Experimental investigation and optimization of WEDM process for AISI 420 stainless steel

Jha, Mukulanand; Garg, Rajiv Kumar; Shrivastava, Shekhar

doi:10.1088/1757-899x/1259/1/012031

Cited by 1 publication

(1 citation statement)

References 19 publications

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“…Sapit Azwan et al (25) utilized the statistical analysis (ANOVA) to conclude that the intensity of the pressure of process dielectric fluid with nano powder has a significant effect upon the enhanced SR. More specifically, the best value determined in the SR was (2,87 µm), which is regarded a (95 %) rate of enhancement. Mukulanand Jha et al (26) examined the SR measurable output response characteristic, taking into consideration the machine input control factors (T ON , T OFF , I and rate of WF). Taguchi L16 orthogonal arrays were used to build the experiments, and the Taguchi-based GRA was employed for optimizing the governing settings.…”

Section: Surface Roughnessmentioning

confidence: 99%

WEDM Process Parameters Analysis and Optimization: A REVIEW

Anwar,

Shather,

Khudhir

2024

Salud, Ciencia y Tecnología - Serie de Conferencias

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Wire Electrical Discharge Machining (WEDM) represents a non-conventional machining approach that harnesses thermal electrical energy for the fabrication of intricate structures. WEDM machines excel in achieving precise dimensions and a polished surface finish. It finds frequent application in the machining of robust materials that pose challenges for conventional manufacturing methods due to issues like vibrations. Within this machining method, numerous process parameters and performance indicators come into play, prompting various studies and investigations into its intricacies. This paper presents a comprehensive overview of current research trends in WEDM, particularly focusing on parameters for enhancing performance, such as surface roughness (SR), material removal rate (MRR), and Kerf width (KW). Notably, several process parameters, including pulse-off-time (TOFF), servo voltage (SV), pulse-on-time (TON), peak current (I), and wire tension (WT), contribute to the WEDM process. Additionally, various optimization techniques like the Taguchi method, Grey Relation Analysis (GRA), and analysis of variance (ANOVA) are employed across diverse materials, encompassing alloys, superalloys, and composites. The findings of this study suggest the importance of considering various process parameters, such as pulse-off-time (TOFF), servo voltage (SV), pulse-on-time (TON), peak current (I), and wire tension (WT), in the WEDM process. Moreover, the application of optimization techniques like the Taguchi method, Grey Relation Analysis (GRA), and analysis of variance (ANOVA) is recommended. These recommendations aim to improve the understanding and optimization of WEDM processes, especially when applied to diverse materials, including alloys, superalloys, and composites.

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Section: Surface Roughnessmentioning

confidence: 99%