Multi-objective optimization of Abrasive water jet Machining parameters for Inconel 625 alloy using TGRA

Abstract

It is discussed in this article how the Taguchi grey relational analysis (TGRA) was used on Inconel-625, a high-performance engineering material with a broad variety of industrial applications, by machining it through abrasive water jet machining. Abrasive water jet machining (AWJM) has been shown to be capable of imitating the machining capabilities of Inconel 625, as shown in this study by the use of the TGRA approach for multi objective optimization of its machining parameters. Taguchi method is used to model the influence of three input parameters, namely Standoff distance (SOD), Abrasive mass flow rate (AMF), and Transverse Speed (TS), on three selected responses - material removal rate (MRR) and surface roughness (SR). The regression equations, mathematical models, and contribution of the selected parameters are obtained, and it is found that they have an impact on the three chosen output responses. A link between the MRR, SF and Kf was established through the application of multi-objective optimization. It has been shown that SOD, TS, and AMF all have statistically significant impacts on MRR; however, TS has a substantial, but less significant, influence on SF and Kerf when compared to SOD and AMF. It was revealed via the use of Grey rational grades that when MRR grew, it resulted in inferior SF and greater Kf values. As a result, using regression analysis, a mathematical model for MRR, SF, and Kf was developed in order to achieve the optimal conditions. The parameters: Standoff distance, 1 mm; Mass flow rate, 400 gm/min; and Transverse speed have maximum grey relational grade and hence are the optimal parameter values generating higher machining performance in terms of cutting material removal rate and surface roughness. As a result, the potential for optimising the production process by the AWJM for Inconel-625 using TGRA has been effectively proven.