Optimisation of machining parameters using grey relation analysis for EDM with impulse flushing

Dewangan, Shailesh; Biswas, Chandan Kumar

doi:10.1504/ijmms.2013.053826

Cited by 28 publications

(15 citation statements)

References 17 publications

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“…However, increase in gap current between the electrodes has resulted in lowering the TWI. This is due to the fact that at higher current, the spark intensity also will be larger resulting in higer tool wear and thus it affects the TWI [27]. But in general, the machinability in terms of TWI has been found to be better in Aluminium workpiece than in Mild Steel as depicted in Figure.…”

Section: Effect Of Workpiece Properties On Improving the Twimentioning

confidence: 99%

Influence of thermo-electrical property of materials on Powder Mixed Electrical Discharge Machining

Jeavudeen¹,

Siddhi²,

Murugan³

2019

FME Transactions

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Powder Mixed Electrical Discharge Machining (PMEDM) is considered as one of the viable methods to machine the materials which are hard and tough but with appreciable thermo-electrical properties. In PMEDM, it has been established that machinability is enhanced by adding additives in the form of fine powders in the spark gap of EDM process. In this investigation, the role of the thermo-electrical properties of workpiece on PMEDM process has been studied. Materials with distinct thermoelectric property, namely Mild Steel and Aluminium are taken as workpiece with Alumina as additive powder for the PMEDM process. Experiments have been conducted with Taguchi L9 Orthogonal Array (OA) with Material Removal Rate (MRR) and Tool Wear Index (TWI) as responses. Gap current, duty cycle and flow rate of powder mixed dielectric liquid have been taken as process parameters at 3 levels with circular copper rod of 12 mm diameter as tool electrode. Determination of the influence of properties of the workpiece on the machinability has been performed using a custom made PMEDM setup. ANOVA and main effect plot of data means for the aforementioned conditions have been analysed. The results are noteworthy with significant influence of the properties of the workpiece on the machinability of PMEDM process.

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Section: Effect Of Workpiece Properties On Improving the Twimentioning

confidence: 99%

Influence of thermo-electrical property of materials on Powder Mixed Electrical Discharge Machining

Jeavudeen¹,

Siddhi²,

Murugan³

2019

FME Transactions

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“…Shailesh Dewangan et al (2013) [7] studied about the selection of machining parameters in electrical discharge machining of AISI P20 tool steel material with impulse flushing system using three different electrode materials. L27 taguchi orthogonal array was framed with six different process parameters to observe the MRR and TWR.…”

Section: Introductionmentioning

confidence: 99%

Performance Assessment and Mathematical Modeling of Process Parameters in Electrical Discharge Machining of EN-31 Tool Steel Material Using Taguchi DOE

Pavani¹,

Rao²,

Rao³

2017

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Abstract. In non-traditional machining, electrical discharge machining (EDM) has tremendous potential on account of versatility of its applications and is successfully, commercially used in modern industries. EDM process is capable to machine geometrically complex, hard material components, tool steels, composites, super alloys, ceramics and carbides. In EDM, Material Removal Rate (MRR) and Tool wear rate (TWR) are generally analyzed to assess its performance. For this, a perfect combination of input variables is required. In the present study, machining is done on Tool steel workpiece material using a pure copper electrode. The input parameters like Pulse-ON time, Pulse-OFF time, Current and Gap voltage are selected for experimentation and Taguchi method is employed for the DOE by considering 4 factors and 3 levels. A total of 27 experiments (L27 orthogonal array) have been designed with a possible combination of selected input parameters. The present work mainly focuses on development of an extensive mathematical model for correlating the input and output variables using a conventional regression analysis. The adequacy of proposed model was tested with the help of some collected data through experimentation using Taguchi optimized DOE. The proposed linear multi-variable regression equation was found to be a best fitted model with 98% confidence levels.Keywords: Electrical discharge machining (EDM), material removal rate (MRR), tool wear rate (TWR).

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“…The same technique was utilized in optimization of multiple responses during EDM of Ale10%SiC P composites by converting the responses into single response grey relational grade [5]. Simultaneous increase in MRR as well as reduction in TWR could be achieved through successful implementation of GRA technique in EDM of AISI P20 tool steel [6].…”

Section: Introductionmentioning

confidence: 99%

Multi-response optimization of surface integrity characteristics of EDM process using grey-fuzzy logic-based hybrid approach

Dewangan

Gangopadhyay

Biswas

2015

Engineering Science and Technology, an International Journal

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Keywords:AISI P20 tool steel Grey-fuzzy logic Multi-response optimization Surface integrity Electric discharge machining a b s t r a c t Surface integrity remains one of the major areas of concern in electric discharge machining (EDM). During the current study, grey-fuzzy logic-based hybrid optimization technique is utilized to determine the optimal settings of EDM process parameters with an aim to improve surface integrity aspects after EDM of AISI P20 tool steel. The experiment is designed using response surface methodology (RSM) considering discharge current (Ip), pulse-on time (T on ), tool-work time (T w ) and tool-lift time (T up ) as process parameters. Various surface integrity characteristics such as white layer thickness (WLT), surface crack density (SCD) and surface roughness (SR) are considered during the current research work. Grey relational analysis (GRA) combined with fuzzy-logic is used to determine grey fuzzy reasoning grade (GFRG). The optimal solution based on this analysis is found to be Ip ¼ 1 A, T on ¼ 10 ms, T w ¼ 0.2 s, and T up ¼ 0.0 s. Analysis of variance (ANOVA) results clearly indicate that T on is the most contributing parameter followed by Ip, for multiple performance characteristics of surface integrity.

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Optimisation of machining parameters using grey relation analysis for EDM with impulse flushing

Cited by 28 publications

References 17 publications

Influence of thermo-electrical property of materials on Powder Mixed Electrical Discharge Machining

Influence of thermo-electrical property of materials on Powder Mixed Electrical Discharge Machining

Performance Assessment and Mathematical Modeling of Process Parameters in Electrical Discharge Machining of EN-31 Tool Steel Material Using Taguchi DOE

Multi-response optimization of surface integrity characteristics of EDM process using grey-fuzzy logic-based hybrid approach

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