1. Unlocking AISI420 Martensitic Stainless Steel's Potential: Precision Enhancement Via S-EDM with Copper Electrodes and Multivariate Optimization.
- Author
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Kumar, Sudhir, Ghoshal, Sanjoy Kumar, Arora, Pawan Kumar, Kumar, Harish, and Nagdeve, Leeladhar
- Subjects
ELECTRIC metal-cutting ,MARTENSITIC stainless steel ,COPPER electrodes ,GREY relational analysis ,COPPER ,RESPONSE surfaces (Statistics) ,MACHINING - Abstract
The current study explores the precision enhancement of AISI420 Martensitic Stainless Steel (MSS) using sinking-electrical discharge machining (S-EDM) with Copper electrodes, which is a unique combination of materials and machining process and conducts a comprehensive multivariate analysis to investigate the correlation between machine control variables (MCV) and measured machining performance (MMP) in the context of AISI420 Martensitic Stainless Steel and Sinking-Electrical Discharge Machining. The analysis of variance (ANOVA) establishes the hierarchy of machine control variables influence: Pulse current (B) > Gap voltage (A) > Pulse on Time (C). Remarkably, Pulse current (B) emerges as the paramount parameter, thus constituting a cornerstone of this study's findings. This research article utilizes the RSM–GRA–PCA methodology, which combines response surface methodology (RSM), grey relational analysis (GRA), and principal component analysis (PCA) to optimize the machining process. Using traditional RSM–GRA technique and RSM–GRA–PCA methodology, the experimental Grey Relational Grade (GRG
experiment ) are achieved 0.8048 and 0.9817, respectively. The validation test has been performed to confirm the fittest method positions. The percentage significance of significant factor is also improved from 64.63 to 79.71% and error is reduced from 5.22 to 1.68% using RSM–GRA–PCA methodology with improved GRG of 0.068. This integrated approach improves the grey relational grade (GRG) and reduces errors, leading to more accurate and efficient machining. [ABSTRACT FROM AUTHOR]- Published
- 2024
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