The Accuracy of Finishing WEDM of Inconel 718 Turbine Disc Fir Tree Slots

Experimental Investigation on the Impact of Graphite Electrodes Grain Size on Technological Parameters and Surface Texture of Hastelloy C-22 after Electrical Discharge Machining with Negative Polarity

Electrical discharge machining (EDM) is a rapidly evolving method in modern industry that manufactures highly complex components. The physical properties of a tool electrode material are significant factors in determining the effectiveness of the process, as well as the characteristics of the machined surfaces. The current trend of implementing graphite tool electrodes in manufacturing processes is observed. Innovative material engineering solutions enable graphite production with miniaturized grain size. However, the correlation between the graphite electrode grain size and the mechanism of the process removal in the EDM is a challenge for its widespread implementation in the industry. This research introduces a new method to evaluate the impact of the graphite electrode grain size and machining parameters on the material removal effectiveness, relative tool wear rate, and surface roughness (Ra) of Hastelloy C-22 following EDM with negative polarity. The study utilized new graphite materials with a grain size of 1 µm (POCO AF-5) and 10 µm (POCO EDM-180). An assessment of the impact of the EDM process parameters on the technological parameters and the development of the surface roughness was carried out. Electrical discharge machining with fine-grained graphite electrodes increases process efficiency and reduces tool wear. Graphite grains detached from the tool electrode affect the stability of electrical discharges and the efficiency of the process. Based on the experimental results, mathematical models were developed, enabling the prediction of machining effects to advance state-of-the-art manufacturing processes. The obtained mathematical models can be implemented in modern industrial EDM machines as guidelines for selecting adequate machining parameters depending on the desired process efficiency, tool wear rate, and surface roughness for advanced materials.

Study of Wire-Cut Electro-Discharge Machining of Heat-Resistant Nickel Alloys

This paper presents an analysis and theoretical model for assessing the quality and accuracy of wire-cut electro-discharge machining (WEDM) of products made from novel heat-resistant nickel alloys such as CrNi56KVMTYB. It is observed that WEDM processing of Ni alloy led to high surface roughness for the thick specimens, and electrical parameters such as pulse duration for the selected range depict an insignificant role in the value of surface roughness. On the other hand, the cut width of the machined surface decreases as the pulse duration increases, while the cut width is elevated for thick workpieces. Secondary discharges developed in WEDM have negative effects that cause sludge adhering and deterioration in the quality and productivity of processing. The regression model is developed to predict the surface roughness and cut width of machined surfaces, which holds significant importance in modern engineering. The workpiece is examined for surface integrity and material deposition. It is observed that an increase in the height of the specimen leads to the occurrence of secondary discharges, which in turn results in the formation of cracks on the surfaces of high-temperature nickel alloys. These cracks have a detrimental effect on the performance of critical products made from next-generation heat-resistant nickel alloys.

Optimization with artificial intelligence of the machinability of Hardox steel, which is exposed to different processes

In this study, different process types were processed on Hardox 400 steel. These processes were carried out with five different samples as heat treatment, cold forging, plasma welding, mig-mag welding and commercial sample. The aim here is to determine the changes in properties such as microstructure, microhardness and conductivity that occur in the structure of hardox 400 steel when exposed to different processes. Then, the samples affected by these changes were processed in WEDM with the box-behnken experimental design. Ra, Kerf, MRR and WWR results were analyzed in Minitab 21 program. In the continuation of the study, using these data, a prediction models were created for Ra, Kerf, MRR and WWR with Deep Learning (DL) and Extreme Learning Machine (ELM). Anaconda program Python 3.9 version was used as a program in the optimization study. In addition, a linear regression models are presented to comparison the results. According to the results the lowest Ra values were obtained in heat-treated, cold forged, master sample, plasma welded and mig-mag welded processes, respectively. The best Ra (surface roughness) value of 1.92 µm was obtained in the heat treated sample and in the experiment with a time off of 250 µs. Model F value in ANOVA analysis for Ra is 86.04. Model for Ra r2 value was obtained as 0.9534. The lowest kerf values were obtained in heat-treated, cold forged, master sample, plasma welded and mig-mag welded processes, respectively. The best kerf value of 200 µ was obtained in the heat treated sample and in the experiment with a time off of 200 µs. Model F value in ANOVA analysis for Kerf is 90.21. Model for Kerf r2 value was obtained as 0.9555. Contrary to Ra and Kerf, it is desirable to have high MRR values. On average, the highest MRR values were obtained in mig-mag welded, plasma welded, cold forged, master sample and heat-treated processes, respectively. The best mrr value of 200 g min-1 was obtained in the mig-mag welded sample and in the experiment with a time off of 300 µs. Model for MRR r2 value was obtained as 0.9563. The lowest WWR values were obtained in heat-treated, cold forged, master sample, plasma welded and mig-mag welded processes, respectively. The best wwr value of 0.098 g was obtained in the heat treated sample and in the experiment with a time off of 200 µs. Model F value in ANOVA analysis for WWR is 92.12. Model for wwr r2 value was obtained as 0.09561. In the analysis made with artificial intelligence systems; The best test MSE value for Ra was obtained as 0.012 in DL and the r squared value 0.9274. The best test MSE value for kerf was obtained as 248.28 in ELM and r squared value 0.8676. The best MSE value for MRR was obtained as 0.000101 in DL and the r squared value 0.9444. The best MSE value for WWR was obtained as 0.000037 in DL and the r squared value 0.9184. As a result, it was concluded that different optimization methods can be applied according to different outputs (Ra, Kerf, MRR, WWR). It also shows that artificial intelligence-based optimization methods give successful estimation results about Ra, Kerf, MRR, WWR values. According to these results, ideal DL and ELM models have been presented for future studies.

Effects of Wire Electrical Discharge Finishing Cuts on the Surface Integrity of Additively Manufactured Ti6Al4V Alloy

The Selective laser melting (SLM) technology of recent years allows for building complex-shaped parts with difficult-to-cut materials such as Ti6Al4V alloy. Nevertheless, the surface integrity after SLM is characterized by surface roughness and defects in the microstructure. The use of additional finishing technology, such as machining, laser polishing, or mechanical polishing, is used to achieve desired surface properties. In this study, improving SLM Ti6Al4V alloy surface integrity using wire electrical discharge machining (WEDM) is proposed. The influence of finishing WEDM cuts and the discharge energy on the surface roughness parameters Sa, Svk, Spk, and Sk and the composition of the recast layer were investigated. The proposed finishing technology allows for significant improvement of the surface roughness by up to 88% (from Sa = 6.74 µm to Sa = 0.8 µm). Furthermore, the SEM analyses of surface morphology indicate improving surface integrity properties by removing the balling effect, unmelted particles, and the presence of microcracks. EDS analysis of the recast layer indicated a significant influence of discharge energy and the polarization of the electrode on its composition and thickness. Depending on the used discharge energy and the number of finishing cuts, changes in the composition of the material in the range of 2 to 10 µm were observed.

The Review of Current and Proposed Methods of Manufacturing Fir Tree Slots of Turbine Aero Engine Discs

This review article presents a summary of currently used and proposed methods of manufacturing fir tree slots of discs in turbine engines. The production of aircraft, including aircraft engines during times of overlapping global economic crises related to the COVID-19 pandemic or the war in Eastern Europe requires a quick response to the changing numbers of passengers and cargo. Similarly, the aviation industry must adapt to these conditions, and thus utilize flexible production methods allowing for a quick change in the design or type of a given part. Due to the constant adoption of new materials for the most critical aero engine parts and the necessity of complying with environmental regulations, it is necessary to search for new methods of manufacturing these parts, including fir tree slots. As an alternative to currently used expensive and energy-intensive broaching, many manufacturers try to implement creep feed grinding CFG or contour milling. However, other manufacturing methods, thus far rarely used for crucial machine parts such as WEDM, ECDM or AWJ, are gaining more and more popularity in the aviation industry. This article presents the advantages and shortcomings of these methods in the context of manufacturing fir tree slots.

Experimental Investigation and Optimization of Rough EDM of High-Thermal-Conductivity Tool Steel with a Thin-Walled Electrode

The industrial application of electrical discharge machining (EDM) for manufacturing injection molding, in many cases, requires forming depth cavities with high length-to-width ratios, which is quite challenging. During slot EDM with thin-walled electrodes, short-circuits and arcing discharges occur, as a result of low efficiency in removing debris and bubble gas from the gap. Furthermore, unstable discharges can cause increases in tool wear and shape deviation of the machined parts. In order to characterize the influence of the type of electrode material and EDM parameters on the deep slot machining of high-thermal-conductivity tool steel (HTCS), experimental studies were conducted. An analytical and experimental investigation is carried out on the influence of EDM parameters on discharge current and pulse-on-time on the tool wear (TW), surface roughness (Ra), slot width (S)-dimension of the cavity, and material removal rate (MRR). The analyses of the EDS spectrum of the electrode indicate the occurrence of the additional carbon layer on the electrode. Carbon deposition on the anode surface can provide an additional thermal barrier that reduces electrode wear in the case of the copper electrode but for graphite electrodes, uneven deposition of carbon on the electrode leads to unstable discharges and leads to increase tool wear. The response surface methodology (RSM) was used to build empirical models of the influence of the discharge current I and pulse-on-time t_on on Ra, S, TW, and MRR. Analysis of variance (ANOVA) was used to establish the statistical significance parameters. The calculated contribution indicated that the discharge current had the most influence (over 70%) on the Ra, S, TW, and MRR, followed by the discharge time. Multicriteria optimization with Derringer's function was then used to minimize the surface roughness, slot width, and TW, while maximizing MRR. A validation test confirms that the maximal error between the predicted and obtained values did not exceed 7%.

Evaluation of Prediction Models of the Microwire EDM Process of Inconel 718 Using ANN and RSM Methods

Precise machining of micro parts from difficult-to-cut materials requires using advanced technology such as wire electrical discharge machining (WEDM). In order to enhance the productivity of micro WEDM, the key role is understanding the influence of process parameters on the surface topography and the material's removal rate (MRR). Furthermore, effective models which allow us to predict the influence of the parameters of micro-WEDM on the qualitative effects of the process are required. This paper influences the discharge energy, time interval, and wire speed on the surface topography's properties, namely Sa, Sk, Spk, Svk, and MRR, after micro-WEDM of Inconel 718 were described. Developed RSM and ANN model of the micro-WEDM process, showing that the discharge energy had the main influence (over 70%) on the surface topography's parameters. However, for MRR, the time interval was also significant. Furthermore, a reduction in wire speed can lead to a decrease in the cost process and have a positive influence on the environment and sustainability of the process. Evaluation of developed prediction models of micro-WEDM of Inconel 718 indicates that ANN had a lower value for the relative error compared with the RSM models and did not exceed 4%.

Experimental Investigation of Technological Indicators and Surface Roughness of Hastelloy C-22 after Electrical Discharge Machining Using POCO Graphite Electrodes

Modern industry is focused on looking for new and effective technologies to manufacture complex shapes from alloys based on nickel and chromium. One of the materials widely used in the chemical and aerospace industry is Hastelloy C-22. This material is difficult to machine by conventional methods, and in many cases, unconventional methods are used to manufacture it, such as electrical discharge machining (EDM). In the EDM process, the material is removed by electrical discharges between a workpiece and a tool electrode. The physical and mechanical properties of the tool electrodes have a direct impact on the process efficiency, machining accuracy, and surface roughness. Currently, there has been a significant increase in the use of graphite as a material for tool electrodes due to the low purchase cost of the raw material, good machinability, and high sublimation temperature. In this work, an experimental investigation of the influence of the grain size of the graphite tool electrode on material removal rate (MRR), tool wear rate (TWR), and surface roughness (Ra) of Hastelloy C-22 was carried out. Two POCO graphite tool electrodes with a grain size of 1 µm (AF-5) and 10 µm (S-180) were used. Based on the experimental studies, empirical models describing the influence of machining parameters on technological indicators and the condition of the surface texture were determined. The research indicates that graphite with a larger grain provides higher process efficiency with high relative wear of the tool electrode. The lowest surface roughness was obtained for graphite with a smaller grain size (AF-5). The analysis of the machining parameters proves that the discharge current and pulse duration are the main factors determining the MRR and Ra values for both AF-5 and S-180 graphite. The time interval is the dominant parameter with regard to the relative wear of the graphite electrode.