This paper proposes development of optimized heterogeneous ensemble models for prediction of responses based on given sets of input parameters for wire electrical discharge machining (WEDM) processes, which have found immense applications in many of the present-day manufacturing industries because of their ability to generate complicated 2D and 3D profiles on hard-to-machine engineering materials. These ensembles are developed combining predictions of the three base models, i.e. random forest, support vector machine and ridge regression. These three base models are first framed utilizing the training datasets, providing predictions for all the responses under consideration. Based on these predictions, two optimization problems are formulated for each of the responses, while minimizing root mean squared error and mean absolute error, for subsequent development of two optimized ensembles whose predictions are the weighted sum of the predictions of the base models. The prediction performance of all the five models is ascertained through nine statistical metrics, after which a cumulative quality loss-based multi-response signal-to-noise (MRSN) ratio for each model is computed, for each of the responses, where a higher MRSN ratio indicates greater accuracy in prediction. This study is conducted using two experimental datasets of WEDM process. Overall, the optimized ensemble models having higher MRSN ratios than the base models are indicated to deliver better prediction accuracy.

• Klíčová slova
• Multi-response S/N ratio, Optimized heterogeneous ensemble, Prediction performance, Response, Wire electrical discharge machining,
• Publikační typ
• časopisecké články MeSH

Unconventional wire electrical discharge machining technology (WEDM) is a key machining process, especially for machining newly emerging materials, as there are almost no restrictions (only at least minimal electrical conductivity) in terms of demands on the mechanical properties of the workpiece or the need to develop new tool geometry. This study is the first to present an analysis of the machinability of newly developed high entropy alloys (HEAs), namely FeCoCrMnNi and FeCoCrMnNiC0.2, using WEDM. The aim of this study was to find the optimal setting of machine parameters for the efficient production of parts with the required surface quality without defects. For this reason, an extensive design of experiments consisting of 66 rounds was performed, which took into account the influence of five input factors in the form of pulse off time, gap voltage, discharge current, pulse on time, and wire speed on cutting speed and the quality of the machined surface and its subsurface layer. The analysis of topography, morphology, subsurface layers, chemical composition analysis (EDX), and lamella analysis using a transmission electron microscope (TEM) were performed. An optimal setting of the machine parameters was found, which enables machining of FeCoCrMnNi and FeCoCrMnNiC0.2 with the required surface quality without defects.

• Klíčová slova
• WEDM, design of experiment, high entropy alloy, machining parameters, wire electrical discharge machining,
• Publikační typ
• časopisecké články MeSH

Nimonic alloy is difficult to machine using traditional metal cutting techniques because of the high cutting forces required, poor surface integrity, and tool wear. Wire electrical discharge machining (WEDM) is used in a number of sectors to precisely machine complex forms of nickel-based alloy in order to attempt to overcome these challenges and provide high-quality products. The Taguchi-based design of experiments is utilized in this study to conduct the tests and analyses. The gap voltage (GV), pulse-on time (Ton), pulse-off time (Toff), and wire feed (WF), are considered as the variable process factors. GRA is used for the WEDM process optimization for the Nimonic-263 superalloy, which has multiple performance qualities including the material removal rate (MRR), surface roughness (SR), and kerf width (KW). ANOVA analysis was conducted to determine the factors' importance and influence on the output variables. Multi objective optimization techniques were employed for assessing the machining performances of WEDM using GRA. The ideal input parameter combinations were determined to be a gap voltage (GV) of 40 V, a pulse-on time (Ton) of 8 µs, a pulse-off time (Toff) of 16 µs, and a wire feed (WF) of 4 m/min. A material removal rate of 8.238 mm3/min, surface roughness of 2.83 µm, and kerf width of 0.343 mm were obtained. The validation experiments conducted also demonstrated that the predicted and experimental values could accurately forecast the responses.

• Klíčová slova
• Taguchi—grey approach, WEDM, kerf width, material removal rate, superalloy, surface roughness,
• Publikační typ
• časopisecké články MeSH

The unconventional technology wire electrical discharge machining is a highly used technology for producing precise and indented shaped parts of all materials that are at least electrically conductive. Its wide use makes this technology applicable in almost all branches of industry, even in the automotive industry, where the abrasion resistant material under investigation Hardox 400 steel is widely used for the manufacturing of truck bodies. The aim of this study was a comprehensive analysis of the machinability of this material using WEDM employing a 33-round experiment. Based on the change in machine parameters (pulse off time, gap voltage, discharge current, pulse on time, and wire feed), the cutting speed, the topography of machined surfaces, and the chemical composition of the workpiece surface, the morphology and condition of the subsurface layer including lamella production and a subsequent determination of the distribution of individual elements in the given area were analyzed. It has been found that during the machining of this steel, many defects occur in the subsurface layer of the material in the form of cracks with a depth of up to 22 µm and burned cavities. However, by appropriately adjusting the machine parameters, it was possible to completely remove these cracks.

• Klíčová slova
• WEDM, cavities, cracks, electrical discharge machining, hardox,
• Publikační typ
• časopisecké články MeSH

Wire Electrical Discharge Machining (WEDM) technology represents an unconventional but vital manufacturing technology in many different industrial branches. The automotive industry and its many significant requirements bring the need to manufacture inserts and mould segments for plastic injections from Albromet W130 material, with a required roughness, Ra, from 4.5 to 5 µm so that subsequent profile etching can be eliminated. A planned experiment of 60 rounds was carried out to discover the optimal machining parameters, namely, the pulse-off time, gap voltage, discharge current, pulse-on time, and wire speed in order for the thickness of 10 to 100 mm (after 10 mm) to demonstrate the required roughness. The goal was to evaluate the surface roughness, maximise the cutting speed, and manufacture it without surface or subsurface defects. The evaluation of the planned experiment led to the establishment of optimised WEDM machining parameters with which thicknesses of 10-100 mm will always be produced with the required roughness, Ra, from 4.5 to 5 µm and with the highest possible cutting speed. It was also proven that the machining does not lead to surface or subsurface defects, and thus, the service life of the manufactured parts will not be affected.

• Klíčová slova
• Albromet W130, WEDM, design of experiment, surface roughness, thicknesses, wire electrical discharge machining,
• Publikační typ
• časopisecké články MeSH

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%.

• Klíčová slova
• ANN, Inconel, RSM, surface topography, wire electrical discharge machining,
• Publikační typ
• časopisecké články MeSH

The unconventional technology of wire electrical discharge machining is widely used in all areas of industry. For this reason, there is always an effort for efficient machining at the lowest possible cost. For this purpose, the following comprehensive study has been carried out to optimize the machining of the copper alloy Ampcoloy 35, which is particularly useful in plastic injection moulds. Within the study, a half-factor experiment of 25-1 with 10 axial points and seven central points of a total of 33 rounds was carried out, which was focused on the response monitoring of the input factors in the form of the machine parameters setup: gap voltage, pulse on time, pulse off time, discharge current, and wire speed. Based on the study of the response in the form of cutting speed and surface topography, their statistical models were created, while the optimal setting of machine parameters was determined to maximize the cutting speed and minimize the topography parameters. Further, a detailed cross-sectional analysis of surface and subsurface layer morphology was performed using electron microscopy including chemical composition analysis. In order to study microstructural changes in the material at the atomic level, a lamella was created, which was then studied using a transmission electron microscope.

• Klíčová slova
• WEDM, ampcoloy, design of experiment, electrical discharge machining, machining parameters,
• Publikační typ
• časopisecké články MeSH

LM5 alloy is suitable for metal castings for marine and aesthetic uses due to its admirable resistance to corrosion. In order to make intricate shapes in the LM5 alloy, this study intends to assess the impact of Wire Electric Discharge Machining process variables, like Pulse on Time (Ton), Pulse off Time (Toff), Gap Voltage (GV) and Wire Feed (WF) on responses like Material Removal Rate (MRR), Surface Roughness (SR), and Kerf Width (Kw). The LM5 aluminium alloy plate was produced through stir casting process. SEM, EDAX and XRD images confirm the LM5 Al alloy's microstructure and crystal structure. WEDM studies were conducted using design of experiments approach based on L9 orthogonal array and analysed using Taguchi's Signal to Noise Ratio (S/N) analysis. Pulse on Time has the greatest statistical effects on MRR (68.25%), SR (79.46%) and kerf (81.97%). In order to assess the surface integrity of the WEDM machined surfaces, the SEM study on the topography was conducted using the optimum surface roughness process variables: Ton 110 μs, Toff 50 μs, GV 40 V, and WF 9 m/min. SEM images show the recast layer and its thickness. The average absolute error for MRR is 1.69%, SR is 3.89% and kerf is 0.88%, based on mathematical (linear regression) models. The Taguchi's Signal to Noise ratio analysis is the most appropriate for single objective optimization of responses.

• MeSH
• hliník * chemie   MeSH
• mikroskopie elektronová rastrovací MeSH
• povrchové vlastnosti * MeSH
• slitiny * chemie   MeSH
• testování materiálů MeSH
• Publikační typ
• časopisecké články MeSH
• Názvy látek
• hliník * MeSH
• slitiny * MeSH

Wire electrical discharge machining (WEDM) is an unconventional machining technology that can be used to machine materials with minimum electrical conductivity. The technology is often employed in the automotive industry, as it makes it possible to produce mold parts of complex shapes. Copper alloys are commonly used as electrodes for their high thermal conductivity. The subject of this study was creating mathematical models for the machining optimization of Ampcoloy 35 with different thicknesses (ranging from 5 to 160 mm with a step of 5 mm) using WEDM to improve the surface properties of the mold parts. The Box-Behnken type experiment was used with a total of 448 samples produced. The following machining parameters were altered over the course of the experiment: the pulse on and off time, discharge current, and material thickness. The cutting speed was measured, and the topography of the machined surfaces in the center and at the margins of the samples was analyzed. The morphology and subsurface layer were also studied. What makes this study unique is the large number of the tested thicknesses, ranging from 5 to 160 mm with a step of 5 mm. The contribution of this study to the automotive industry and plastic injection mold production is, therefore, significant. The regression models for the cutting speed and surface topography allow for efficient defect-free machining of Ampcoloy 35 of 5-160 mm thicknesses, both on the surface and in the subsurface layer.

• Klíčová slova
• Ampcoloy, WEDM, cutting speed, design of experiment, machining parameters, surface topography,
• Publikační typ
• časopisecké články MeSH

This work intended to improve the precision and machining efficiency of Magnesium alloy (Mg-Li-Sr) using Wire electrical discharge machining (WEDM). Mg-Li-Sr alloy is prepared through inert gas assisted stir casting route. Taguchi approach is used for experimental design for WEDM parameter such as pulse OFF time, pulse ON time, wire feed rate, servo voltage and current. L27 orthogonal array is considered to understand the influence of control parameter such as Kerf Width (KW), Roughness of the surface (Ra), Material Removal Rate (MRR). Integration of the CRITIC (Criteria Importance Through Intercriteria Correlation) -WASPAS (Weighted Aggregated Sum Product Assessment) multi-objective optimization method with Artificial Neural Network (ANN) modelling with different network structure for prediction and optimization is a novel approach that significantly improves prediction accuracy and machining outcomes. The developed ANN model with better R2 value of 99.9 % has better ability for prediction while correlated with formulated conventional regression equation. The error percentages identified through confirmation tests for regression and ANN models are Ra - 8.5 % and 3.4 %, MRR - 5.9 % and 2.8 %, KW - 6.7 % and 2.2 % respectively. Optimal output response attained by CRITIC-WASPAS approach yields surface roughness of 4.62 μm, material removal rate of 0.073 g/min and kerf width of 0.388 μm.

• Klíčová slova
• ANN, CRITIC-WASPAS, Mg-Li alloy, Modelling and optimization, WEDM,
• Publikační typ
• časopisecké články MeSH