An experimental and simulation study on parametric analysis in turning of inconel 718 and GFRP composite using coated and
uncoated tools

Abstract

Process simulation is one of the important aspects in any
manufacturing/production context because it generates the scenarios to gain insight into process performance in reasonable time and cost. With upcoming worldwide applications of Inconel 718 and Glass Fiber Reinforced Polymer (GFRP) composites, machining has become an important issue which needs to be investigated in detail. In turning of hard materials (such as Inconel 718), cutting tool environment features high-localized temperatures (~1000ºC) and high stress (~700 MPa) due to contact between cutting tool and work piece. The tool may experience
repeated impact loads during interrupted cuts and the work piece chips may chemically interact with the tool materials. Therefore, the use of coated tool is preferred for turning of Inconel 718. It is observed that performance of machining process is influenced by different machining parameters such as spindle speed, depth of cut and feed rate as in case of turning. Material removal rate (MRR) and flank wear in turning of Inconel 718 using physical vapour deposition (PVD) and chemical vapour deposition (CVD) coated on carbide insert tool are reported. A simulation model based on finite element approach is proposed using DEFORM 3D software. The simulation results are validated with experimental results. The results indicate that simulation model can be effectively used to predict the flank wear and MRR in turning of Inconel 718. For simultaneous optimization of multiple responses, a fuzzy inference system (FIS) is used to convert multiple responses into a single equivalent response so that uncertainty and fuzziness in data can be addressed in an effective manner. The single response characteristics so generated is known as Multi Performance characteristic Index (MPCI). A non-linear empirical model has been developed using regression analysis between MPCI and process parameters. The optimal process parameters are obtained by a recent population-based optimization method known as imperialistic competitive algorithm (ICA). Analysis of variance (ANOVA) is performed to identify the most influencing factors for all the performance characteristics. The optimal conditions of process parameters during turning of Inconel 718 and GFRP composites are reported. It is observed that flank wear is combatively less when machined with PVD coated tool
than CVD coated tool in turning of both Inconel 718 and GFRP composite.