Experimental Investigations and Optimization of Electrical Discharge Machining Process Parameters for Shape Memory Alloys

Abstract

Shape memory alloys (SMAs) are recently developed next generation alloys that exhibit a unique property of memorizing its initial form (shape) and regaining it upon heating. A shape-memory alloys exhibit in numerous forms. Nickel-titanium alloys are also commonly referred to as NiTi alloys or Nitinol alloys in honor of its discovery at the Naval Ordnance Laboratory (NOL). One of the shape memory alloys which possesses superelasticity and biocompatibility is nickel–titanium alloy. Apart from these, the alloys also possess high corrosion resistance, wear resistance, and pseudoelasticity. However, past studies of SMAs with conventional machining reports poor chip breaking, high tool wear, poor surface quality, low-dimensional accuracy and most importantly retaining the shape memory effect after machining. Thus, SMAs and most preferably nitinol are best machined through nonconventional machining techniques. Wire electrical discharge machining (WEDM) is a nonconventional machining process which is best-suited for ‘‘difficult-to-machine’’ materials. Wire electrical discharge machining (WEDM) is a non-contact type process, where the material is removed with the help of high frequency sparks generated between the tool and workpiece in the presence of a suitably chosen dielectric. This process operates on the principle of material erosion due to the thermoelectric effect achieved by generating a series of sparks between the workpiece and wire under a suitable dielectric fluid. This process has been widely applied to machine various components incorporating close tolerances, complex geometries, and requiring minimum damage to the base material properties. This realization leads to the initiation studies of WEDM of SMAs. Although, WEDM process for SMA has been discussed briefly in open literature, limited attempts have been made for certain considerations after machining e.g. retention of shape memory effect after machining. Majority of studies have investigated the parametric optimization of WEDM process parameters using various techniques. The optimization of process parameters for the machining of SMA has been performed primarily for material removal rate (MRR), surface roughness (SR), and microhardness (MH). However, these optimized parameters have not yet been explored for their effects on the shape memory effect of the machined surface. In addition, majority studies optimized an individual response rather xii than conducting a simultaneous optimization of multiple variables which is important in light of industrial manufacturing. Moreover, microscopic changes in the surface characteristics after SMA machining can affect the properties of the product, with retention of the shape memory effect being the most important requirements. Researchers have correlated the shape memory effect with the MH value. But studies on preserving the shape memory effect after machining by techniques such as differential scanning calorimetry (DSC) are scarcely reported. Thus, the aim of the present research is to investigate the machining of shape memory alloys using WEDM technique. The three most important input process parameters such as pulse-on time, pulse-off time, and current were selected to get optimum value of while the major output variables such as material removal rate, surface roughness, and microhardness. A series of structured experiments were conducted according to Box-Behnken Design (BBD) philosophy of response surface methodology, which is a robust Design of Experiment technique. The Experiments were conducted on round bar of diameter 6 mm and 8 mm for nitinol SMA and superelastic nitinol SMA respectively. Mathematical models were generated for each output variable and the robustness of the equations was tested by analysis of variance (ANOVA). Furthermore, contour plot analysis was carried out. To achieve optimal solution for multiple responses, heat transfer search optimization technique has been used. Additionally, case studies including real-time manufacturing scenarios along with simultaneous optimization of output variables were performed using the advanced parameterless evolutionary algorithm heat transfer search (HTS); for confirming research outcome with respect to objectives of study. A validation study has been undertaken to compare the predicted and measured responses. DSC testing was also performed on the machined surface obtained using the optimized parameters to ensure retention of the shape memory effect, which is the main goal of the study. The published optimization studies focus on either single or multi-objective optimization with limited consideration of actual industrial requirements. Pareto optimal curves have been reported in literature for the WEDM of SMAs restricted to only two response variables and ignoring the third response. In current study, 3D Pareto curve showing non-dominant optimal xiii points were generated using the multi-objective HTS algorithm. For improved understanding of the 3D Pareto points, corresponding 2D views of the generated solutions. In the current study, surface analysis of the material that was machined at the optimal process-parameter setting is reported. From a detailed literature survey, it was found that the majority of research work was carried out and concentrated on the parametric optimization of shape-memory alloys, but studies on surface integrity after WEDM for shape-memory alloys are rarely reported. For the current study, surface morphology, phase analysis, and elemental composition after WEDM using scanning electron microscope (SEM) and energy dispersive X-ray analysis (EDX) are discussed. This research study contributes substantial input to end users working the WEDM of SMAs. Keywords: Shape Memory Alloys, Nitinol, Superelastic SMAs, WEDM, DSC test, Shape Memory Effect, Surface Integrity.