Empirical Investigations during WEDM of Ni-27Cu-3.15Al-2Fe-1.5Mn Based Superalloy for High Temperature Corrosion Resistance Applications

Aggarwal, Vivek; Pruncu, Catalin I.; Singh, Jujhar; Sharma, Shubham; Pimenov, Danil Yurievich

doi:10.3390/ma13163470

Cited by 57 publications

(30 citation statements)

References 25 publications

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“…The maximum MRR of 0.662 mg/s is obtained at current of 5 A. An increase in current level from low to high increase the breakdown voltage and raise its spark energy [36,37] as given by the Equation ( 6). Due to higher E s , the high current results in melting and vaporization of more volume of material [41,42].…”

Section: The Effect Of Current and Wire Speed On Mrrmentioning

confidence: 99%

“…Considering these factors, an attempt is made in this work to investigate the effects of wire-EDM process parameters such as current, pulse-on and pulse-off time, wire speed and voltage on MRR and optimize these settings to improve the productivity in terms of MRR. Although, artificial neural networkbased optimization methods such as fuzzy AHP-ARAS [34], genetic algorithm [35], particle swarm, moth-flame and Grass-Hooper optimization [36] methods are more attractive tools of optimization for the experiments with large data sets, for limited experimental trails as in this work, Taguchi and response surface [37] methods are more viable methods. Therefore, this works adopts Taguchi method for optimization of MRR and to develop the regression model to predict the MRR.…”

Section: Introductionmentioning

confidence: 96%

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Optimization and Modeling of Material Removal Rate in Wire-EDM of Silicon Particle Reinforced Al6061 Composite

et al. 2021

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The mechanical, physical and interfacial properties of aluminum alloys are improved by reinforcing the silicon carbide particles (SiCp). Machinability of such alloys by traditional methods is challenging due to higher tool wear and surface roughness. The objective of research is to investigate the machinability of SiCp reinforced Al6061 composite by Wire-Electrical Discharge Machining (wire-EDM). The effect of wire-EDM parameters namely current (I), pulse-on time (Ton), wire-speed (Ws), voltage (Iv) and pulse-off time (Toff) on material removal rate (MRR) is investigated and their settings are optimized for achieving the high MRR. The experiments are designed by using Taguchi L16 orthogonal arrays. The MRR obtained at different experiments are analyzed using statistical tools. It is observed that all the chosen process parameters showed significant influence of on the MRR with contribution of 27.39%, 22.08%, 21.32%, 15.76% and 12.94% by I, Iv, Toff, Ton and Ws, respectively. At optimum settings, the Wire-EDM resulted in MRR of 65.21 mg/min and 62.41 mg/min for samples with 4% and 8% SiCp. The results also indicated reinforcing SiCp upto 8% showed marginally low influence on MRR. Microstructural investigation of the cut surface revealed the presence of craters with wave pattern on its surface. The top surface of the crater is featured by the recast layers connecting adjacent craters. Further, the statistical model is developed using linear regression to predict the MRR (?2—73.65%) and its predicting accuracy is verified by the confirmation trials. The statistical model is useful for predicting the MRR for different settings of the process parameters. The optimized settings can be used to improve the machining productivity by increasing the MRR while machining of Al6061-SiCp (upto 8 wt. %) alloy by wire-EDM industries.

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Section: The Effect Of Current and Wire Speed On Mrrmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 96%

Optimization and Modeling of Material Removal Rate in Wire-EDM of Silicon Particle Reinforced Al6061 Composite

et al. 2021

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“…Through analysis of the influence between pulse type and process performance indicators, it showed that MRR and TWR values increased as the number of normal pulses grew while the TWR decreased in the condition of increasing in arcs and delayed pulses [ 38 ]. Moreover, it was found that cutting rate and surface roughness were affected significantly by input parameters (Ton, Toff, SV, WF) during WEDM process of Ni-27Cu-3.15Al-2Fe-1.5Mn, and the empirical relations between them were concluded by Aggarwal et al [ 39 ]. Gurupavan et al [ 40 ] proposed a machine vision system which can provide wire electrode status and workpiece surface texture information in WEDM of aluminum silicon nitride (AlSi3N4) composite material via acquire the images of wire electrode and machined surface specimens using the machine vision system.…”

Section: Introductionmentioning

confidence: 99%

Spark Analysis Based on the CNN-GRU Model for WEDM Process

et al. 2021

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Wire electrical discharge machining (WEDM), widely used to fabricate micro and precision parts in manufacturing industry, is a nontraditional machining method using discharge energy which is transformed into thermal energy to efficiently remove materials. A great amount of research has been conducted based on pulse characteristics. However, the spark image-based approach has little research reported. This paper proposes a discharge spark image-based approach. A model is introduced to predict the discharge status using spark image features through a synchronous high-speed image and waveform acquisition system. First, the relationship between the spark image features (e.g., area, energy, energy density, distribution, etc.) and discharge status is explored by a set of experiments). Traditional methods have claimed that pulse waveform of “short” status is related to the status of non-machining while through our research, it is concluded that this is not always true by conducting experiments based on the spark images. Second, a deep learning model based on Convolution neural network (CNN) and Gated recurrent unit (GRU) is proposed to predict the discharge status. A time series of spark image features extracted by CNN form a 3D feature space is used to predict the discharge status through GRU. Moreover, a quantitative labeling method of machining state is proposed to improve the stability of the model. Due the effective features and the quantitative labeling method, the proposed approach achieves better predict result comparing with the single GRU model.

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“…This process is suitable for the machining of high-strength and high ductility alloys, as it does not cause any distortion during machining. However, this process is quite time-consuming as it has a very slow material removal rate and has high energy consumption [5,6]. Therefore, it would be quite useful to employ other types of processes in the production of molds and mold inserts, made from these copper-based alloys, especially copper-beryllium.…”

Section: Introductionmentioning

confidence: 99%

Wear Behavior of Uncoated and Coated Tools in Milling Operations of AMPCO (Cu-Be) Alloy

et al. 2021

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Copper-Beryllium alloys have excellent wear resistance and high mechanical properties, they also possess good electrical and thermal conductivity, making these alloys very popular in a wide variety of industries, such as aerospace, in the fabrication of tools for hazardous environments and to produce injection molds and mold inserts. However, there are some problems in the processing of these alloys, particularly when these are subject to machining processes, causing tools to deteriorate quite rapidly, due to material adhesion to the tool’s surface, caused by the material’s ductile nature. An assessment of tool-wear after machining Cu-Be alloy AMPCOLOY 83 using coated and uncoated tools was performed, offering a comparison of the machining performance and wear behavior of solid-carbide uncoated and DLC/CrN multilayered coated end-mills with the same geometry. Multiple machining tests were conducted, varying the values for feed and cutting length. In the initial tests, cutting force values were registered. The material’s surface roughness was also evaluated and the cutting tools’ edges were subsequently analyzed, identifying the main wear mechanisms and how these developed during machining. The coated tools exhibited a better performance for shorter cutting lengths, producing a lower degree of roughness on the surface on the machined material. The wear registered for these tools was less intense than that of uncoated tools, which suffered more adhesive and abrasive damage. However, it was observed that, for greater cutting lengths, the uncoated tool performed better in terms of surface roughness and sustained wear.

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Empirical Investigations during WEDM of Ni-27Cu-3.15Al-2Fe-1.5Mn Based Superalloy for High Temperature Corrosion Resistance Applications

Cited by 57 publications

References 25 publications

Optimization and Modeling of Material Removal Rate in Wire-EDM of Silicon Particle Reinforced Al6061 Composite

Optimization and Modeling of Material Removal Rate in Wire-EDM of Silicon Particle Reinforced Al6061 Composite

Spark Analysis Based on the CNN-GRU Model for WEDM Process

Wear Behavior of Uncoated and Coated Tools in Milling Operations of AMPCO (Cu-Be) Alloy

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