Parametric Optimization and Effect of Nano-Graphene Mixed Dielectric Fluid on Performance of Wire Electrical Discharge Machining Process of Ni55.8Ti Shape Memory Alloy

Abstract

In the current scenario of manufacturing competitiveness, it is a requirement that new technologies are implemented in order to overcome the challenges of achieving component accuracy, high quality, acceptable surface finish, an increase in the production rate, and enhanced product life with a reduced environmental impact. Along with these conventional challenges, the machining of newly developed smart materials, such as shape memory alloys, also require inputs of intelligent machining strategies. Wire electrical discharge machining (WEDM) is one of the non-traditional machining methods which is independent of the mechanical properties of the work sample and is best suited for machining nitinol shape memory alloys. Nano powder-mixed dielectric fluid for the WEDM process is one of the ways of improving the process capabilities. In the current study, Taguchi’s L16 orthogonal array was implemented to perform the experiments. Current, pulse-on time, pulse-off time, and nano-graphene powder concentration were selected as input process parameters, with material removal rate (MRR) and surface roughness (SR) as output machining characteristics for investigations. The heat transfer search (HTS) algorithm was implemented for obtaining optimal combinations of input parameters for MRR and SR. Single objective optimization showed a maximum MRR of 1.55 mm3/s, and minimum SR of 2.68 µm. The Pareto curve was generated which gives the optimal non-dominant solutions.

Experimental Investigations and Pareto Optimization of Fiber Laser Cutting Process of Ti6Al4V

“…Figure 4 shows the residual plots for SR. Residual plots are important for verifying the ANOVA results [43]. The given four-in-one residual plots include a normal probability plot, a residual vs. fitted value plot, a histogram, and a residual vs. observation order plot.…”

Multi-Response Optimization of Al2O3 Nanopowder-Mixed Wire Electrical Discharge Machining Process Parameters of Nitinol Shape Memory Alloy

“…This clearly shows that the addition of Al 2 O 3 amount has reduced the surface defects to a larger extent. The addition of nanopowder creates uniform sparking among the work–tool interface [ 40 , 66 ]. This uniform sparking between work and tool has reduced the micro-crack substantially [ 67 ].…”

Integration of Fuzzy AHP and Fuzzy TOPSIS Methods for Wire Electric Discharge Machining of Titanium (Ti6Al4V) Alloy Using RSM

“…Saedon et al [ 30 ] attributed increasing MRR with increasing T on and current to the reduced dynamic shear strength of Ti alloy due to higher thermal influence in the machining region. The outcome of T off on MRR shows a decreasing trend with a rise in T off because of reduced spark ejection time and less MRR [ 9 , 54 ]. Thus, with an increase in T off , MRR is decreasing.…”