Wire electrical discharge machining (WEDM) is a manufacturing process whereby a desired shape is ... more Wire electrical discharge machining (WEDM) is a manufacturing process whereby a desired shape is obtained using electrical discharges (sparks). WEDM involves high cutting rates and superior quality to improve machining performance in manufacturing hard materials. The machining performance of computer-controlled WEDM is directly dependent on spark energy (pulse on time, peak current, and gap voltage), pulse frequency (pulse off time and pulse on time), and wire electrode parameters (material, wire speed, and wire tension). In the field of wire electrical discharge machining, it is necessary to develop suitable WEDM technology to facilitate the production of high quality workpiece surfaces at high cutting rates. Surface roughness and white layer thickness are the most important factors in evaluating WEDM surface quality. In order to ensure good surface quality, the surface roughness must be low and the white layer must be as thin as possible, homogeneous, crack-free, and well-bonded t...
Surface roughness is a key measure that defines machined surface integrity. In this current work,... more Surface roughness is a key measure that defines machined surface integrity. In this current work, an experimental investigation was conducted to determine the effects of cutting conditions on surface roughness when turning the Al20%Mg Si metal matrix composite and Bi-treated Al20%Mg Si composite. The results showed that surface roughness value improved with cutting speed increment. In addition, Bi treated workpiece showed better surface finish results compared to base composite KeywordSurface roughness, Built up edge, Metal Matrix Composite
Surface roughness is a key measure that defines machined surface integrity. In this current work,... more Surface roughness is a key measure that defines machined surface integrity. In this current work, an experimental investigation was conducted to determine the effects of cutting conditions on surface roughness when turning the Al20%Mg Si metal matrix composite and Bi-treated Al20%Mg Si composite. The results showed that surface roughness value improved with cutting speed increment. In addition, Bi treated workpiece showed better surface finish results compared to base composite KeywordSurface roughness, Built up edge, Metal Matrix Composite
Surface roughness prediction for the end-milling process, which is one of the major cutting proce... more Surface roughness prediction for the end-milling process, which is one of the major cutting processes, is a very important economical consideration in order to increase machine operation and decrease production cost in an automated manufacturing environment. In this study; prediction of surface roughness (Ra) for Brass (60/40) material based on cutting parameters: cutting speed, feed rate, and depth of cut; was studied. Adaptive neuro-fuzzy inference system (ANFIS) was used to predict the surface roughness in the end milling process. Surface roughness was used as dependant variable while cutting speed of range (750 - 1750rpm), feed rate of range (50 - 250mm/min) and depth of cut of range (0.3 - 0.7mm) were used as predictor variables. Normal and feed forces were used as predictor variables to verify the ANFIS model. Different membership functions were adopted during the training process of ANFIS. Surface roughness was measured in an off line manner using stylus based profile-meter (surtronic 3+). The normal and feed forces were measured in an on-line manner using two components dynamometer. The effects of cutting parameters on the normal force, feed force and surface roughness were discussed. Experimental test data were used to examine the ANFIS model by defining the reliability and percentage error of the model. Experimental results demonstrate the effectiveness of the proposed model. While the predicted surface roughness was compared with measured data; the mean square error has been found equal to 8.5 % hence the achieved accuracy is equal to 91.5 %. Although this work focuses on prediction of surface roughness for end-milling operation, the concepts introduced are general; ie., prediction of surface roughness using ANFIS can be applied to many other cutting and machining processes.
ABSTRACT– Multiple regression and adaptive neuro-fuzzy in ference system (ANFIS) were used to pre... more ABSTRACT– Multiple regression and adaptive neuro-fuzzy in ference system (ANFIS) were used to predict the surface roughness in the end milling process. Spindle speed, feed rate and depth of cut were used as predictor variables. Generalized bell me mberships function (gbellmf) was adopted during the training process of ANFIS in this study. The pr edicted surface roughness using multiple regression and ANFIS were compared with measured data, the ac hieved accuracy were 91.9% and 94% respectively. These results indicate that the tr aining of ANFIS with the gbellmf is accurate than multiple regression in the prediction of surface roughness.
Wire Electric Discharge Machining (WEDM) is a nontraditional technique by which the required prof... more Wire Electric Discharge Machining (WEDM) is a nontraditional technique by which the required profile is acquired using spark energy. Regarding wire cutting, precision machining is necessary to achieve high product quality. White Layer Thickness (WLT) is one of the most important factors for assessing superior surface finish. In this research, Adaptive Neuro-fuzzy Inference System (ANFIS) was used to predict the WLT in WEDM using coated wire electrode. The predicted data were compared with measured values, and the average prediction error for WLT was 2.61 %.
Electrical discharge machining (EDM) is a non-conventional machining technique that is well-known... more Electrical discharge machining (EDM) is a non-conventional machining technique that is well-known for use in fabricating dies and molds owing to machinability of high hardness materials. Although the electro-thermal mechanism of EDM offers many advantages over other available machining methods, its sluggish nature limits the wide application of such machines for mass production. In this research, adding graphite powder to dielectric is proposed to improve EDM performance factors. Material removal rate (MRR) and average surface roughness (Ra) have been monitored and evaluated after addition of graphite powder to dielectric in electrical discharge milling and sinking. It is found that the presence of powder particles in dielectric fluid enhances the MRR steadily up to ~11 and ~17% for milling and sinking process, respectively. Moreover, the highest enhancement if Ra is ~31% at 1g/l graphite powder concentration for electrical discharge milling and up to ~11% for sinking process. Field...
In this research, the effect of water-silica slurry impacts on polylactic acid (PLA) processed by... more In this research, the effect of water-silica slurry impacts on polylactic acid (PLA) processed by fused deposition modeling (FDM) is examined under different conditions with the assistance of an adaptive neuro-fuzzy interference system (ANFIS). Building orientation, layer thickness, and slurry impact angle are considered as the controllable variables. Weight gain resulting from water, net weight gain, and total weight gain are the predicting variables. Results uncover the accomplishment of the ANFIS model to appropriately appraise slurry erosion in correlation with comparing real data. Both experimental and ANFIS results are almost identical with average percentage error less than 5.45 × 10−6. We observed during the slurry impacts tests that all specimens showed an increase in their weights. This weight gain was finally interpreted to the synergetic effect of water absorption and the solid particles fragmentations immersed within the specimens due to the successive slurry impacts.
Wire electrical discharge machining (WEDM) is one of the most important nontraditional machining ... more Wire electrical discharge machining (WEDM) is one of the most important nontraditional machining process that is well-known for cutting difficult to machine materials. The wire electrode along with machining parameters control the WEDM process. This research work focuses on optimizing WEDM parameters using Taguchi technique to minimize wire rupture. Experiments have been done using the L18 orthogonal array. Each experiment is repeated three times to ensure accurate readings of the wire rupture. The statistical methods of signal to noise ratio (S/N ratio) is applied to study effects of peak current, pulse width, charging time, wire speed, and wire tension on wire rupture. As a results, the peak current, pulse width, and wire tension have the most significant effect on wire rupture followed by charging time and wire speed. The developed analysis can be used in the metal cutting field to identify the optimum machining parameters for less wire rupture.
The International Journal of Advanced Manufacturing Technology
Wire electrical discharge machining (WEDM) is a manufacturing process whereby a desired shape is ... more Wire electrical discharge machining (WEDM) is a manufacturing process whereby a desired shape is obtained using electrical discharges (sparks). WEDM demands high cutting rate and high quality to improve machining performance for manufacturing hard materials. The machining performance of computer-controlled WEDM is directly dependent on spark energy and pulse frequency parameters including discharge voltage, peak current, pulse duration, and charging time. In this paper, a new performance index to measure the effects of spark energy and pulse frequency on machining performance is proposed. Moreover, the effects of electric process parameters on performance measures including cutting speed, surface roughness, and white layer thickness are introduced.
Wire cutting electrical discharge machining (WEDM) is a non-traditional technique by which the re... more Wire cutting electrical discharge machining (WEDM) is a non-traditional technique by which the required profile is acquired using spark energy. Concerning wire cutting, precision machining is necessary to achieve high product quality. White layer thickness (WLT) is one of the most important factors for evaluating surface quality. Furthermore, WLT is among the most critical constraints in cutting parameters selection in WEDM. In this research, the adaptive neuro-fuzzy inference system (ANFIS) was used to predict the WLT in WEDM using a coated wire electrode. Experimental runs were conducted to validate the ANFIS model. The predicted data were compared with measured values, and the average prediction error for WLT was 2.61%. Based on the ANFIS model, minimum WLT is achieved at the lowest levels of peak current and pulse on-time with high level of pulse off-time.
Reference Module in Materials Science and Materials Engineering, 2016
One of the major requirements of wire electrical discharge machining (WEDM) is to develop suitabl... more One of the major requirements of wire electrical discharge machining (WEDM) is to develop suitable technology for producing smooth surfaces. The main characteristic of WEDM is the development of the white layer. To ensure good surface quality, the white layer thickness (WLT) must be as thin as possible, homogeneous, and crack-free. Spark energy and wire electrode type are the most important parameters to experimentally investigate WLT. Experimental results show that the WLT increases linearly by 3 and 2 µm for every 20-µJ increase in the spark energy while using brass and coated wire, respectively.
Reference Module in Materials Science and Materials Engineering, 2016
Electrical discharge machining (EDM) is a powerful, nonconventional machining technique with the ... more Electrical discharge machining (EDM) is a powerful, nonconventional machining technique with the ability to machine any conductive material regardless of mechanical property. However, the sluggish nature of EDM stands out when the target is in mass production in industrial plants. Poor surface quality, residual stress, and heat-affected zone are among other disadvantages of this technique. Researchers have proposed several solutions to enhance EDM capabilities by utilizing more innovative materials or methods. With emphasis on EDM development aspects, this chapter provides a detailed review of accessible research accompanied by clear categories to build a clear mapping for further research on EDM.
Wire electrical discharge machining (WEDM) is a manufacturing process whereby a desired shape is ... more Wire electrical discharge machining (WEDM) is a manufacturing process whereby a desired shape is obtained using electrical discharges (sparks). WEDM involves high cutting rates and superior quality to improve machining performance in manufacturing hard materials. The machining performance of computer-controlled WEDM is directly dependent on spark energy (pulse on time, peak current, and gap voltage), pulse frequency (pulse off time and pulse on time), and wire electrode parameters (material, wire speed, and wire tension). In the field of wire electrical discharge machining, it is necessary to develop suitable WEDM technology to facilitate the production of high quality workpiece surfaces at high cutting rates. Surface roughness and white layer thickness are the most important factors in evaluating WEDM surface quality. In order to ensure good surface quality, the surface roughness must be low and the white layer must be as thin as possible, homogeneous, crack-free, and well-bonded t...
Surface roughness is a key measure that defines machined surface integrity. In this current work,... more Surface roughness is a key measure that defines machined surface integrity. In this current work, an experimental investigation was conducted to determine the effects of cutting conditions on surface roughness when turning the Al20%Mg Si metal matrix composite and Bi-treated Al20%Mg Si composite. The results showed that surface roughness value improved with cutting speed increment. In addition, Bi treated workpiece showed better surface finish results compared to base composite KeywordSurface roughness, Built up edge, Metal Matrix Composite
Surface roughness is a key measure that defines machined surface integrity. In this current work,... more Surface roughness is a key measure that defines machined surface integrity. In this current work, an experimental investigation was conducted to determine the effects of cutting conditions on surface roughness when turning the Al20%Mg Si metal matrix composite and Bi-treated Al20%Mg Si composite. The results showed that surface roughness value improved with cutting speed increment. In addition, Bi treated workpiece showed better surface finish results compared to base composite KeywordSurface roughness, Built up edge, Metal Matrix Composite
Surface roughness prediction for the end-milling process, which is one of the major cutting proce... more Surface roughness prediction for the end-milling process, which is one of the major cutting processes, is a very important economical consideration in order to increase machine operation and decrease production cost in an automated manufacturing environment. In this study; prediction of surface roughness (Ra) for Brass (60/40) material based on cutting parameters: cutting speed, feed rate, and depth of cut; was studied. Adaptive neuro-fuzzy inference system (ANFIS) was used to predict the surface roughness in the end milling process. Surface roughness was used as dependant variable while cutting speed of range (750 - 1750rpm), feed rate of range (50 - 250mm/min) and depth of cut of range (0.3 - 0.7mm) were used as predictor variables. Normal and feed forces were used as predictor variables to verify the ANFIS model. Different membership functions were adopted during the training process of ANFIS. Surface roughness was measured in an off line manner using stylus based profile-meter (surtronic 3+). The normal and feed forces were measured in an on-line manner using two components dynamometer. The effects of cutting parameters on the normal force, feed force and surface roughness were discussed. Experimental test data were used to examine the ANFIS model by defining the reliability and percentage error of the model. Experimental results demonstrate the effectiveness of the proposed model. While the predicted surface roughness was compared with measured data; the mean square error has been found equal to 8.5 % hence the achieved accuracy is equal to 91.5 %. Although this work focuses on prediction of surface roughness for end-milling operation, the concepts introduced are general; ie., prediction of surface roughness using ANFIS can be applied to many other cutting and machining processes.
ABSTRACT– Multiple regression and adaptive neuro-fuzzy in ference system (ANFIS) were used to pre... more ABSTRACT– Multiple regression and adaptive neuro-fuzzy in ference system (ANFIS) were used to predict the surface roughness in the end milling process. Spindle speed, feed rate and depth of cut were used as predictor variables. Generalized bell me mberships function (gbellmf) was adopted during the training process of ANFIS in this study. The pr edicted surface roughness using multiple regression and ANFIS were compared with measured data, the ac hieved accuracy were 91.9% and 94% respectively. These results indicate that the tr aining of ANFIS with the gbellmf is accurate than multiple regression in the prediction of surface roughness.
Wire Electric Discharge Machining (WEDM) is a nontraditional technique by which the required prof... more Wire Electric Discharge Machining (WEDM) is a nontraditional technique by which the required profile is acquired using spark energy. Regarding wire cutting, precision machining is necessary to achieve high product quality. White Layer Thickness (WLT) is one of the most important factors for assessing superior surface finish. In this research, Adaptive Neuro-fuzzy Inference System (ANFIS) was used to predict the WLT in WEDM using coated wire electrode. The predicted data were compared with measured values, and the average prediction error for WLT was 2.61 %.
Electrical discharge machining (EDM) is a non-conventional machining technique that is well-known... more Electrical discharge machining (EDM) is a non-conventional machining technique that is well-known for use in fabricating dies and molds owing to machinability of high hardness materials. Although the electro-thermal mechanism of EDM offers many advantages over other available machining methods, its sluggish nature limits the wide application of such machines for mass production. In this research, adding graphite powder to dielectric is proposed to improve EDM performance factors. Material removal rate (MRR) and average surface roughness (Ra) have been monitored and evaluated after addition of graphite powder to dielectric in electrical discharge milling and sinking. It is found that the presence of powder particles in dielectric fluid enhances the MRR steadily up to ~11 and ~17% for milling and sinking process, respectively. Moreover, the highest enhancement if Ra is ~31% at 1g/l graphite powder concentration for electrical discharge milling and up to ~11% for sinking process. Field...
In this research, the effect of water-silica slurry impacts on polylactic acid (PLA) processed by... more In this research, the effect of water-silica slurry impacts on polylactic acid (PLA) processed by fused deposition modeling (FDM) is examined under different conditions with the assistance of an adaptive neuro-fuzzy interference system (ANFIS). Building orientation, layer thickness, and slurry impact angle are considered as the controllable variables. Weight gain resulting from water, net weight gain, and total weight gain are the predicting variables. Results uncover the accomplishment of the ANFIS model to appropriately appraise slurry erosion in correlation with comparing real data. Both experimental and ANFIS results are almost identical with average percentage error less than 5.45 × 10−6. We observed during the slurry impacts tests that all specimens showed an increase in their weights. This weight gain was finally interpreted to the synergetic effect of water absorption and the solid particles fragmentations immersed within the specimens due to the successive slurry impacts.
Wire electrical discharge machining (WEDM) is one of the most important nontraditional machining ... more Wire electrical discharge machining (WEDM) is one of the most important nontraditional machining process that is well-known for cutting difficult to machine materials. The wire electrode along with machining parameters control the WEDM process. This research work focuses on optimizing WEDM parameters using Taguchi technique to minimize wire rupture. Experiments have been done using the L18 orthogonal array. Each experiment is repeated three times to ensure accurate readings of the wire rupture. The statistical methods of signal to noise ratio (S/N ratio) is applied to study effects of peak current, pulse width, charging time, wire speed, and wire tension on wire rupture. As a results, the peak current, pulse width, and wire tension have the most significant effect on wire rupture followed by charging time and wire speed. The developed analysis can be used in the metal cutting field to identify the optimum machining parameters for less wire rupture.
The International Journal of Advanced Manufacturing Technology
Wire electrical discharge machining (WEDM) is a manufacturing process whereby a desired shape is ... more Wire electrical discharge machining (WEDM) is a manufacturing process whereby a desired shape is obtained using electrical discharges (sparks). WEDM demands high cutting rate and high quality to improve machining performance for manufacturing hard materials. The machining performance of computer-controlled WEDM is directly dependent on spark energy and pulse frequency parameters including discharge voltage, peak current, pulse duration, and charging time. In this paper, a new performance index to measure the effects of spark energy and pulse frequency on machining performance is proposed. Moreover, the effects of electric process parameters on performance measures including cutting speed, surface roughness, and white layer thickness are introduced.
Wire cutting electrical discharge machining (WEDM) is a non-traditional technique by which the re... more Wire cutting electrical discharge machining (WEDM) is a non-traditional technique by which the required profile is acquired using spark energy. Concerning wire cutting, precision machining is necessary to achieve high product quality. White layer thickness (WLT) is one of the most important factors for evaluating surface quality. Furthermore, WLT is among the most critical constraints in cutting parameters selection in WEDM. In this research, the adaptive neuro-fuzzy inference system (ANFIS) was used to predict the WLT in WEDM using a coated wire electrode. Experimental runs were conducted to validate the ANFIS model. The predicted data were compared with measured values, and the average prediction error for WLT was 2.61%. Based on the ANFIS model, minimum WLT is achieved at the lowest levels of peak current and pulse on-time with high level of pulse off-time.
Reference Module in Materials Science and Materials Engineering, 2016
One of the major requirements of wire electrical discharge machining (WEDM) is to develop suitabl... more One of the major requirements of wire electrical discharge machining (WEDM) is to develop suitable technology for producing smooth surfaces. The main characteristic of WEDM is the development of the white layer. To ensure good surface quality, the white layer thickness (WLT) must be as thin as possible, homogeneous, and crack-free. Spark energy and wire electrode type are the most important parameters to experimentally investigate WLT. Experimental results show that the WLT increases linearly by 3 and 2 µm for every 20-µJ increase in the spark energy while using brass and coated wire, respectively.
Reference Module in Materials Science and Materials Engineering, 2016
Electrical discharge machining (EDM) is a powerful, nonconventional machining technique with the ... more Electrical discharge machining (EDM) is a powerful, nonconventional machining technique with the ability to machine any conductive material regardless of mechanical property. However, the sluggish nature of EDM stands out when the target is in mass production in industrial plants. Poor surface quality, residual stress, and heat-affected zone are among other disadvantages of this technique. Researchers have proposed several solutions to enhance EDM capabilities by utilizing more innovative materials or methods. With emphasis on EDM development aspects, this chapter provides a detailed review of accessible research accompanied by clear categories to build a clear mapping for further research on EDM.
Wire electrical discharge machining (WEDM) is a manufacturing process whereby a
desired shape is ... more Wire electrical discharge machining (WEDM) is a manufacturing process whereby a desired shape is obtained using electrical discharges (sparks). WEDM involves high cutting rates and superior quality to improve machining performance in manufacturing hard materials. The machining performance of computer-controlled WEDM is directly dependent on spark energy (pulse on time, peak current, and gap voltage), pulse frequency (pulse off time and pulse on time), and wire electrode parameters (material, wire speed, and wire tension). In the field of wire electrical discharge machining, it is necessary to develop suitable WEDM technology to facilitate the production of high quality workpiece surfaces at high cutting rates. Surface roughness and white layer thickness are the most important factors in evaluating WEDM surface quality. In order to ensure good surface quality, the surface roughness must be low and the white layer must be as thin as possible, homogeneous, crack-free, and well-bonded to the substrate material. In this study, the effect of cutting parameters is investigated on the machining performance parameters including cutting speed, surface roughness, wire rupture, and white layer thickness. The adaptive Neuro-Fuzzy Inference System (ANFIS) along with the Taguchi method is applied to determine the effects of the significant parameters on WEDM performance. Moreover, a new performance index is proposed to identify the effects of spark energy and pulse frequency simultaneously on machining performance and to identify the wire rupture limit. However, the performance index cannot be used to identify the most feasible wire electrode from ecological (energy and wire consumption) and economic (machining costs) perspectives. Therefore, a new performance criterion (production economic index) is developed to select the most feasible wire electrode considering the economic and ecological aspects along with the performance index to achieve superior machining performance at the lowest cost. This can be done by dividing the performance index by the total machining cost ((Es×DF)/Ct). In addition, a new coated-wire electrodeiv design with higher strength for less wire rupture and high machining performance in WEDM is proposed. The results obtained represent a technological knowledge base for the selection of optimal machining conditions along with suitable types of wire electrodes for WEDM in terms of ecological and economic aspects. By applying the proposed performance criterion (Es×DF/Ct), it appears that using lower spark and higher pulse cycle settings with a brass wire electrode can decrease the surface roughness and white layer thickness, and facilitate more economical cutting speed. This could lead to faster cutting with good surface finish and less wire rupture.
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Papers by Ibrahem Maher
desired shape is obtained using electrical discharges (sparks). WEDM involves high
cutting rates and superior quality to improve machining performance in manufacturing
hard materials. The machining performance of computer-controlled WEDM is directly
dependent on spark energy (pulse on time, peak current, and gap voltage), pulse frequency
(pulse off time and pulse on time), and wire electrode parameters (material, wire speed,
and wire tension). In the field of wire electrical discharge machining, it is necessary to
develop suitable WEDM technology to facilitate the production of high quality workpiece
surfaces at high cutting rates. Surface roughness and white layer thickness are the most
important factors in evaluating WEDM surface quality. In order to ensure good surface
quality, the surface roughness must be low and the white layer must be as thin as possible,
homogeneous, crack-free, and well-bonded to the substrate material. In this study, the
effect of cutting parameters is investigated on the machining performance parameters
including cutting speed, surface roughness, wire rupture, and white layer thickness. The
adaptive Neuro-Fuzzy Inference System (ANFIS) along with the Taguchi method is
applied to determine the effects of the significant parameters on WEDM performance.
Moreover, a new performance index is proposed to identify the effects of spark energy
and pulse frequency simultaneously on machining performance and to identify the wire
rupture limit. However, the performance index cannot be used to identify the most
feasible wire electrode from ecological (energy and wire consumption) and economic
(machining costs) perspectives. Therefore, a new performance criterion (production
economic index) is developed to select the most feasible wire electrode considering the
economic and ecological aspects along with the performance index to achieve superior
machining performance at the lowest cost. This can be done by dividing the performance
index by the total machining cost ((Es×DF)/Ct). In addition, a new coated-wire electrodeiv
design with higher strength for less wire rupture and high machining performance in
WEDM is proposed. The results obtained represent a technological knowledge base for
the selection of optimal machining conditions along with suitable types of wire electrodes
for WEDM in terms of ecological and economic aspects. By applying the proposed
performance criterion (Es×DF/Ct), it appears that using lower spark and higher pulse
cycle settings with a brass wire electrode can decrease the surface roughness and white
layer thickness, and facilitate more economical cutting speed. This could lead to faster
cutting with good surface finish and less wire rupture.