Conclusions and research contributions

CHAPTER 8

Conclusions and Future Scope

The main objective of the present work was to enhance the surface characteristics of AISI P20 mold steel in terms of its hardness, corrosion, and wear resistance by electrical Discharge Alloying. In view of this, the work was planned to investigate the alloying of titanium, aluminium, and nitrogen over AISI P20 mold steel. For this, a powder metallurgy tool of titanium and aluminium was used, and three different dielectric media viz. hydrocarbon oil, deionized water, and urea mixed deionized water were used. Further, to study the underlying process mechanism of EDA, a physics-based numerical model has been developed to predict the alloyed layer thickness. The alloyed layer thickness was computed by considering accurate values of the fraction of energy distributed to the workpiece. This fraction of energy distribution was computed by the inverse estimation method. Thereafter, the developed model has been integrated with ANN to develop a robust predictive model. The overall research work has been carried out in the following major stages.

 Experimental investigations into electrical discharge alloying of titanium and aluminium with AISI P20 mold steel in the presence of hydrocarbon oil dielectric medium

 Experimental investigations into electric discharge alloying of Ti and Al on P20 mold steel with a water-based dielectric medium

 Characterization and assessment of the alloyed workpieces in terms of its wear and corrosion resistance behavior.

 Computation of alloyed layer thickness in electric discharge alloying by inverse estimation of energy distribution.

hydrocarbon oil dielectric medium. A systematic experimental work has been carried out to study the elemental transfer of the tool material and decomposed dielectric, alloyed layer thickness, and hardness of the alloyed layer at varying discharge current and pulse on-time. The discharge current was varied in four levels viz. 6, 8, 10, and 12A, while the pulse on-time values considered were 546, 706, 856, and 1006 µs. Further, the type of alloy formed has been characterized and presented in detail. Following conclusions can be drawn from this study.

 The transfer of the tool elements over the workpiece surface has been successfully confirmed from the EDS result. Elemental mapping of the alloyed surface over the top surface, as well as the cross-sectioned region, indicated that the tool elements present are uniformly distributed in the alloyed region. Elemental composition up to a maximum of 18 % Ti and 18.7 % Al was observed over the alloyed workpiece surface.

 X-ray diffraction pattern indicated the formation of Fe3C and TiAl at the alloyed region. Therefore, it can be concluded that the electric discharge surface alloying of Ti and Al with AISI P20 mold steel has been successfully achieved.

 A uniform layer of 70 µm thickness can easily be alloyed on the substrate material using powder metallurgy-based green compact tool electrodes with the composition of 50 % Ti and 50 % Al.

 The hardness of the alloyed region was found to be four times more than that of the parent material, i.e., 300 HV0.3 to 1125 HV0.3. That ascertains the usefulness of the EDA process in improving the surface characteristics of the parent material.

 The material deposition rate was affected by the change in discharge current and pulse on-time. Increase in the discharge current and pulse on-time results in a higher material deposition rate.

 The surface roughness of the alloyed workpieces exhibited a roughness value in the range of 4.5 to 8.5 µm.

8.1.2 Experimental investigations into electric discharge alloying of Ti and Al with water-based dielectric medium

The effects of urea mixed deionized water on the electric discharge alloying of AISI P20 mold steel using powder metallurgy electrodes of titanium and aluminium have been investigated. A comparative study was carried out between the alloyed surfaces obtained with deionized water and that with the urea mixed deionized water. Detailed

investigations have also been carried out to study the effect of pulse on-time discharge current and dielectric medium on the material transfer rate and alloyed layer thickness.

The hardness of the alloyed layer has also been characterized. Following conclusions have been drawn.

 EDS examination confirms successful transfer of tool material along with decomposed elements from the dielectric on the workpiece. A uniform distribution was noticed from the elemental mapping. An elemental composition up to a maximum of 16.5 % Ti with 12 % Al, 35.02 % oxygen, and 4 % nitrogen was observed for the workpiece processed in urea mixed deionized water. For the workpiece processed in deionized water, a maximum of 27.2 % titanium with 7.6 % aluminum and 40.3 % oxygen was observed.

 Formation of an alloyed layer composed of TiAl, Fe3O4, and Ti4AlN3 was observed from the XRD analysis for the workpiece processed using urea mixed DI water, while for the workpiece processed in deionized water, the alloyed layer was noted to be composed of TiAl and Fe3O4.

 The analysis of the alloyed layer thickness indicated that the thickness was more for the workpieces processed using DI water as compared to that with the urea mixed. An alloyed layer of 60.19 µm thickness was noted for the workpiece processed using DI water, while that for urea mixed deionized water was 53.25 µm.

 In case of hardness study, the hardness of the alloyed layer was observed 579.83 HV0.3

while using deionized water. For the workpiece processed with mixed deionized water, the hardness was noted to be 604.35 HV0.3. The percentage increase in the hardness of the alloyed region for the workpiece processed in DI water was found to be enhanced by 87.04 % as compared to that of the parent material, while that for the workpiece processed in urea mixed deionized water was 101.45 %.

 The material deposition rate was mainly affected by the discharge current. Increase in discharge current resulted in higher deposition rate for both the type of dielectric medium.

 During surface roughness study, the surface roughness of the processed workpieces was found to be dependent on the discharge current and pulse on-time; however, the addition of urea did not find any significant influence on the surface roughness value.

The surface roughness extends a range of 5.94 to 12.45 µm for the workpiece

processed in deionized water while that of urea mixed deionized water, the range was found to be 5.98 to 12.54 µm

8.1.3 Wear and corrosion resistance behavior of electric discharge alloyed workpieces

An investigation of the wear behavior has been made by analyzing the real-time wear data, friction coefficient, and mass loss during the wear test. Further, the corrosion behavior for the alloyed workpieces was studied by studying the electrochemical impedance spectrum. A comparative study has been made for the wear and corrosion resistance of the workpieces processed in three types of dielectric media. From the present work, the following conclusions have been drawn.

 The real-time wear data acquired during the test indicated that the wear of the workpieces processed in hydrocarbon oil was the least followed by workpieces processed in urea mixed deionized water, unprocessed workpiece, and workpiece processed in deionized water.

 The low slope in the trend of the wear after a depth of about 10 µm signifies that there was a formation of a uniform hard alloyed region after a depth of 10 µm from the alloyed surface for the workpiece processed in hydrocarbon oil.

 The friction coefficient trend for the workpiece processed using hydrocarbon oil was decreasing. For the unprocessed workpiece and the workpieces processed in deionized water and urea mixed deionized water, the friction behavior was noted to be increasing.

 The mass loss during the wear test result showed that the workpiece processed in hydrocarbon oil was the least followed by workpieces processed in urea mixed deionized water, deionized water, and the unprocessed workpiece. The mass loss for the workpiece processed in hydrocarbon oil was significantly reduced by 46 % from that of the unprocessed workpiece. The change in mass loss is quite marginal for the unprocessed workpiece and the workpieces processed in the water-based dielectric.

 From the Bode diagrams, it was observed that the impedance modulus and the maximum phase angle were the highest for the workpiece processed in hydrocarbon oil, indicating the highest polarization resistance.

 The corrosion resistance value for the workpiece processed using hydrocarbon oil was almost double the corrosion resistance of the workpieces processed using deionized

water and urea mixed deionized water and unprocessed workpiece. There was 110 % enhancement in the corrosion resistance for the workpiece processed in hydrocarbon oil from that of the unprocessed workpiece.

8.1.4 Computation of alloyed layer thickness in electric discharge alloying by inverse estimation of energy distribution

An integrated FEM-ANN model has been successfully developed to accurately predict the alloyed layer thickness in electric discharge alloying of AISI P20 mold steel using powder metallurgy electrodes of titanium and aluminium at different processing conditions such as varying discharge current, pulse on-time, and various dielectric media.

The alloyed layer thickness was computed by considering the accurate values of fraction of energy distribution to the workpiece, FA. These values were computed by using the inverse estimation method and the ANN-based model. Following important conclusions were drawn from the study.

 The neural network of 3-10-1 architecture was found to be the optimum network.

 The developed methodology suggests that the fraction of energy FA varies from 0.129 to 0.215. This can be employed in the thermal analysis of the electric discharge-based manufacturing processes.

 The performance of the developed FEM-ANN was verified by carrying out the experiments. It was found acceptable with an average prediction deviation of 6.55 %.

 The present work facilitates a simple and quick methodology for accurate prediction of the alloyed layer thickness for complex manufacturing processes such as EDA.

This provides an efficient and economical alternative to the costly, tedious, and time- consuming experimental work.