even with the most up-to-date CNC WED machine. The study presents the machining of Titanium grade 2 material using L’16 Orthogonal Array (OA). The process parameters considered for the present work are pulse on time, pulse off time, current, bed speed, voltage and flush rate. Among these process parameters voltage and flush rate were kept constant and the other four parameters were varied for the machining. Molybdenum wire of 0.18mm is used as the electrode material. Titanium is used in engine applications such as rotors, compressor blades, hydraulic system components and nacelles. Its application can also be found in critical jet engine rotating and airframes components in aircraft industries. Firstly optimization of the process parameters was done to know the effect of most influencing parameters on machining characteristics viz., Surface Roughness (SR) and Electrode Wear (EW). Then the simpler functional relationship plots were established between the parameters to know the possible information about the SR and EW. This simpler method of analysis does not provide the information on the status of the material and electrode. Hence more sophisticated method of analysis was used viz., Artificial Neural Network (ANN) for the estimation of the experimental values. SR and EW parameters prediction was carried out successfully for 50%, 60% and 70% of the training set for titanium material using ANN. Among the selected percentage data, at 70% training set showed remarkable similarities with the measured value then at 50% and 60%.

scholarly journals Multi-Objective Optimization of Wire Electro Discharge Machining (WEDM) Process Parameters Using Grey-Fuzzy Approach

2018 ◽  
Vol 63 (1) ◽  
pp. 16-25 ◽  
Author(s):  
Partha Protim Das ◽  
Sunny Diyaley ◽  
Shankar Chakraborty ◽  
Ranjan Kumar Ghadai
Keyword(s):  
Process Parameters ◽  
Removal Rate ◽  
Machining Process ◽  
Wire Tension ◽  
Electro Discharge Machining ◽  
Pulse On Time ◽  
Pulse Off Time ◽  
Wedm Process ◽  
Fuzzy Logic Technique ◽  
Off Time

Wire electro discharge machining (WEDM) is a versatile non-traditional machining process that is extensively in use to machine the components having intricate profiles and shapes. In WEDM, it is very important to select the optimal process parameters so as to enhance the machine performance. This paper emphasizes the selection of optimal parametric combination of WEDM process while machining on EN31 steel, using grey-fuzzy logic technique. Process parameters such as servo voltage, wire tension, pulse-on-time and pulse-off-time were considered while taking into account several multi-responses such as material removal rate (MRR) and surface roughness (SR). It was found that pulse-on-time of 115 µs, pulse-off-time of 35 µs, servo voltage of 40 V and wire tension of 5 kgf results in a larger value of grey fuzzy reasoning grade (GFRG) which tends to maximize MRR and improve SR. Finally, analysis of variance (ANOVA) is applied to check the influence of each process parameters in the estimation of GFRG.

scholarly journals Taguchi Optimization In Machining Inconel 600 With WEDM Process Using Cryogenically Treated Brass Wire

2021 ◽  
Vol 309 ◽  
pp. 01110
Author(s):  
K. Satyanarayana ◽  
B Ramya Krishna ◽  
M. Bhargavi ◽  
R. Eswari Vasuki ◽  
K. Raj Kiran
Keyword(s):  
Surface Roughness ◽  
Metal Removal ◽  
Removal Rate ◽  
Machining Parameters ◽  
Inconel 600 ◽  
Pulse On Time ◽  
Pulse Off Time ◽  
Wedm Process ◽  
Off Time ◽  
Brass Wire

Wire electric discharge machining (WEDM) is one amongst the unconventional machining processes which might cut all kinds of shapes with an accuracy of +/−0.001mm. It will cut the materials that conduct electricity and can even cut the exotic metals like tungsten carbide, Hastelloy, Inconel etc. In the present work, machining on Inconel 600 by wire EDM with cryogenically treated brass wire is performed. Brass wire of 0.25mm diameter has been cryogenically treated at −90°C, −100°C and −110°C temperatures separately. An Experimental layout is designed as per Taguchi’s L-9 orthogonal array and experiments were conducted by varying machining parameters viz. Voltage, Pulse ON time and Pulse OFF time. The machining parameters are optimized using Taguchi’s methodology for minimum surface roughness and maximum metal removal rate (MRR). A Mathematical regression model for surface roughness and MRR is generated with the help of regression analysis. Through the Analysis of Variance (ANOVA) It was found that for MRR, pulse on time is the foremost contributing factor with 32.69% and for surface roughness, pulse off time is the foremost contributing factor with 23.59%.

scholarly journals PSI and TOPSIS Based Selection of Process Parameters in WEDM

2017 ◽  
Vol 61 (4) ◽  
pp. 255 ◽  
Author(s):  
Sunny Diyaley ◽  
Pramod Shilal ◽  
Ishwer Shivakoti ◽  
Ranjan Kumar Ghadai ◽  
Kanak Kalita
Keyword(s):  
Tool Steel ◽  
Process Parameters ◽  
Machining Process ◽  
Wire Tension ◽  
Input Parameters ◽  
The Wire ◽  
Pulse On Time ◽  
Pulse Off Time ◽  
Off Time ◽  
Selection Of

Wire electric discharge machining (WEDM) is a nontraditional machining process for machining conductive materials with complex and intricate shapes with a high surface finish and dimensional accuracy. The decision making for the selection of the best set of combinations of input process parameters is a major challenge. Therefore a proper optimization tool should be used for the optimal selection of process parameters. The resent work deals with the comparative study of Preferential Selection Index (PSI) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) for the selection of process parameters during machining of EN31 tool steel. Four input parameters- Pulse on Time (Ton ), Pulse off Time (Toff  ), Servo Voltage (SV) and the Wire tension (WT) are considered. Surface roughness and material removal rate are the measured output responses. Taguchi L9 orthogonal array is used for developing the experimental design. Three levels of each control factor are considered. The results show that a single parameter alone does not have a significant influence on the output responses. Thequality of the output responses depends on the combination of the various set of input parameters. The best set of combination suggested from the current input parameters for machining of EN31 Tool Steel by Wire EDM Process is found to be Pulse on Time (Ton )= 15μs, Pulse Off Time (Toff  )=35μs, Servo Voltage (SV)=40V and the Wire tension (WT)=5kgf from both PSI as well as TOPSIS techniques. Confirmation experiments are performed to validate the optimal results.

COMPARATIVE STUDY OF MATERIAL REMOVAL RATE AND TOOL WEAR RATE OF COPPER AND ALUMINIUM ON DIE SINKING EDM

2015 ◽  
Vol 77 (21) ◽  
Author(s):  
Maidin S. ◽  
H.H. El Grour ◽  
Seeying C.
Keyword(s):  
Tool Wear ◽  
Material Removal Rate ◽  
Material Removal ◽  
Removal Rate ◽  
Copper Electrode ◽  
Machining Process ◽  
Work Piece ◽  
Small Depth ◽  
Pulse On Time ◽  
Pulse Off Time

The electrical discharge machining (EDM) is one of non - conventional machining process where the erosion of the work piece take place based on the thermal energy between the electrode and the work piece. Due to the widely used and its availability, copper and aluminium was used in this study. These two materials was machined using die sinking EDM to study the characteristics of each material using copper electrode. Few research has been conducted to study copper electrode to machined copper work piece and this was considered as a challenge in this research. More heat was generated and more time consumed was the reason behind machining small depth in this research. The important factors such as discharge current, voltage, pulse on time and pulse off time monitored and recorded to know how these factors effect on the Material Removal Rate (MRR) and Tool Wear Ratio (TWR) of the copper and aluminium work piece material. The experiments conducted under the designed full factorial procedure where pulse on-time and pulse current are used as the input parameters. It was found that material MRR increases with increase in current and pulse duration, but MRR is higher during machining of aluminum than that of copper. In term of TWR it is found that the TWR resulting of machining copper is lower than aluminium

scholarly journals Optimization of Wire EDM Process Parameters for Medical Grade Nickel Titanium Shape Memory Alloy

2020 ◽  
Vol 70 (1) ◽  
pp. 69-80
Author(s):  
Vinayak N Kulkarni ◽  
V N Gaitonde ◽  
K S Nalavade ◽  
Mrityunjay Doddamani ◽  
Gajanan M Naik
Keyword(s):  
Shape Memory ◽  
Process Parameters ◽  
Nickel Titanium ◽  
Machining Process ◽  
Simultaneous Optimization ◽  
System Control ◽  
Morphological Studies ◽  
Pulse On Time ◽  
Pulse Off Time ◽  
Wedm Process

AbstractNickel Titanium (NiTi) alloys are the class of smart materials classified under shape memory alloys. The traditional machining of these alloys is hard because of various inherent mechanical characteristics of these alloys. Therefore, non-traditional machining process such as wire electro discharge machining (WEDM) has been employed for machining of such alloys. The present study is focused on multi-performance characteristic simultaneous optimization of WEDM process parameters, in which three system control factors, namely, pulse on time (TON), pulse off time (TOFF) and wire feed (WF) are considered for simultaneously maximizing material removal rate (MRR), while minimizing surface roughness (SR) and tool wear rate (TWR). The simultaneous optimization is performed using Taguchi’s Quality Loss Function. Analysis of means and analysis of variance have been carried out to identify the significance level of each system control factor. The different levels of settings and the optimized setting have been analysed using scanning electron microscope images for surface morphological studies. The multi-response optimization investigations revealed that TON is the major contributing factor and optimal performance values were obtained at TON of 125μs, TOFF of 25μs and at WF of 4 m/min.

Multi-Response Optimization of Wire-EDM Process Parameters of Titanium Alloy Using Taguchi Method and Grey Relational Analysis

2015 ◽  
Vol 772 ◽  
pp. 245-249
Author(s):  
A. Ramamurthy ◽  
R. Sivaramakrishnan ◽  
S. Venugopal ◽  
T. Muthuramalingam
Keyword(s):  
Titanium Alloy ◽  
Process Parameters ◽  
Grey Relational Analysis ◽  
Wire Edm ◽  
Relational Analysis ◽  
Response Optimization ◽  
Grey Relational ◽  
Pulse On Time ◽  
Pulse Off Time ◽  
Edm Process

It is very important and complexity to find the optimum values of wire EDM process parameters and contribution of each parameter to attain the better performance characteristics. In this study, an attempt has been made to optimize those parameters while machining the titanium alloy. Since the process involves more one than one response parameter, it is essential to carry out the multi-response optimization methodology .The experiments have been conducted with different levels of input factors such as pulse on time,pulse off time and wire tension based on Taguchi L9 orthogonal table.Wire EDM optimal process parameter has been identified using grey relational analysis and significant parameter has been determined by analysis of variance. Experimental results have indicated that the multi-response characteristic such as material removal rate and surface roughness can be improved effectively through grey relational analysis.

scholarly journals Study of wire-electrical discharge machining parameters of titanium alloy by using taguchi method

2018 ◽  
Vol 7 (2.8) ◽  
pp. 10
Author(s):  
A VS Ram Prasad ◽  
Koona Ramji ◽  
B Raghu Kumar
Keyword(s):  
Surface Roughness ◽  
Taguchi Method ◽  
Process Parameters ◽  
Optimization Technique ◽  
Machining Process ◽  
Machining Parameters ◽  
Wire Edm ◽  
Pulse On Time ◽  
Pulse Off Time ◽  
Edm Process

Machining of Titanium alloys is difficult due to their chemical and physical properties namely excellent strength, chemical reactivity and low thermal conductivity. Traditional machining of such materials leads to formation of continuous chips and tool bits are subjected to chatter which leads to formation of poor surface on machined surface. In this study, Wire-EDM one of the most popular unconventional machining process which was used to machine such difficult-to-cut materials. Effect of Wire-EDM process parameters namely peak current, pulse-on- time, pulse-off-time, servo voltage on MRRand SR was investigated by Taguchi method. 0.25 mm brass wire was used in this process as electrode material. A surface roughness tester (Surftest 301) was used to measure surface roughness value of the machined work surface. A multi-response optimization technique was then utilized to optimize Wire-EDM process parameters for achieving maximum MRR and minimum SR simultaneously.

scholarly journals Modelling of Rotary EDM Process Parameters of Inconel 718 Using Artificial Neural Networks

Mechanika ◽  
2020 ◽  
Vol 26 (6) ◽  
pp. 540-544
Author(s):  
Jayaraj JEEVAMALAR ◽  
Sundaresan RAMABALAN ◽  
Chinnamuthu SENTHILKUMAR
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Process Parameters ◽  
Inconel 718 ◽  
Machining Process ◽  
Artificial Neural ◽  
Pulse On Time ◽  
Pulse Off Time ◽  
Matlab Programming ◽  
The Relationship

Modelling is used for correlating the relationship between the input process parameters and the output responses during the machining process. To characterize real-world systems of considerable complexity, an Artificial Neural Network (ANN) model is regularly used to replace the mathematical approximation of the relationship. This paper explains the methodological procedure and the outcome of the ANN modeling process for Electrical Discharge Drilling of Inconel 718 superalloy and hollow tubular copper as tool electrode. The most important process parameters in this work are peak current, pulse on time and pulse off time with machining performances of material removal rate and surface roughness. The experiments were performed by L20 Orthogonal Array. In such conditions, an Artificial Neural Network model is developed using MATLAB programming on the Feed Forward Back Propagation technique was used to predict the responses. The experimental data were separated into three parts to train, test the network and validate the model. The developed model has been confirmed experimentally for training and testing in considering the number of iterations and mean square error convergence criteria. The developed model results are to approximate the responses fairly exactly. The model has the mean correlation coefficient of 0.96558. Results revealed that the proposed model can be used for the prediction of the complex EDM drilling process.

Sign in / Sign up

Export Citation Format

Share Document