Machining
A. Mehrvar; AR. Mirak; M. Motamedi
Abstract
Electrochemical machining (ECM) is an effective method for machining CMSX-4 superalloy, a single-crystal nickel-based superalloy, due to its unique performance in metal machining. The microstructure of this superalloy consists of three phases: gamma (γ), gamma prime (γ'), and carbide. The ...
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Electrochemical machining (ECM) is an effective method for machining CMSX-4 superalloy, a single-crystal nickel-based superalloy, due to its unique performance in metal machining. The microstructure of this superalloy consists of three phases: gamma (γ), gamma prime (γ'), and carbide. The gamma prime phase is distributed cubically and homogeneously in the gamma field without any boundaries. It is essential to maintain this microstructure after the production process. In the present study, ECM was performed on a CMSX-4 superalloy workpiece. The microstructure of the workpiece was then investigated before and after ECM using scanning electron microscopy and energy-dispersive spectroscopy analysis from two sides. The results showed that no changes were observed in the CMSX-4 microstructure after ECM process. The single-crystal structure and the distribution of the gamma prime phase were maintained after this machining process, indicating that ECM is an effective machining method for CMSX-4 superalloy without compromising its critical microstructural features.
Machining
Mohammad Reza Shabgard; Reza Rostami Heshmatabad
Abstract
In this study, relationship between effect of machining parameters on machining characteristics and surface morphology was studied in electrochemical machining (ECM). The characteristics were Material Removal Rates (MRR), Over Cut (OC), Surface Roughness (SR) and surface morphology. The results show ...
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In this study, relationship between effect of machining parameters on machining characteristics and surface morphology was studied in electrochemical machining (ECM). The characteristics were Material Removal Rates (MRR), Over Cut (OC), Surface Roughness (SR) and surface morphology. The results show that MRR is increased by increasing current but OC is decreased. Increasing concentration causes to increase MRR, OC and SR. Also, the analysis of surface morphology shows that the electrolyte type affects the dissolution mechanism and surface layer formation in ECM. There are cavities in NaCl and KCl that their diameter, depth and distribution on the machined surface are changed by parameters and their diameters were 4μm to 9μm. Increasing ion concentration causes to enhance the diameter size and depth of created cavities on work piece but their uniform distribution decreases, while the current has a reverse effect on them. On the other hand, an oxide layer is formed on the machined surface in NaNO3 and by increasing current and concentration, breaking and the anion cavity effect are increased on this layer. So, increasing the MRR and SR is due to this phenomenon in NaNO3.
Machining
A. Amith Gadagi; B. Chandrashekar Adake
Abstract
In a turning process, it is essential to predict and choose appropriate process parameters to get a component’s proper surface roughness (Ra). In this paper, the prediction of Ra through the artificial neural network (ANN), multiple regression analysis (MRA), and random forest method (machine learning) ...
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In a turning process, it is essential to predict and choose appropriate process parameters to get a component’s proper surface roughness (Ra). In this paper, the prediction of Ra through the artificial neural network (ANN), multiple regression analysis (MRA), and random forest method (machine learning) are made and compared. Using the process variables such as feed rate, spindle speed, and depth of cut, the turning process of glass fiber-reinforced plastic (GFRP) composite specimens is conducted on a conventional lathe with the help of a single-point HSS turning tool brazed with a carbide tip. The surface roughness of turned GFRP components is measured experimentally using the Talysurf method. By utilizing Taguchi's L27 array, the experiments are carried out and the experimental results are utilized in the development of MRA, ANN, and random forest method models for predicting the Ra. It is observed that the mean absolute error (MAE) of MRA, ANN and random forest for the training cases are found to be 39.33%, 0.56%, and 24.88%, respectively whereas for the test cases MAE is 54.34%, 2.59%, and 24.88% for MRA, ANN, and random forest, respectively.
Machining
S. L. N. Jayasimha; Ganapathy Bawge; H. P. Raju
Abstract
Traditional methods of finishing like grinding, lapping, and honing are limited to finishing of vital shapes such as flat and circular. These conventional methods are lagging for processing components that are fabricated by hard materials, involving complicated profiles in particular. Hence, it is essential ...
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Traditional methods of finishing like grinding, lapping, and honing are limited to finishing of vital shapes such as flat and circular. These conventional methods are lagging for processing components that are fabricated by hard materials, involving complicated profiles in particular. Hence, it is essential to explore a finishing process, which addresses wide applications, better accuracy, higher efficiency, consistent quality and economy in finishing complex shaped parts. So, a new precision finishing process like extrusion honing has been implemented for polishing from several microns to the nano level. This work aims to assess the influence of a number of abrasive media passes on the surface integrity of aluminum, copper, and titanium grade-2 materials. The study has been performed by adopting an abrasive 36 mesh size with a concentration of 40% followed by 10 abrasive media passes. The influence of these process parameters has been studied in analyzing the roughness characteristics Ra, Rmax, Rz, and Rmax/Ra and the nature of surface induced by SEM characterization for the metals of consideration using the extrusion honing process.
Machining
Nhu-Tung Nguyen; Dong Van Pham; Cuong Duc Pham; Dung Hoang Tien
Abstract
Cutting force coefficients (CFCs) are the most important factors in the prediction of CFs (CFs) and other machining characteristics (MCs). This study was conducted to model the CFs and MCs in the milling process based on the calculated values of CFCs. From the relationship of average values of CFs and ...
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Cutting force coefficients (CFCs) are the most important factors in the prediction of CFs (CFs) and other machining characteristics (MCs). This study was conducted to model the CFs and MCs in the milling process based on the calculated values of CFCs. From the relationship of average values of CFs and feed rate, CFCs were determined and used to predict dynamic CFs (DCFs) in the flat milling process. In static models, the average values of CFs were presented as a linear regression of feed rate. The DCFs and other MCs were modeled depending on the cutting parameters, cutter geometry, CFCs, and structure parameters of the machine-tool system. By performing the flat-milling process of gray cast iron GG25 using HSS-Co solid tool, the average CFs were modeled as the linear regression of feed rate with large determination coefficients (R2 > 93%). Besides, all CFCs of a pairs of tool and workpiece for each cutting type were successfully determined based on the measured data of CFs from the experimental process. Moreover, the proposed models of DCFs were successfully verified based on the compared results between the predicted CFs and measured CFs in several cutting tests with different cutting parameters. The proposed models of cutting force in this study were successfully used to predict the DCFs and several MCs in milling processes using a flat milling tool. And can be used to design and develop tools and machine in industrial manufacturing.
Machining
P. Kumar; M. Gupta; V. Kunar
Abstract
The present research attempts to analyze the surface topography of WEDMed Inconel 825 concerning surface crack density (SCDi) and recast layer thickness (RCLt). Formation of cracks, recast layer, and heat-affected zone are the major issues in determining the final performance of the WEDM machined sample. ...
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The present research attempts to analyze the surface topography of WEDMed Inconel 825 concerning surface crack density (SCDi) and recast layer thickness (RCLt). Formation of cracks, recast layer, and heat-affected zone are the major issues in determining the final performance of the WEDM machined sample. In this study, WEDM characteristics viz. pulse on time (Ton), pulse off time (Toff), gap voltage (SV), peak current (IP), wire tension (WT), and wire feed (WF) are optimized for the response SCDi and RCLt by response surface methodology. The outcome manifests that the topography of the machined surface becomes more rougher at the increased value of Ton, IP, and SV. RSM emerges as a great tool in the development of a predicted model based on the desirability approach and finding optimal parametric combinationm which results in reduced SCDi and RCLt. At the optimum combination of process parameters, i.e., 109 machine unit Ton, 36 machine unit Toff, 54 V SV, 120A IP, 9 machine unit WT and 7 m/min WF, the values obtained for SCDi and RCLt are 0.00160 μm/μm2 and 20.991μm, respectively with an error of less than 5%.
Machining
P. Kumar; M. Gupta; V. Kumar
Abstract
With the increased diversity of the customer demand and complexity of the product, Inconel 825 is widely used to meet the actual needs, especially in the aerospace industry. It is difficult-to-cut material because of its high toughness and hardness. The present research attempts to optimize the process ...
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With the increased diversity of the customer demand and complexity of the product, Inconel 825 is widely used to meet the actual needs, especially in the aerospace industry. It is difficult-to-cut material because of its high toughness and hardness. The present research attempts to optimize the process parameters of wire electric discharge machining during the cutting operation of Inconel 825. The wire electric discharge machining characteristics such as pulse-on time, pulse-off time, spark gap voltage, peak current, wire tension, wire feed are taken into consideration. The performance was measured in terms of material removal rate, surface roughness, and wire wear ratio. The central composite design of response surface methodology at an α value of ± 2 was employed to establish the mathematical model between process parameters and performance measures. A multi-objective particle swarm optimization algorithm has been used to find the optimal solutions called Pareto optimal solutions. It uses the concept of dominance to find the non dominated set in the entire population and the crowding distance approach to finding the best Pareto optimal solutions with a good diversity of objectives. The confirmation experiments of the multi-objective particle swarm optimization algorithm show a significant improvement in material removal rate (27.934 to 31.687 mm2/min), surface roughness (2.689 to 2.448μm), and wire wear ratio (0.027 to 0.030). SEM micrograph studies showed the number of cracks, pockmarks, craters, and pulled out material on the workpiece and wire electrode surface. Energy Dispersive X-ray analysis is performed to investigate the presence of elements on the work surface other than the base material.
