Investigations on Machining Characteristics of Cryotreated Titanium Alloys and Electrodes Using EDM

Abstract

In the past, the development of titanium alloys came initially from the aerospace industry when there was a crucial need for new materials with high strength to weight ratios, which fall between those of iron and aluminum. Due to its excellent properties, titanium alloy are widely used in the aerospace, chemical, automotive, biomedical, power generation, nuclear plants and many other emerging fields of science and technology. Titanium is recognized as a material which is difficult-to-machine with conventional machining processes. Economical machining of titanium alloys becomes important for industrial products and research work. Although machining of titanium alloy becomes easier with non-traditional or non-conventional machining processes, but the selection of suitable machining process and their parameters is a challenging task for the researchers to increase its machinability. Electric discharge machining (EDM) is a popular non-conventional machining process used for machining of any type of electrically conductive materials in a contact less mode especially when complex geometries are required. Due to its favorable characteristics and advantages, EDM process is extensively used for machining of titanium alloys. In EDM, the overall machining performance depends on the thermo-electrical properties of tool and workpiece materials. However, high electrical resistivity and poor thermal conductivity of titanium, makes the machining difficult by this process. Cryogenic treatment has a historical background of improving the properties of the materials, i.e. mechanical, electrical and thermal. Cryogenic treatment process has been used for improving the mechanical, electrical and thermal properties of materials. Cryogenic treatment process consists of a slow cooling from room temperature to the liquid nitrogen temperature, soaked for a suitable time at this temperature, and after that the material is heated up to room temperature. The cooling rate, heating rate and soaking period are the most important parameters in cryogenic treatment that highly affected the properties of the materials. Two cooling temperatures were used for this study: (i) -1100C for shallow cryogenic treatment (SCT) and (II) -1840C for deep cryogenic treatment (DCT). In the present study, the primary experimental work was completed during Phase-A (Main study). Subsequently, experimentation was carried out in two more phases (Phase-B and Phase-C). During Phase–A experimentation, three grades of titanium namely (i) Ti (ASTM grade 2), Ti-6Al-4V (ASTM grade 5) and (III) Ti-5Al-2.5Sn (ASTM grade 6) were machined with three electrodes Copper (Cu), Copper-Chromium (Cu-Cr) and Copper-Tungsten (Cu-W). Peak current (Ip), pulse-on-time (Ton), pulse-off-time (Toff), dielectric medium, electrode material, workpiece material and cryogenic treatment of the electrode and workpiece materials were identified as the machining parameters. The parameters were varied to investigate their effect on Material Removal Rate (MRR), Tool Wear Rate (TWR), Surface Roughness (SR) and Micro-Hardness (MH) using Taguchi L18 orthogonal array (OA). Peak current (Ip) was observed to be the most significant factor, followed by tool or electrode material and pulse-on-time (Ton) that affected the MRR and TWR. Increase in MRR was observed in case of DCT titanium alloys due to improvement in electrical and thermal conductivity of the material. A mathematical model for predicting MRR and TWR was developed by using dimensional analysis (Buckingham’s π theorem) based on the outcomes of Taguchi model and the thermal-physical properties of the workpiece and electrode material. The predicted results obtained from the developed mathematical model were validated by comparing with the experimental results and were found to be in good agreement with each other. The experimental results and the predicted results show good agreement. Experimental results also revealed that Ip, Ton and Toff significantly affected the surface roughness and micro-hardness of the surface. Artificial Neural Network (ANN) coupled with the Taguchi approach was applied for optimization and prediction of surface roughness and micro-hardness. An optimum setting of machining parameters was identified for maximizing the micro-hardness and MRR and minimizes the TWR and SR by using the Taguchi approach. After optimization of the individual responses, the responses, namely MRR, TWR, SR and MH were collectively optimized by using the Analytical Hierarchy Process (AHP) technique. The surface properties of the tool-electrode materials were also investigated in terms of electrode surface roughness. In the next Phase–B, experimentation, grade VI of titanium alloy (Ti-5Al-2.5Sn) without cryogenic treatment (WCT) and cryogenic treated (shallow and deep) were machined with untreated Cu-Cr tool. Simple FERROLAC 3M EDM Oil was used as the dielectric medium. Using the Phase-A results, two machine parameters (Ip and Ton) were identified as process variables and varied at three levels during the process, using Taguchi L9 orthogonal array. Machining performances of WCT, SCT and DCT machined surface were analyzed and compared in terms of MRR, TWR, SR and MH. The result of the study show significant improvement with DCT alloy when compared with SCT and WCT workpieces. From the study, it was observed that there is a significant increase of 21.84% in MRR, a reduction of 27.40% in TWR, an improvement of 19.58% in surface finish and increase of 17.30% in micro-hardness. During Phase–C experimentation, three materials; namely Ti, Ti-6Al-4V and Ti-5Al-2.5Sn were machined with three different types of cryogenically treated electrode material (WCT, SCT, DCT); namely Cu, Cu-Cr and Cu-W in Mn powder added dielectric. The machining performance of WCT titanium alloys was compared with DCT titanium alloys. Four different input parameters namely (i) peak current, (ii) pulse-on-time, (iii) electrode material and (iv) cryogenic treatment of electrode material were varied at three levels. Peak current was observed to be the most significant factor that affected the EDM performance followed by the pulse-on-time. The significant effect of cryogenic treatment of the tool was observed. The experimental results revealed that the higher MRR and MH, lower TWR and SR were observed in the case of DCT titanium alloy workpiece machined with DCT electrode as compared with WCT workpiece and tool material. In this stage, optimization of the input parameters for the EDM of TITAN 15 alloy was performed for multiple performance characteristics (MRR, TWR, SR and MH) by using Grey Relational Analysis (GRA) approach followed by confirmation experiments. The present research work has also focused on study of surface integrity of the workpiece and tool surfaces after machining. For this purpose, each workpiece and tool/electrode surface after machining for main experimentation (Phase-A) and selected titanium workpiece samples for Phase-A and Phase-C were examined by Scanning Electron Microscope (SEM) coupled with Energy Dispersive X-Ray (EDX) analyzer followed by X-ray Diffraction (XRD) for surface integrity. The XRD patterns clearly show the formation of different chemical compounds and new phases on the machined surface. EDX spectrum represents the migration of various elements on the machined surface either of the workpiece base metal or transfer from the tool surface or migration from dielectric medium. SEM micrographs indicated surface defects such as surface cracks, larger and deeper size of craters, recast layer, micro pores, pin holes, debris, pock marks etc. on the machined surface. The amount of discharge energy significantly resulted in generation of such surface defects. Experimental results clearly showed that surface properties were significantly affected by current followed by pulse-on-time. A significant amount of carbon particles were migrated on both tool and workpiece surfaces due to decomposition of dielectric. Various carbides and oxides were formed either in free and/ or in compound form on both the workpiece and electrode surface. Different compounds, namely Titanium-Carbide (TiC), Aluminum-Titanium-Carbide (Al2Ti4C2), Tin-Titanium-Carbide (SnTi2C), Titanium-Zinc-Carbide (Zn2Ti4C), Titanium-Oxide also known as hongquite (TiO), Titanium-Dioxide also known as rutile (TiO2), Tin-Titanium-Tungsten-Oxide (Sn2TiWO7), Copper- Titanium-Oxide (Cu2TiO3), Manganese-Titanium-Oxide (Mn2TiO4) precipitated on the machined surface due to phase transformations and were analyzed by using the XRD analyzer. In the last chapter, the results of the three phases of the study have been summarized. Some of the significant conclusions are: I. During the EDM process spark energy increases as the value of Ip and Ton increases, which affect the machining performance significantly. II. Arcing on workpiece or electrode surface was noticed at higher current (14A), longer duration of pulse-on-time (150µs) and smaller duration of pulse-off-time (30µs). Due to arcing the machining efficiency was reduced in terms of low MRR, poor surface finish, higher TWR and more deposition of carbon on the machined surface. III. A mathematical model considering the significant machine parameters and the thermo-physical properties of the workpiece and electrode materials was developed for predicting MRR and TWR using dimensional analysis approach. IV. The structural design of Artificial Neural Network (ANN) was selected, trained, validated, tested and then used for simulation to optimize the surface roughness and micro-hardness. Experimental results and ANN predicted results showed good agreement. V. The SEM micrographs show that high discharge energy (Ip ×Ton) was responsible for producing the surface defects such as; surface or thermal cracks, craters, thick recast layer, micro pores, pin holes, residual stresses and debris.