Multi-response optimization of PMEDM on Inconel 718 using hybrid T-GRA, TOPSIS, and ANN model

Abstract

Inconel 718 is one of the Nickel-based superalloys considered one of the most difficult-to-machine materials owing to its property to retain hardness at higher temperatures. This study examined the performance of Edcutor-based PMEDM machining on Inconel 718. Taguchi L9 OA has been used with current, Pulse-OFF time & Pulse-ON time as process parameters with a delivery side pressure of 6 bar for the Alumina mixed dielectric. Material removal rate (MRR), Tool wear rate (TWR), & surface roughness (SR) have been taken as output responses. The results have been investigated by MADM techniques, namely Taguchi-based Grey Relational Analysis (T-GRA) & TOPSIS analysis. Furthermore, the ranks obtained from T-GRA & TOPSIS have been validated by developing a single layered ANN model. Ranks predicted by the ANN model are the same for T-GRA and TOPSIS and the R-values are 0.924 & 0.871, respectively. ANOVA has also been used to analyze parameter effects on output responses.

Keywords

• multi-attribute decision making
• t-gra
• topsis
• ann
• pmedm
• mrr
• twr
• sr