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Optimization of machining parameters of wire-cut EDM on ceramic particles reinforced Al-metal matrix composites – A review
Materials Today: Proceedings xxx (xxxx) xxx
Contents lists available at ScienceDirect
Materials Today: Proceedings journal homepage: www.elsevier.com/locate/matpr
Optimization of machining parameters of wire-cut EDM on ceramic particles reinforced Al-metal matrix composites – A review D. Vijay Praveen a,⇑, D. Ranga Raju b, M.V. Jagannadha Raju c a
Department of Mechanical Engineering, Andhra University, Vishakhapatnam, India Department of Mechanical Engineering, Srinivasa Institute of Engineering & Technology, Amalapuram, India c Department of Mechanical Engineering, A.U. College of Engineering (A), Vishakhapatnam, India b
a r t i c l e
i n f o
Article history: Received 29 March 2019 Received in revised form 6 May 2019 Accepted 10 May 2019 Available online xxxx Keywords: Al-MMC Wire-cut EDM Optimization AMMC Taguchi
a b s t r a c t Wire-cut Electrical discharge machining process [WEDM] is used in manufacturing industries to machine conductive and hard materials like metal matrix composites, ceramic composites and super alloys, which are having enormous applications in space craft, defense, transportation vehicles, micro systems, farm machinery etc. Aluminum based ceramic particle reinforced metal matrix materials is one of the key factor in producing composites, which enhances mechanical and thermal properties. These Composites (AlMMCs) owing to having higher strength and stiffness are suitable for variety of engineering applications The current paper reviews the optimization of WEDM machining parameters, responses by deploying different techniques. Ó 2019 Elsevier Ltd. All rights reserved. Selection and peer-review under responsibility of the scientific committee of the International Conference on Recent Advances in Materials, Manufacturing & Energy Systems.
1. Introduction Researchers nowadays are showing interests into advanced materials like ceramic particle reinforced composites, hybrid composites; metal particle coated ceramic reinforced MMCs for the development of advanced components for the present generation. Conventional machining such as turning, milling, drilling etc. shows inefficacious in machining of ceramic reinforced MMCs [1]. Non-uniform distribution of reinforced particles, high hardness, and higher brittleness leads to poor materials removal rate, excessive tool wear and increased surface roughness [2]. Consecutively to attain complex shapes in the composite materials, researchers are focusing on non-conventional machining techniques which can be successfully employed to machine composite materials [3–4] Fig. 1. Non-Conventional Machining processes are classified with the sort of energy used for the machining of the work materials. i.e. (Ultrasonic machining, Water jet machining, Abrasive jet machining, Thermal Electrical discharge machining, Electron beam machining, Laser beam machining, and chemical machining). Most of these non-conventional machining processes are still need to be
analyzed to determine the ‘‘optimal” machining conditions and achieve cost efficient machining in combination with high process reliability and reproducibility [2]. Wire Electrical Discharge Machine (WEDM) is a distinctive promotion of Conventional EDM process, which uses an electrode to initialize the sparking process. WEDM is becoming more important in providing a non-contact machining process, which is suitable for effective machining of MMCs regardless of the hardness and the complexity in contours over the components [4]. WEDM utilizes a incessantly travelling wire electrode made of skinny copper, brass or tungsten of diameter 0.05–0.30 mm, which is capable of achieving very small corner radii, is fed on-to the work piece, that is submerged in a tank of dielectric fluid like deionized water. The wire that is consistently fed from a spool is held between upper and lower diamond guides. The guides are usually CNC-controlled and move within the x–y plane. Filters and deionizing units are used for controlling the resistivity and other electrical properties. The water conjointly helps in flushing away the rubble from the cutting zone. The flushing also helps to determine the feed rates to be given for a variety of thickness of the materials. During the WEDM method, the material is battered ahead of the wire and there’s no direct contact between the work piece and also the wire, eliminating the mechanical stresses during
⇑ Corresponding author. E-mail address: [email protected] (D. Vijay Praveen). https://doi.org/10.1016/j.matpr.2019.05.392 2214-7853/Ó 2019 Elsevier Ltd. All rights reserved. Selection and peer-review under responsibility of the scientific committee of the International Conference on Recent Advances in Materials, Manufacturing & Energy Systems.
Please cite this article as: D. Vijay Praveen, D. Ranga Raju and M. V. Jagannadha Raju, Optimization of machining parameters of wire-cut EDM on ceramic particles reinforced Al-metal matrix composites – A review, Materials Today: Proceedings, https://doi.org/10.1016/j.matpr.2019.05.392
2
D. Vijay Praveen et al. / Materials Today: Proceedings xxx (xxxx) xxx
Fig.1. schematic diagram of wire cut EDM [18].
machining. The following figure shows the schematic diagram of Wire cut EDM experimental setup. 2. WEDM process parameters Input machining process parameters can be broadly classified as electrical parameters and non electrical parameters. Electrical parameters are servo voltage, pulse on time, pulse off time, peak current, Gap voltage etc. Non electrical parameters such as wire material, wire tension, wire feed rate, wire size, dielectric flow rate, dielectric conductivity, work piece material and work piece size. 3. WEDM machining features The following are the characteristics of the WEDM, which must be optimized for economy and better performance. They are Metal Removal rate (MRR), Surface Roughness (Ra) [5,6]. 3.1. Metal removal rate (MRR) MRR can be obtained by the ratio between volume of material removal to time taken for the machining. It highly influences the efficiency of the machining process. It depends upon the parameters which are related with the machining process. Many authors had worked to maximize the material removal rate using different approaches. 3.2. Surface roughness (Ra) The surface roughness (Ra) value of the square block is quantified in lm by using a surface roughness tester SJ-210, which is very important parameter to be minimized. To attain good surface finish, there is need to control the influencing parameters like dielectric medium, material and electrical parameters. Several researchers suggested that to achieve good surface finish electrical discharge current must be controlled. 4. Literature review The following literature describes the research findings carried out by various authors on different types of MMCs, techniques used, their responses, which lead to future research prospects. Harmesh kumar et al. [7] Analyzed the process parameters for surface roughness height and used RSM based Box–Behnken design for experimental investigation and developed quadratic
regression model for surface roughness height (Ra) of SiC reinforced Al metal matrix composite during WEDM. An attempt had been made to optimize the process parameters for surface roughness height (Ra) and also discussed the possible reasons of various surface defects. Kumar Dinesh et al. [8] Investigated the effect of process parameters on the combined objective of maximum Metal Removal Rate (MRR) and minimum Surface Roughness (SR) during machining of AA7178-10 wt% ZrB2 composite using Taguchi based Grey Relational Analysis (GRA) and revealed that peak current and pulse on time are influencing the machining factors. L16 orthogonal array, for the four machining parameters at four levels each, was opted to conduct the experiments. Analysis of variance (ANOVA) was performed to find the validity of the experimental data. Dey et al. [9] analyzed the effects of significant machining parameters on the performance characteristics using Box Behnken of response surface methodology. ANOVA analysis was imposed to investigate the influence of process variables and their interactions and concluded that surface roughness decreases with the increase of pulse on time. Udaya Prakash et al. [10] used S/N analysis for optimizing the WEDM input parameters of 356/B4C composites for better MRR and concluded that gap voltage has highest influence on MRR and also studied the effect of reinforcement. Ugrasen et al. [11] investigated on estimation of machining performances in the WEDM of Al-2024-5%TiC-5% fly ash hybrid metal matrix composite using Multiple Regression Analysis (MRA) and Group Method of Data Handling (GMDH) technique. They concluded that dimensional error can be minimized by low pulse off and low current and maximum MRR can be achieved at high bed speed and high pulse on. Mohinder Pal Garg et al. [12] investigated the dimensional deviation induced by WEDM of zirconium silicate reinforced Al6063 using RSM. Analysis of variance (ANOVA) technique is used to analyze the characteristics and confirmation experiments had also been conducted for verification and concluded that dimensional deviation impacted by large values of pulse on time, peak current. Shubhajit Das et al. [13] used RSM modeling to analyze the influence of process parameters of WEDM process of Al-6061 metal matrix composite (MMC) reinforced with 7%SiC/ 3%B4C hybrid MMCs and the machining characteristics are evaluated using desirability analysis (DA) and suggested that voltage and pulse-on time are more influencing factors on surface roughness. Pramanik et al. [14] investigated the effect of the size of reinforced particles on Al6061alloy with 10% of SiC reinforced MMCs while wire electrical discharge machining in terms of material removal rate (MRR), surface integrity and wear of wire electrodes (WEs).
Please cite this article as: D. Vijay Praveen, D. Ranga Raju and M. V. Jagannadha Raju, Optimization of machining parameters of wire-cut EDM on ceramic particles reinforced Al-metal matrix composites – A review, Materials Today: Proceedings, https://doi.org/10.1016/j.matpr.2019.05.392
D. Vijay Praveen et al. / Materials Today: Proceedings xxx (xxxx) xxx
Chengal Reddy [15] used Taguchi’s grey relational analysis to optimize the process parameters on multiple performance characteristics such as Material removal rate, surface finish. The results showed that the combination of pulse on time, pulse off time, wire tension, lower flush, wire tension and upper flush is essential to achieve maximization of material removal rate and minimization of surface roughness and kerf width. Naga Raju et al. [16] had studied the effect of machining parameters (i.e. pulse on time, pulse off time and peak current) on Al alloy with 5% SiC while WEDM and concluded with optimal machining characteristics. Ravindranadh Bobbili et al. [17] had carried out a comparative study between AL7017 and RHA steel using Buckingham Pi theorem establish the relationship between machine variables and performance measures. Results revealed that wear rate of brass wire increases with increase in input energy leads to wire breakage. He had shown the dependence of thermo physical parameters on the mechanism of MRR and Ra. Ravindranadh Bobbili et al. [18] had performed experimentation on WEDM on ballistic grade aluminum alloy material as per Taguchi technique. He developed mathematical model using RSM and determined the relation between machine variables and performance measures. Ashish Srivastava et al. [19] carried out the experimental study on composite of Al2024/SiC investigate the effects parameters such as current, pulse on time and volume fraction on surface finish and MRR. Response surface methodology technique applied to optimize the machining parameters for minimum surface roughness and maximum MRR. He revealed that surface roughness increases with the increase of reinforcement percentage, pulse on time and MRR increased with increase in peak current and pulse on time. Babu rao et al. [20] investigated machining performance of SiCp reinforced Al7075 during WEDM. Response surface methodology is used to build up the pragmatic models and Analysis of variance (ANOVA) is used to confirm the capability of the developed models. Non-dominated Sorting Genetic Algorithm-II was used to solve the developed problem and the results were validated by experimental tests. Selvakumar et al. [21] optimized the machining parameters of Al 5083 alloy while WEDM. ANOVA test was performed to determine to level of significance of parameters on cutting speed and surface roughness and revealed that cutting speed was independent of wire tension and surface roughness is independent of pulse off time and wire tension. Bagherian Azhiri et al. [22] analyzed experimental dry WEDM process to enhance the machining environment by replacing the liquid with gas medium while machining of Al/SiC MMC. ANOVA is used to identifying significant factors and to correlate relation between input parameters and responses Adaptive – neuro fuzzy system has been used. It is observed that brass wire results to higher cutting velocity in the presence of oxygen gas. From ANOVA, wire tension also important parameter which influences the machining responses. Amalgamation of low pulse on time, high pulse off time, high gap voltage, low discharge current, low wire feed and low wire tension can leads to lower surface roughness. Meena et al. [23] performed the experimental work on Al6063 alloy reinforced with SiC, while wire cut EDM to investigate the effect of process parameters on machining characteristics, revealed that with the increase of wire tension, cutting speed and MRR increased up to some extent and then decreased. Authors concluded with optimum values for maximum MRR and minimum surface roughness. Sanjeev Garg et al. [24] had carried out an experimental investigation on AL/ZrO2 particulate reinforced metal matrix while WEDM machining to analyze the effect of various process parameters on machining responses. Multi-optimized
3
results obtained by initial parameters setting, response surface methodology and grey relational technology have been compared and validated by confirm experiments. Pragya Shandilya et al. [25] described the response of the surface methodology (RSM) and artificial neural networks (ANN) which are based on mathematical modeling for average cutting speed of the SiCp/6061 Al metal matrix composite (MMC) during the operation of the WEDM. To evaluate the model a back propagation neural networks has also developed for process model and concluded that on comparison of ANN and RSM models, ANN provided more accurate value with the average cutting speed. Pragya Shandilya et al. [26] studied the effect of process parameters on kerf in WEDM of Sic particle reinforced Al6061 using RSM. In addition mathematical model was developed. He revealed that for minimization of kerf, input parameters played major role. Satish kumar et al. [27] investigated the effect of wire electrical discharge machining (WEDM) parameters on material removal rate and surface roughness in metal matrix composites consisting of aluminium alloy (Al6063) reinforced with silicon carbide (SiCp with 5%, 10% and 15% volume fractions. The experiments are conceded out as per design of experiments approach with L9, orthogonal array. It is concluded that optimal combinations of process parameters are revealed to achieve higher MRR and lower Ra for Al6063WEDM process parameters and effect of reinforcement was also discussed. Ahmad et al. [28] had proposed a methodology to determine the optimal machining parameters to investigate the machinability of AMC reinforced 5% alumina (Al2O3) using wire-cut electric discharge machining (WEDM). It is concluded that lower value of servo voltage can increase the MRR. Nilesh Patil et al. [29] proposed a semi-empirical model, developed using dimensional analysis and non-linear estimation technique such as quasi-Newton and simplex, for MRR in WEDM based on thermo-physical properties of the work piece and machining parameters. To study the effect of combination of reinforcement, current, pulse on-time, off-time, servo reference voltage etc. are analyzed the use of the Taguchi’s orthogonal array. It is concluded that Predictions of the empirical as well as empirical models agree with the experimental responses and revealed that with the increase percentage of reinforcement causes decreased MRR. Manna and Bhattacharyya [30] focused on the reliable set off parameters that demonstrate versatility and numerous and diverse range by taking aluminiumreinforced silicon carbide metal matrix composite material. Taguchi method is used for experimental design to optimize the CNC-wire cut-EDM parameters. On the basis of the experimental results, the calculated S/N ratio(dB), the analysis of ANOVA, F-test values, confirmation test results, the developed mathematical models, and the verification test of the developed models, concluded that wire tension and wire federate are most important parameters for surface roughness. Gap voltage and gap current are most significant parameters to for controlling gap current. Biing Hwa Yan et al. [31] explored the machinability of the 6061aluminum alloy and the 20 volume fraction Al2O3p/6061 Al composites by WEDM and studied the effects on machining performance including cutting speed, width of slit and surface roughness. It is concluded that increasing volume fraction facilitated wire breakage and revealed the effects of reinforcement on wire breakage, machining responses, craters etc. Z.N. Guo [32] explained how electrical parameters have influence the surface roughness and conducted orthogonal experiment and revealed that low energy will cause the wire breakage; proper pulse interval should be selected. It is concluded that quality machining can be attained when proper parameters are selected.
Please cite this article as: D. Vijay Praveen, D. Ranga Raju and M. V. Jagannadha Raju, Optimization of machining parameters of wire-cut EDM on ceramic particles reinforced Al-metal matrix composites – A review, Materials Today: Proceedings, https://doi.org/10.1016/j.matpr.2019.05.392
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D. Vijay Praveen et al. / Materials Today: Proceedings xxx (xxxx) xxx
T.M. Yue [33] investigated MRR mechanism and surface morphologies in WEDM of alumina particulate reinforced MMCs under two difference cutting conditions (coarse and fine) and revealed that no significant difference occurred in surface roughness but surface topographies were found to be intrinsically different. 5. Conclusion From the literature it may be concluded that Researchers have worked on WEDM but, scanty investigations reported on MMCs. The influence of various reinforcements (eg. metal coated ceramic reinforced MMC, hybrid MMC) on the machining characteristics is need to be analyzed and optimized in the machining of MMCs on WEDM. In most of the research papers, past authors made emphasis on electrical parameters only but non electrical parameters also influences the machining characteristics. The advancements in the development of metal matrix composites demand the viability of WED machining process in the future machining domain. So there is abundant scope for research in the field of machining for latest materials to improve productivity.
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[7] Harmesh Kumar, Alakesh Manna, Rajesh Kumar, Trans. Indian Inst. Met. 71 (1) (2018) 231–244. [8] S. Dinesh Kumar, M. Ravichandran, Silicon (2018) 1–10. [9] A. Dey, V.R. Reddy Bandi, K.M. Pandey, Mater. Today Proc. 5 (1) (2018) 1278– 1285. [10] J. Udaya Prakash, T.V. Moorthy, J. Chem. Pharma. Sci., ISSN 974: 2115. [11] G. Ugrasen, K.G. Mukesh, B.M. Darshan, Sachin Sreenath, Shridhar B. Koladur, H.V. Ravindra, Mater. Today Proc. 5 (1) (2018) 3084–3092. [12] Mohinder Pal Garg, Anand Sharma, Compos. Commun. 6 (2017) 6–10. [13] Das, Shubhajit, M. Chandrasekaran, and S. Samanta, in: Conference Proceedings of the International and 27th All India Manufacturing Technology, Design and Research Conference (AIMTDR-2016) College of Engineering, December, pp. 16–18. 2016. [14] Alokesh Pramanik, A.K. Basak, Mohammad Nazrul Islam, Int. J. Machin. Machinab. Mater. 17 (2) (2015) 139–149. [15] V. Chengal Reddy, N. Deepthi, N. Jayakrishna, Mater. Today Proc. 2 (4-5) (2015) 2548–2554. [16] B. Raju, M. Raja Naga, S. Rajesh Roy, K. Ramji, Int. J. Eng. Trends Technol. (IJETT) 23 (2015). [17] Ravindranadh Bobbili, V. Madhu, A.K. Gogia, Eng. Sci. Technol. Int. J. 18 (4) (2015) 664–668. [18] Ravindranadh Bobbili, V. Madhu, A.K. Gogia, Eng. Sci. Technol. Int. J. 18 (4) (2015) 720–726. [19] Ashish Srivastava, Amit Rai Dixit, Sandeep Tiwari, Int. J. Adv. Res. Innov. 2 (2014) 511–515. [20] Thella Babu Rao, Gopala Krishna, Int. J. Adv. Manuf. Technol. 73 (1–4) (2014) 299–314. [21] G. Selvakumar, G. Sornalatha, S. Sarkar, S. Mitra, Trans. Nonferrous Metals Soc. China 24 (2) (2014) 373–379. [22] Reza Bagherian Azhiri, Reza Teimouri, Mohammadhosein Ghasemi Baboly, Zayd Leseman, Int. J. Adv. Manuf. Technol. 71 (1–4) (2014) 279–295. [23] K.L. Meena, A. Manna, S. Banwait, S. Jaswanti, Eur. J. Eng. Technol. 1 (1) (2013). [24] Sanjeev K.R. Garg, Alakesh Manna, Ajai Jain, J. Eng. Res. 1 (3) (2013) 145–160. [25] Pragya Shandilya, P.K. Jain, N.K. Jain, Proc. Eng. 64 (2013) 767–774. [26] Pragya Shandilya, P.K. Jain, N.K. Jain, Proc. Eng. 38 (2012) 2371–2377. [27] D. Satishkumar, M. Kanthababu, V. Vajjiravelu, R. Anburaj, N. Thirumalai Sundarrajan, H. Arul, Int. J. Adv. Manuf. Technol. 56 (9–12) (2011) 975–986. [28] R.N. Ahmad, M.N. Derman, M. Marzuki, Int. J. Eng. Technol. 10 (2010) 145–150. [29] Nilesh Ganpatrao Patil, P.K. Brahmankar, Int. J. Adv. Manuf. Technol. 51 (5-8) (2010) 599–610. [30] A. Manna, B. Bhattacharyya, Int. J. Adv. Manuf. Technol. 28 (1–2) (2006) 67–75. [31] Biing Hwa Yan, Hsien Chung Tsai, Fuang Yuan Huang, Long Chorng Lee, Int. J. Mach. Tools Manuf. 45 (3) (2005) 251–259. [32] Z.N. Guo, X. Wang, Z.G. Huang, T.M. Yue, J. Mater. Process. Technol. 129 (1–3) (2002) 56–59. [33] T.M. Yue, Y. Dai, W.S. Lau, Mater. Manuf. Process 11 (3) (1996) 341–350.
Please cite this article as: D. Vijay Praveen, D. Ranga Raju and M. V. Jagannadha Raju, Optimization of machining parameters of wire-cut EDM on ceramic particles reinforced Al-metal matrix composites – A review, Materials Today: Proceedings, https://doi.org/10.1016/j.matpr.2019.05.392
Contents lists available at ScienceDirect
Materials Today: Proceedings journal homepage: www.elsevier.com/locate/matpr
Optimization of machining parameters of wire-cut EDM on ceramic particles reinforced Al-metal matrix composites – A review D. Vijay Praveen a,⇑, D. Ranga Raju b, M.V. Jagannadha Raju c a
Department of Mechanical Engineering, Andhra University, Vishakhapatnam, India Department of Mechanical Engineering, Srinivasa Institute of Engineering & Technology, Amalapuram, India c Department of Mechanical Engineering, A.U. College of Engineering (A), Vishakhapatnam, India b
a r t i c l e
i n f o
Article history: Received 29 March 2019 Received in revised form 6 May 2019 Accepted 10 May 2019 Available online xxxx Keywords: Al-MMC Wire-cut EDM Optimization AMMC Taguchi
a b s t r a c t Wire-cut Electrical discharge machining process [WEDM] is used in manufacturing industries to machine conductive and hard materials like metal matrix composites, ceramic composites and super alloys, which are having enormous applications in space craft, defense, transportation vehicles, micro systems, farm machinery etc. Aluminum based ceramic particle reinforced metal matrix materials is one of the key factor in producing composites, which enhances mechanical and thermal properties. These Composites (AlMMCs) owing to having higher strength and stiffness are suitable for variety of engineering applications The current paper reviews the optimization of WEDM machining parameters, responses by deploying different techniques. Ó 2019 Elsevier Ltd. All rights reserved. Selection and peer-review under responsibility of the scientific committee of the International Conference on Recent Advances in Materials, Manufacturing & Energy Systems.
1. Introduction Researchers nowadays are showing interests into advanced materials like ceramic particle reinforced composites, hybrid composites; metal particle coated ceramic reinforced MMCs for the development of advanced components for the present generation. Conventional machining such as turning, milling, drilling etc. shows inefficacious in machining of ceramic reinforced MMCs [1]. Non-uniform distribution of reinforced particles, high hardness, and higher brittleness leads to poor materials removal rate, excessive tool wear and increased surface roughness [2]. Consecutively to attain complex shapes in the composite materials, researchers are focusing on non-conventional machining techniques which can be successfully employed to machine composite materials [3–4] Fig. 1. Non-Conventional Machining processes are classified with the sort of energy used for the machining of the work materials. i.e. (Ultrasonic machining, Water jet machining, Abrasive jet machining, Thermal Electrical discharge machining, Electron beam machining, Laser beam machining, and chemical machining). Most of these non-conventional machining processes are still need to be
analyzed to determine the ‘‘optimal” machining conditions and achieve cost efficient machining in combination with high process reliability and reproducibility [2]. Wire Electrical Discharge Machine (WEDM) is a distinctive promotion of Conventional EDM process, which uses an electrode to initialize the sparking process. WEDM is becoming more important in providing a non-contact machining process, which is suitable for effective machining of MMCs regardless of the hardness and the complexity in contours over the components [4]. WEDM utilizes a incessantly travelling wire electrode made of skinny copper, brass or tungsten of diameter 0.05–0.30 mm, which is capable of achieving very small corner radii, is fed on-to the work piece, that is submerged in a tank of dielectric fluid like deionized water. The wire that is consistently fed from a spool is held between upper and lower diamond guides. The guides are usually CNC-controlled and move within the x–y plane. Filters and deionizing units are used for controlling the resistivity and other electrical properties. The water conjointly helps in flushing away the rubble from the cutting zone. The flushing also helps to determine the feed rates to be given for a variety of thickness of the materials. During the WEDM method, the material is battered ahead of the wire and there’s no direct contact between the work piece and also the wire, eliminating the mechanical stresses during
⇑ Corresponding author. E-mail address: [email protected] (D. Vijay Praveen). https://doi.org/10.1016/j.matpr.2019.05.392 2214-7853/Ó 2019 Elsevier Ltd. All rights reserved. Selection and peer-review under responsibility of the scientific committee of the International Conference on Recent Advances in Materials, Manufacturing & Energy Systems.
Please cite this article as: D. Vijay Praveen, D. Ranga Raju and M. V. Jagannadha Raju, Optimization of machining parameters of wire-cut EDM on ceramic particles reinforced Al-metal matrix composites – A review, Materials Today: Proceedings, https://doi.org/10.1016/j.matpr.2019.05.392
2
D. Vijay Praveen et al. / Materials Today: Proceedings xxx (xxxx) xxx
Fig.1. schematic diagram of wire cut EDM [18].
machining. The following figure shows the schematic diagram of Wire cut EDM experimental setup. 2. WEDM process parameters Input machining process parameters can be broadly classified as electrical parameters and non electrical parameters. Electrical parameters are servo voltage, pulse on time, pulse off time, peak current, Gap voltage etc. Non electrical parameters such as wire material, wire tension, wire feed rate, wire size, dielectric flow rate, dielectric conductivity, work piece material and work piece size. 3. WEDM machining features The following are the characteristics of the WEDM, which must be optimized for economy and better performance. They are Metal Removal rate (MRR), Surface Roughness (Ra) [5,6]. 3.1. Metal removal rate (MRR) MRR can be obtained by the ratio between volume of material removal to time taken for the machining. It highly influences the efficiency of the machining process. It depends upon the parameters which are related with the machining process. Many authors had worked to maximize the material removal rate using different approaches. 3.2. Surface roughness (Ra) The surface roughness (Ra) value of the square block is quantified in lm by using a surface roughness tester SJ-210, which is very important parameter to be minimized. To attain good surface finish, there is need to control the influencing parameters like dielectric medium, material and electrical parameters. Several researchers suggested that to achieve good surface finish electrical discharge current must be controlled. 4. Literature review The following literature describes the research findings carried out by various authors on different types of MMCs, techniques used, their responses, which lead to future research prospects. Harmesh kumar et al. [7] Analyzed the process parameters for surface roughness height and used RSM based Box–Behnken design for experimental investigation and developed quadratic
regression model for surface roughness height (Ra) of SiC reinforced Al metal matrix composite during WEDM. An attempt had been made to optimize the process parameters for surface roughness height (Ra) and also discussed the possible reasons of various surface defects. Kumar Dinesh et al. [8] Investigated the effect of process parameters on the combined objective of maximum Metal Removal Rate (MRR) and minimum Surface Roughness (SR) during machining of AA7178-10 wt% ZrB2 composite using Taguchi based Grey Relational Analysis (GRA) and revealed that peak current and pulse on time are influencing the machining factors. L16 orthogonal array, for the four machining parameters at four levels each, was opted to conduct the experiments. Analysis of variance (ANOVA) was performed to find the validity of the experimental data. Dey et al. [9] analyzed the effects of significant machining parameters on the performance characteristics using Box Behnken of response surface methodology. ANOVA analysis was imposed to investigate the influence of process variables and their interactions and concluded that surface roughness decreases with the increase of pulse on time. Udaya Prakash et al. [10] used S/N analysis for optimizing the WEDM input parameters of 356/B4C composites for better MRR and concluded that gap voltage has highest influence on MRR and also studied the effect of reinforcement. Ugrasen et al. [11] investigated on estimation of machining performances in the WEDM of Al-2024-5%TiC-5% fly ash hybrid metal matrix composite using Multiple Regression Analysis (MRA) and Group Method of Data Handling (GMDH) technique. They concluded that dimensional error can be minimized by low pulse off and low current and maximum MRR can be achieved at high bed speed and high pulse on. Mohinder Pal Garg et al. [12] investigated the dimensional deviation induced by WEDM of zirconium silicate reinforced Al6063 using RSM. Analysis of variance (ANOVA) technique is used to analyze the characteristics and confirmation experiments had also been conducted for verification and concluded that dimensional deviation impacted by large values of pulse on time, peak current. Shubhajit Das et al. [13] used RSM modeling to analyze the influence of process parameters of WEDM process of Al-6061 metal matrix composite (MMC) reinforced with 7%SiC/ 3%B4C hybrid MMCs and the machining characteristics are evaluated using desirability analysis (DA) and suggested that voltage and pulse-on time are more influencing factors on surface roughness. Pramanik et al. [14] investigated the effect of the size of reinforced particles on Al6061alloy with 10% of SiC reinforced MMCs while wire electrical discharge machining in terms of material removal rate (MRR), surface integrity and wear of wire electrodes (WEs).
Please cite this article as: D. Vijay Praveen, D. Ranga Raju and M. V. Jagannadha Raju, Optimization of machining parameters of wire-cut EDM on ceramic particles reinforced Al-metal matrix composites – A review, Materials Today: Proceedings, https://doi.org/10.1016/j.matpr.2019.05.392
D. Vijay Praveen et al. / Materials Today: Proceedings xxx (xxxx) xxx
Chengal Reddy [15] used Taguchi’s grey relational analysis to optimize the process parameters on multiple performance characteristics such as Material removal rate, surface finish. The results showed that the combination of pulse on time, pulse off time, wire tension, lower flush, wire tension and upper flush is essential to achieve maximization of material removal rate and minimization of surface roughness and kerf width. Naga Raju et al. [16] had studied the effect of machining parameters (i.e. pulse on time, pulse off time and peak current) on Al alloy with 5% SiC while WEDM and concluded with optimal machining characteristics. Ravindranadh Bobbili et al. [17] had carried out a comparative study between AL7017 and RHA steel using Buckingham Pi theorem establish the relationship between machine variables and performance measures. Results revealed that wear rate of brass wire increases with increase in input energy leads to wire breakage. He had shown the dependence of thermo physical parameters on the mechanism of MRR and Ra. Ravindranadh Bobbili et al. [18] had performed experimentation on WEDM on ballistic grade aluminum alloy material as per Taguchi technique. He developed mathematical model using RSM and determined the relation between machine variables and performance measures. Ashish Srivastava et al. [19] carried out the experimental study on composite of Al2024/SiC investigate the effects parameters such as current, pulse on time and volume fraction on surface finish and MRR. Response surface methodology technique applied to optimize the machining parameters for minimum surface roughness and maximum MRR. He revealed that surface roughness increases with the increase of reinforcement percentage, pulse on time and MRR increased with increase in peak current and pulse on time. Babu rao et al. [20] investigated machining performance of SiCp reinforced Al7075 during WEDM. Response surface methodology is used to build up the pragmatic models and Analysis of variance (ANOVA) is used to confirm the capability of the developed models. Non-dominated Sorting Genetic Algorithm-II was used to solve the developed problem and the results were validated by experimental tests. Selvakumar et al. [21] optimized the machining parameters of Al 5083 alloy while WEDM. ANOVA test was performed to determine to level of significance of parameters on cutting speed and surface roughness and revealed that cutting speed was independent of wire tension and surface roughness is independent of pulse off time and wire tension. Bagherian Azhiri et al. [22] analyzed experimental dry WEDM process to enhance the machining environment by replacing the liquid with gas medium while machining of Al/SiC MMC. ANOVA is used to identifying significant factors and to correlate relation between input parameters and responses Adaptive – neuro fuzzy system has been used. It is observed that brass wire results to higher cutting velocity in the presence of oxygen gas. From ANOVA, wire tension also important parameter which influences the machining responses. Amalgamation of low pulse on time, high pulse off time, high gap voltage, low discharge current, low wire feed and low wire tension can leads to lower surface roughness. Meena et al. [23] performed the experimental work on Al6063 alloy reinforced with SiC, while wire cut EDM to investigate the effect of process parameters on machining characteristics, revealed that with the increase of wire tension, cutting speed and MRR increased up to some extent and then decreased. Authors concluded with optimum values for maximum MRR and minimum surface roughness. Sanjeev Garg et al. [24] had carried out an experimental investigation on AL/ZrO2 particulate reinforced metal matrix while WEDM machining to analyze the effect of various process parameters on machining responses. Multi-optimized
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results obtained by initial parameters setting, response surface methodology and grey relational technology have been compared and validated by confirm experiments. Pragya Shandilya et al. [25] described the response of the surface methodology (RSM) and artificial neural networks (ANN) which are based on mathematical modeling for average cutting speed of the SiCp/6061 Al metal matrix composite (MMC) during the operation of the WEDM. To evaluate the model a back propagation neural networks has also developed for process model and concluded that on comparison of ANN and RSM models, ANN provided more accurate value with the average cutting speed. Pragya Shandilya et al. [26] studied the effect of process parameters on kerf in WEDM of Sic particle reinforced Al6061 using RSM. In addition mathematical model was developed. He revealed that for minimization of kerf, input parameters played major role. Satish kumar et al. [27] investigated the effect of wire electrical discharge machining (WEDM) parameters on material removal rate and surface roughness in metal matrix composites consisting of aluminium alloy (Al6063) reinforced with silicon carbide (SiCp with 5%, 10% and 15% volume fractions. The experiments are conceded out as per design of experiments approach with L9, orthogonal array. It is concluded that optimal combinations of process parameters are revealed to achieve higher MRR and lower Ra for Al6063WEDM process parameters and effect of reinforcement was also discussed. Ahmad et al. [28] had proposed a methodology to determine the optimal machining parameters to investigate the machinability of AMC reinforced 5% alumina (Al2O3) using wire-cut electric discharge machining (WEDM). It is concluded that lower value of servo voltage can increase the MRR. Nilesh Patil et al. [29] proposed a semi-empirical model, developed using dimensional analysis and non-linear estimation technique such as quasi-Newton and simplex, for MRR in WEDM based on thermo-physical properties of the work piece and machining parameters. To study the effect of combination of reinforcement, current, pulse on-time, off-time, servo reference voltage etc. are analyzed the use of the Taguchi’s orthogonal array. It is concluded that Predictions of the empirical as well as empirical models agree with the experimental responses and revealed that with the increase percentage of reinforcement causes decreased MRR. Manna and Bhattacharyya [30] focused on the reliable set off parameters that demonstrate versatility and numerous and diverse range by taking aluminiumreinforced silicon carbide metal matrix composite material. Taguchi method is used for experimental design to optimize the CNC-wire cut-EDM parameters. On the basis of the experimental results, the calculated S/N ratio(dB), the analysis of ANOVA, F-test values, confirmation test results, the developed mathematical models, and the verification test of the developed models, concluded that wire tension and wire federate are most important parameters for surface roughness. Gap voltage and gap current are most significant parameters to for controlling gap current. Biing Hwa Yan et al. [31] explored the machinability of the 6061aluminum alloy and the 20 volume fraction Al2O3p/6061 Al composites by WEDM and studied the effects on machining performance including cutting speed, width of slit and surface roughness. It is concluded that increasing volume fraction facilitated wire breakage and revealed the effects of reinforcement on wire breakage, machining responses, craters etc. Z.N. Guo [32] explained how electrical parameters have influence the surface roughness and conducted orthogonal experiment and revealed that low energy will cause the wire breakage; proper pulse interval should be selected. It is concluded that quality machining can be attained when proper parameters are selected.
Please cite this article as: D. Vijay Praveen, D. Ranga Raju and M. V. Jagannadha Raju, Optimization of machining parameters of wire-cut EDM on ceramic particles reinforced Al-metal matrix composites – A review, Materials Today: Proceedings, https://doi.org/10.1016/j.matpr.2019.05.392
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D. Vijay Praveen et al. / Materials Today: Proceedings xxx (xxxx) xxx
T.M. Yue [33] investigated MRR mechanism and surface morphologies in WEDM of alumina particulate reinforced MMCs under two difference cutting conditions (coarse and fine) and revealed that no significant difference occurred in surface roughness but surface topographies were found to be intrinsically different. 5. Conclusion From the literature it may be concluded that Researchers have worked on WEDM but, scanty investigations reported on MMCs. The influence of various reinforcements (eg. metal coated ceramic reinforced MMC, hybrid MMC) on the machining characteristics is need to be analyzed and optimized in the machining of MMCs on WEDM. In most of the research papers, past authors made emphasis on electrical parameters only but non electrical parameters also influences the machining characteristics. The advancements in the development of metal matrix composites demand the viability of WED machining process in the future machining domain. So there is abundant scope for research in the field of machining for latest materials to improve productivity.
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Please cite this article as: D. Vijay Praveen, D. Ranga Raju and M. V. Jagannadha Raju, Optimization of machining parameters of wire-cut EDM on ceramic particles reinforced Al-metal matrix composites – A review, Materials Today: Proceedings, https://doi.org/10.1016/j.matpr.2019.05.392