Magnesium alloy is highly potential material for biodegradable implant application. Due to limita... more Magnesium alloy is highly potential material for biodegradable implant application. Due to limitations in conventional machining methods, non-traditional machining method such as electrical discharge machining (EDM) die sinking process is proposed to produce intricate shape with tight tolerance on magnesium alloy. Nine EDM experiments with three levels and four parameters were conducted using Taguchi method on AZ31 magnesium alloy to explore the optimum machining parameters. It was found that pulse on-time was the most significant parameter affecting the surface roughness (Ra) of the machined surface. The optimum EDM condition obtained was 47 A peak current, 80 V voltage, 16 μs pulse on-time and 512 μs pulse off-time. A confirmation test was conducted and the result shows 95.5% similarity with the predicted Ra. However, the formation of cracks and craters were found on the machined surface area. It is proposed to solve this problem by applying powder mixed EDM method in future research work.
Friction stir welding (FSW) process is a solid state joining process in which a non-consumable to... more Friction stir welding (FSW) process is a solid state joining process in which a non-consumable tool is used to generate frictional heat in the abutting surfaces. The welding parameter such as welding speed, tool rotational speed, and tool profile plays a major role in deciding the weld joint strength. In this investigation, effect of welding parameters and tool pin profile on Mechanical properties in AA6061 aluminium alloy was studied. Friction stir welding of aluminium alloy plates with a thickness of 6 mm are used to perform Friction Stir Weld joints. Tapered cylindrical, and square pin profiles have been used to fabricate the joints at three different rotational speeds i.e. 1500, 2000 and 2500 rpm with two traverse speeds of 20 and 40 mm/min. The mechanical properties (tensile strength, hardness) of the joints have been evaluated and analysed. It has been observed that the design of tool pin profile has considerable effect on tensile properties. Square pin profile tool produces the best tensile properties compared to tapered cylindrical tool pin profiles.
This research was conducted to investigate the effect of nano aluminum mixed with electrical disc... more This research was conducted to investigate the effect of nano aluminum mixed with electrical discharge machining dielectric on surface roughness (Ra), corrosion rate and material removal rate (MRR) of titanium alloy. Conventional machining of titanium alloy is a challenge even when using non-conventional machining processes such as electrical discharge machining (EDM). Among the limitations of EDM are machined surface alteration, induced corrosion, low material removal rate and residual stress during the EDM process. A newly developed and improved EDM process known as powder mixed electrical discharge machining (PMEDM) is envisaged able to address some of the above mentioned problems. In this study, PMEDM machining performance on titanium alloy workpiece using nano aluminum powder is assessed to investigate its improvement for biomedical application. Machining process parameters such as peak-current, ON-time, gap voltage and nano aluminum concentration are varied when machining biomedical grade titanium alloy. PMEDM although still is its infancy has shown slight improvement in Ra, corrosion rate and material removal rate. MRR is improved about more than 33.33% due to effect of nano aluminum concentration.
This paper presents the development of a back propagation neural network model for the
prediction... more This paper presents the development of a back propagation neural network model for the prediction of weld bead geometry in pulsed gas metal arc welding process. The model is based on experimental data. The thickness of the plate, pulse frequency, wire feed rate, wire feed rate/travel speed ratio, and peak current have been considered as the input parameters and the bead penetration depth and the convexity index of the bead as output parameters to develop the model. The developed model is then compared with experimental results and it is found that the results obtained from neural network model are accurate in predicting the weld bead geometry.
Abstract Pulsed gas metal arc welding is one of the most
widely used processes in the industry. I... more Abstract Pulsed gas metal arc welding is one of the most widely used processes in the industry. It offers spray metal transfer at low average currents, high metal deposition rate, versatility, less distortion, and the ability to be used in automated robotic welding systems. The weld bead plays an important role in determining the mechanical properties of the weld. Its geometric parameters, viz., width, reinforcement height, and penetration, are decided according to the welding process parameters, such as wire feed rate, welding speed, pulse current magnitude, frequency (cycle time), etc. Therefore, to produce good weld bead geometry, it is important to set the proper welding process parameters. In the present paper, mathematical models that correlate welding process parameters to weld bead geometry are developed with experimental investigation. Taguchi methods are applied to plan the experiments. Five process parameters, viz., wire feed rate, plate thickness, pulse frequency, pulse current magnitude, and travel speed, are selected to develop the models using multiple regression analysis. The models developed were checked for their adequacy. Results of confirmation experiments show that the models can predict the bead geometry
Magnesium alloy is highly potential material for biodegradable implant application. Due to limita... more Magnesium alloy is highly potential material for biodegradable implant application. Due to limitations in conventional machining methods, non-traditional machining method such as electrical discharge machining (EDM) die sinking process is proposed to produce intricate shape with tight tolerance on magnesium alloy. Nine EDM experiments with three levels and four parameters were conducted using Taguchi method on AZ31 magnesium alloy to explore the optimum machining parameters. It was found that pulse on-time was the most significant parameter affecting the surface roughness (Ra) of the machined surface. The optimum EDM condition obtained was 47 A peak current, 80 V voltage, 16 μs pulse on-time and 512 μs pulse off-time. A confirmation test was conducted and the result shows 95.5% similarity with the predicted Ra. However, the formation of cracks and craters were found on the machined surface area. It is proposed to solve this problem by applying powder mixed EDM method in future research work.
Friction stir welding (FSW) process is a solid state joining process in which a non-consumable to... more Friction stir welding (FSW) process is a solid state joining process in which a non-consumable tool is used to generate frictional heat in the abutting surfaces. The welding parameter such as welding speed, tool rotational speed, and tool profile plays a major role in deciding the weld joint strength. In this investigation, effect of welding parameters and tool pin profile on Mechanical properties in AA6061 aluminium alloy was studied. Friction stir welding of aluminium alloy plates with a thickness of 6 mm are used to perform Friction Stir Weld joints. Tapered cylindrical, and square pin profiles have been used to fabricate the joints at three different rotational speeds i.e. 1500, 2000 and 2500 rpm with two traverse speeds of 20 and 40 mm/min. The mechanical properties (tensile strength, hardness) of the joints have been evaluated and analysed. It has been observed that the design of tool pin profile has considerable effect on tensile properties. Square pin profile tool produces the best tensile properties compared to tapered cylindrical tool pin profiles.
This research was conducted to investigate the effect of nano aluminum mixed with electrical disc... more This research was conducted to investigate the effect of nano aluminum mixed with electrical discharge machining dielectric on surface roughness (Ra), corrosion rate and material removal rate (MRR) of titanium alloy. Conventional machining of titanium alloy is a challenge even when using non-conventional machining processes such as electrical discharge machining (EDM). Among the limitations of EDM are machined surface alteration, induced corrosion, low material removal rate and residual stress during the EDM process. A newly developed and improved EDM process known as powder mixed electrical discharge machining (PMEDM) is envisaged able to address some of the above mentioned problems. In this study, PMEDM machining performance on titanium alloy workpiece using nano aluminum powder is assessed to investigate its improvement for biomedical application. Machining process parameters such as peak-current, ON-time, gap voltage and nano aluminum concentration are varied when machining biomedical grade titanium alloy. PMEDM although still is its infancy has shown slight improvement in Ra, corrosion rate and material removal rate. MRR is improved about more than 33.33% due to effect of nano aluminum concentration.
This paper presents the development of a back propagation neural network model for the
prediction... more This paper presents the development of a back propagation neural network model for the prediction of weld bead geometry in pulsed gas metal arc welding process. The model is based on experimental data. The thickness of the plate, pulse frequency, wire feed rate, wire feed rate/travel speed ratio, and peak current have been considered as the input parameters and the bead penetration depth and the convexity index of the bead as output parameters to develop the model. The developed model is then compared with experimental results and it is found that the results obtained from neural network model are accurate in predicting the weld bead geometry.
Abstract Pulsed gas metal arc welding is one of the most
widely used processes in the industry. I... more Abstract Pulsed gas metal arc welding is one of the most widely used processes in the industry. It offers spray metal transfer at low average currents, high metal deposition rate, versatility, less distortion, and the ability to be used in automated robotic welding systems. The weld bead plays an important role in determining the mechanical properties of the weld. Its geometric parameters, viz., width, reinforcement height, and penetration, are decided according to the welding process parameters, such as wire feed rate, welding speed, pulse current magnitude, frequency (cycle time), etc. Therefore, to produce good weld bead geometry, it is important to set the proper welding process parameters. In the present paper, mathematical models that correlate welding process parameters to weld bead geometry are developed with experimental investigation. Taguchi methods are applied to plan the experiments. Five process parameters, viz., wire feed rate, plate thickness, pulse frequency, pulse current magnitude, and travel speed, are selected to develop the models using multiple regression analysis. The models developed were checked for their adequacy. Results of confirmation experiments show that the models can predict the bead geometry
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prediction of weld bead geometry in pulsed gas metal arc welding process. The model is
based on experimental data. The thickness of the plate, pulse frequency, wire feed rate, wire
feed rate/travel speed ratio, and peak current have been considered as the input parameters
and the bead penetration depth and the convexity index of the bead as output parameters to
develop the model. The developed model is then compared with experimental results and it is found that the results obtained from neural network model are accurate in predicting
the weld bead geometry.
widely used processes in the industry. It offers spray metal
transfer at low average currents, high metal deposition
rate, versatility, less distortion, and the ability to be used
in automated robotic welding systems. The weld bead
plays an important role in determining the mechanical
properties of the weld. Its geometric parameters, viz.,
width, reinforcement height, and penetration, are decided
according to the welding process parameters, such as wire
feed rate, welding speed, pulse current magnitude,
frequency (cycle time), etc. Therefore, to produce good
weld bead geometry, it is important to set the proper
welding process parameters. In the present paper, mathematical
models that correlate welding process parameters
to weld bead geometry are developed with experimental
investigation. Taguchi methods are applied to plan the
experiments. Five process parameters, viz., wire feed rate,
plate thickness, pulse frequency, pulse current magnitude,
and travel speed, are selected to develop the models using
multiple regression analysis. The models developed were
checked for their adequacy. Results of confirmation
experiments show that the models can predict the bead geometry
prediction of weld bead geometry in pulsed gas metal arc welding process. The model is
based on experimental data. The thickness of the plate, pulse frequency, wire feed rate, wire
feed rate/travel speed ratio, and peak current have been considered as the input parameters
and the bead penetration depth and the convexity index of the bead as output parameters to
develop the model. The developed model is then compared with experimental results and it is found that the results obtained from neural network model are accurate in predicting
the weld bead geometry.
widely used processes in the industry. It offers spray metal
transfer at low average currents, high metal deposition
rate, versatility, less distortion, and the ability to be used
in automated robotic welding systems. The weld bead
plays an important role in determining the mechanical
properties of the weld. Its geometric parameters, viz.,
width, reinforcement height, and penetration, are decided
according to the welding process parameters, such as wire
feed rate, welding speed, pulse current magnitude,
frequency (cycle time), etc. Therefore, to produce good
weld bead geometry, it is important to set the proper
welding process parameters. In the present paper, mathematical
models that correlate welding process parameters
to weld bead geometry are developed with experimental
investigation. Taguchi methods are applied to plan the
experiments. Five process parameters, viz., wire feed rate,
plate thickness, pulse frequency, pulse current magnitude,
and travel speed, are selected to develop the models using
multiple regression analysis. The models developed were
checked for their adequacy. Results of confirmation
experiments show that the models can predict the bead geometry