Optimizing multiple responses in electrohydraulic forming of 316L stainless steel sheets: Integrating RSM-GRA and PCA for process parameter analysis

Abstract

The primary aim of this work is to experimentally investigate the electrohydraulic forming (EHF) of AISI 316L stainless steel sheets into a conical die and to optimize the process parameters. Voltage (V), stand-off distance (SOD) and electrical conductivity (EC) of discharge medium are input EHF process variables that are to be optimized. Response surface methodology-central composite design (RSM-CCD)-based design of experiment technique was utilized for conducting experiments. EHF offers high strain-rate deformation suitable for lightweight components, but achieving simultaneously low surface roughness and high formability requires multi-objective optimization. To determine the optimal process parameters while considering multiple objectives concurrently, a combined approach using hybrid grey relational analysis (GRA) and principal component analysis (PCA) is employed. ANOVA was utilized to find the significant parameters and findings suggests that voltage is the most influential parameter with a contribution of 61.17% followed by EC of medium=20.90%. The optimized EHF process parameters found out through GRA-PCA technique is V = 16 kV, SOD=38 mm, EC = 2 mS/cm. Confirmatory experiments have conducted to validate the hybrid model and the responses found out to be forming depth = 23 mm, sum of strain = 0.395, surface roughness =0.22 µm which is significant improvement and better than the initial condition. The weighted grey relational grade value is also increased by 17%. The desirability of conventional RSM technique is 75.15% and the desirability of GRA PCA technique was found to be 81.12% an increase of 5.97% making this technique suitable for prediction. The microstructural analysis performed at the optimized condition across the different locations of the EHF formed cone region confirmed uniform deformation without detrimental features. The proposed hybrid optimization method demonstrates an effective approach for improving both process performance and material integrity in high-rate forming applications.