An investigation of material removal rate and kerf on WEDM through grey relational analysis

Pujara, Jay; Kothari, Kartik D.; Gohil, Ashish V.

doi:10.15282/jmes.12.2.2018.10.0322

Cited by 16 publications

(9 citation statements)

References 3 publications

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“…Responses need to be normalized before they are analyzed with GRA [18]. The sequence can be normalized as in (1) for the smaller the better.…”

Section: Data Pre-processingmentioning

confidence: 99%

Determination of Optimum Working Parameters for Multiple Response Characteristics of Worm Gear Box

Chothani*¹,

Maniya²

2019

IJRTE

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The reason for this task is to optimize the multiple response of single start worm gear using three working parameters to improve its performance. As the input torque and lubricant heating time are the most effective responses of worm gear box to reduce the no-load dependent losses, they are taken as the response parameters in this research. Taguchi Grey Relational Analysis (GRA) is the method used to determine the influence of type of lubricant, volume of lubricant and speed of worm gear on multiple responses (input torque & lubricant heating time) of worm gear. The specific test rig is developed based on direct torque measurement technique to measure the input torque and lubricant heating time of worm gear box. Experimental results have shown that the input torque and lubricant heating time can be improved effectively through Taguchi-Grey Relational Analysis. The result is validated using the Confirmation Test. ANOVA determines the important of parameters. It has been found that the type of lubricant and speed of worm gear are influential parameters for worm gear performance. By selecting these parameters, efficiency of the worm gearbox can be increased.

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“…Responses need to be normalized before they are analyzed with GRA [18]. The sequence can be normalized as in (1) for the smaller the better.…”

Section: Data Pre-processingmentioning

confidence: 99%

Determination of Optimum Working Parameters for Multiple Response Characteristics of Worm Gear Box

Chothani*¹,

Maniya²

2019

IJRTE

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“…The multiple regression coefficients (R 2 ) of all the equations are found to be above 85% suggesting the adequacy of the model above 85%. These equations can be used to find out the values of the performance characteristics at the specified operating conditions [14,16]. The regression equations for the various response characteristics are as follows:…”

Section: Development Of Regression Equationsmentioning

confidence: 99%

“…PCA based Gray relational analysis was used for multi-feature optimization. Pujara et al [14] carried out WEDM of Al-SiC composite. They investigated the influence of wire feed, pulse on time, peak current and pulse off time on kerf width and MRR.…”

Section: Introductionmentioning

confidence: 99%

Multi-characteristic optimization of WEDM for Ti-6Al-4V by applying grey relational investigation during profile machining

Sonawane¹,

Ronge²,

Pawar³

2019

JMES

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This research work presents multi-quality features optimization while wire electrical discharge machining (WEDM) of Ti-6Al-4V. Taguchi's L27 orthogonal arrangement is applied to inspect the outcome of governing variables such as pulse-on period, pulse-off interval, discharge voltage, discharge current, wire feed speed and cable tension on the kerf width, material removal rate (MRR), the surface roughness (SR) and overcut during intricate profile manufacturing on Ti-6Al-4V. To optimize all six governing variables, the grey relational investigation (GRI) is applied. The grey relational score is used as a multi-quality unique index (MQUI). From the experimental results the optimal configuration of governing variables obtained is pulse-on period 110 µs, pulse-off interval 55 µs, discharge voltage 40 volts, discharge current 170 Amp., wire feed speed 3 m/min and cable tension 8 gram. ANOVA analysis indicates that pulse-on period is an essential variable concerning the quality outputs. Results of confirmation trials show that the optimal governing variables improved the grey relational score (GRS) from 0.9048 to 0.9226 for the multiple responses. SEM analysis of machined parts shows that at high values of pulse on period and discharge current, deep craters, globules of debris, voids, and micro cracks are formed on the cut surface thus deteriorating the surface finish.Keywords: WEDM; Ti-6Al-4V; Taguchi method; grey relational investigation; grey relational score; profile machining; SEM analysis. S.A.Sonawane et. al / Journal of Mechanical Engineering and Sciences 13(4) 2019 6059-6087 6060 and non-electrical parameters affecting the quality measures namely metal removal rate (MRR), surface finish, surface integrity, and dimensional accuracy. WEDM technology has been widely used in conductive material machining mainly for the production of mold, dies, medical and dental instrumentation, graphite electrodes, parts of automotive and aerospace industries [1]. The process output is a combination of electrodynamic, electromagnetic, thermal dynamic and hydrodynamic actions.Jose and Shunmugum [2] studied the effect of WEDM process factors on surface finish and white layer thickness while machining Ti-6Al-4V. They found that the thickness of the white layer increases with an increase in the pulse on duration. Micro cracks were also observed in the white layer. Pasam et al.[3] studied surface finish characteristic during WEDM of Titanium grade-5. They considered different process factors such as ignition pulse current, injection pressure, short pulse duration, servo reference voltage, the time between two pulses, wire speed, servo speed, and wire tension. A genetic algorithm was employed for the optimization of the surface finish. Jabbaripour et al.[4] carried out electrical discharge machining of Ti-6Al-4V to study the influence of pulse on time, pulse current and open circuit voltage on TWR, MRR and recast layer thickness, microhardness and surface topography of the machined surface. From the results of experiments, it was fo...

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“…This transformation severely reduces the tool life and in turn machinability. Even though it is suggested to machine the ADI prior to the heat treatment [28][29][30][31], there are several instances in which it is necessary to machine it post heat treatment. Various alloying elements present, heat treatment parameters and the selection of machining parameters greatly affect the machinability of ADI.…”

Section: Graphite Nodulementioning

confidence: 99%

Machinability and related properties of austempered ductile iron: A review

Hegde

Sharma

2018

JMES

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When the ductile iron which is also known as Spheroidal Graphite (SG) iron, is subjected to austempering heat treatment, the material is known as austempered ductile iron (ADI). This material has good mechanical properties and has various applications in different fields. This revolutionary material with its excellent combination of strength, ductility, toughness and wear resistance has the potential to replace some of the commonly used conventional materials such as steel, aluminium and other light weight alloys as it offers production advantage as well. One of the problems encountered during manufacturing is machining of ADI parts owing to its high hardness and wear resistance. Many researchers over a period of time have reported the machinability aspects of the ADI. This paper presents a review on the developments made on the machinability aspects of ADI along with other mechanical properties.

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An investigation of material removal rate and kerf on WEDM through grey relational analysis

Cited by 16 publications

References 3 publications

Determination of Optimum Working Parameters for Multiple Response Characteristics of Worm Gear Box

Determination of Optimum Working Parameters for Multiple Response Characteristics of Worm Gear Box

Multi-characteristic optimization of WEDM for Ti-6Al-4V by applying grey relational investigation during profile machining

Machinability and related properties of austempered ductile iron: A review

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