Modelling Surface Finish in Electrical Discharge Machining Tablet Shape Punches using Response Surface Methodology

Danh

et al. 2021

MSF

Self Cite

In electrical discharge machining (EDM) powder material can be mixed into the dielectric fluid to improve quality of machining surface of components. Therefore, finding suitable input parameters of this process becomes an important task. This paper presents a methodology to find the optimum input factors of the EDM process when adding nanosilicon carbide powder into the dielectric fluid for processing cylindrical shaped parts. In this research, the Taguchi method was used for experiment design in order to investigate the effect of the input parameters on the surface roughness. Also, optimum input factors for minimum surface roughness (RS) was proposed. The result from the deviation of SRbetween the analysis and the experiment demonstrates that the optimum input parameters are helpful to predict the value of surface roughness. Therefore, this can increase the economic and technical effectiveness in EDM process.

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Study on Influence of Input Parameters on Surface Roughness in PMEDM Cylindrical Shaped Parts

Danh

et al. 2021

MSF

Self Cite

“…Thus, researchers continuously seek to improve PMEDM process to achieve the optimum machining performance [4][5][6]. Many pieces of research have focused on understanding the relationship between PMEDM process parameters and dimensional accuracy, surface roughness, electrode wear, or MRR [7][8][9][10][11]. The concentration of abrasive silicon powder, peak current, pulse-on time, and duty factor are optimized to achieve better machining performance related to MRR, electrode wear, and surface roughness [12][13].…”

Section: Introductionmentioning

confidence: 99%

Multi-Objective Optimization of PMEDM Process of 90CrSi Alloy Steel for Minimum Electrode Wear Rate and Maximum Material Removal Rate with Silicon Carbide Powder

Danh

et al. 2021

MSF

Self Cite

This study aims to minimize electrode wear (EW) and maximize material removal rate (MRR) in powder mixed electrical discharge machining (PMEDM) process of 9CrSi alloy steel with silicon carbide powder. To achieve these objectives, Taguchi method and Grey Relational Analysis (GRA) are applied to optimize one two-level and four three-level PMEDM process parameters, including Ton, Toff, CP, IP and SV in eighteen experiments based on an orthogonal array L18 (21 and 43). Results have provided a set of optimal PMEDM process parameters in which Ton has the strongest effect on SW and MRR while that of CP is insignificant. The obtained minimum EW and maximum MRR have been verified and proven by a PMEDM experiment using optimal process parameters. The proposed method can be further applied to optimize other PMEDM process parameters for different objectives.

“…Electrical discharge machining (EDM) has various advantages such as finishing surface as mirror, machining cavities with thin walls, or processing difficult geometry [1] and difficult-tomachine material parts. Lately, several studies [2,3] on using EDM to process cylindrically shaped parts were introduced. Although it has various benefits, EDM process has several restrictions such as fast electrode wear, low productivity, and high cost of EDM system.…”

Section: Introductionmentioning

confidence: 99%

Multi-Objective Optimization of PMEDM Input Factors for Processing Cylindrical Shaped Parts

Hien

et al. 2021

MSF

The present work deals with multi-objective optimization of powder mixed electric discharge machining (PMEDM) when processing cylindrically shaped parts. In this work, the pulse on time Ton, the pulse off time Toff, the powder concentration Cp, the pulse current IP, and the server voltage SV were chosen for the optimization problem. Also, the surface roughness (SR), the material removal rate (MRR), and the electrode wear (EW) were chosen as three objectives for the investigation. Besides, the Taguchi method and the grey relational analysis (GRA) were applied for optimizing simultaneously three the SR, the MRR and the EW to find the optimum input factors. The impact of the process parameters on the overall goal was weighed. Additionally, optimum input factors of PMEDM process for multi-objectives were recommended.