Effect of WEDM Process Parameters on Surface Morphology of Nitinol Shape Memory Alloy

Analyzing the Relationship between the Chemical Composition and the Surface Finish of Alnico Alloys in EDM

The purpose of this study was to determine whether the chemical compositions of Alnico alloys had any effects on the electrical discharge machining (EDM) performance and the surface finish. This article compares the behavior of three different Alnico alloys in electrical discharge machining. The experiments were conducted under different conditions using a BP93L EDM machine (ZAP BP, Końskie, Poland), applying an additional rotary motion to the electrode. A Box-Behnken experimental design was employed to analyze the influence of three factors, i.e., the spark current, the pulse-on time, and the pulse-off time, at three levels for three Alnico alloys. The material removal rate (MRR) was calculated for the different process parameters. After the EDM, the surface roughness was studied using a Talysurf CCI Lite non-contact profiler (Taylor-Hobson, Leicester, UK). The next step of the experiments involved preparing metallographic specimens to be observed by means of scanning electron microscopy (SEM) and optical microscopy (OM). Measurements of the nanohardness were also performed. The experimental data were then analyzed using Statistica software version 10 (64-bit) to determine and graphically represent the relationships between the input and output parameters for the three Alnico alloys. The chemical compositions of the Alnico alloys affected the thickness of the white layer (higher cobalt content, lower white layer thickness) and the material removal rate. The higher the cobalt content, the thinner the white layer and the lower the material removal efficiency. Moreover, the cobalt content in Alnico alloys influenced the shape of the precipitates; these ranged from spheroidal (13% Co) to mix-shaped (21.3% Co) to flake-shaped (32.2%). The hardness of the resulting white layer was 874 HV at10 mN.

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.

Enhancing EDM Machining Precision through Deep Cryogenically Treated Electrodes and ANN Modelling Approach

The critical applications of difficult-to-machine Inconel 617 (IN617) compel the process to be accurate enough that the requirement of tight tolerances can be met. Electric discharge machining (EDM) is commonly engaged in its machining. However, the intrinsic issue of over/undercut in EDM complicates the achievement of accurately machined profiles. Therefore, the proficiency of deep cryogenically treated (DCT) copper (Cu) and brass electrodes under modified dielectrics has been thoroughly investigated to address the issue. A complete factorial design was implemented to machine a 300 μm deep impression on IN617. The machining ability of DCT electrodes averagely gave better dimensional accuracy as compared to non-DCT electrodes by 13.5% in various modified dielectric mediums. The performance of DCT brass is 29.7% better overall compared to the average value of overcut (OC) given by DCT electrodes. Among the non-treated (NT) electrodes, the performance of Cu stands out when employing a Kerosene-Span-20 modified dielectric. In comparison to Kerosene-Tween-80, the value of OC is 33.3% less if Kerosene-Span-20 is used as a dielectric against the aforementioned NT electrode. Finally, OC's nonlinear and complex phenomena are effectively modeled by an artificial neural network (ANN) with good prediction accuracy, thereby eliminating the need for experiments.

Optimization and Microstructural Studies on the Machining of Inconel 600 in WEDM Using Untreated and Cryogenically Treated Zinc Electrodes

Any industry that manufactures dies, punches, molds, and machine components from difficult-to-cut materials, such as Inconel, titanium, and other super alloys, largely relies on wire electrical discharge machining (WEDM). In the current study, the effect of the WEDM process parameters on Inconel 600 alloy with untreated zinc and cryogenically treated zinc electrodes was investigated. The controllable parameters included the current (IP), pulse-on time (Ton), and pulse-off time (Toff), whereas the wire diameter, workpiece diameter, dielectric fluid flow rate, wire feed rate, and cable tension were held constant throughout the experiments. The significance of these parameters on the material removal rate (MRR) and surface roughness (Ra) was established using the analysis of the variance. The experimental data acquired using the Taguchi analysis were used to analyze the level of influence of each process parameter on a particular performance characteristic. Their interactions with the pulse-off time were identified as the most influential process parameter on the MRR and Ra in both cases. Furthermore, a microstructural analysis was also performed via scanning electron microscopy (SEM) to examine the recast layer thickness, micropores, cracks, depth of metal, pitching of metal, and electrode droplets over the workpiece surface. In addition, energy-dispersive X-ray spectroscopy (EDS) was also carried out for the quantitative and semi-quantitative analyses of the work surface and electrodes after machining.

Mathematical Models for Machining Optimization of Ampcoloy 35 with Different Thicknesses Using WEDM to Improve the Surface Properties of Mold Parts

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.

Experimental Investigations and Effect of Nano-Powder-Mixed EDM Variables on Performance Measures of Nitinol SMA

In the present study, the effect of alumina (Al₂O₃) nano-powder was investigated for the electrical discharge machining (EDM) of a Nitinol shape memory alloy (SMA). In addition to the nano-powder concentration, other parameters of pulse-on-time (T_on), pulse-off-time (T_off), and current were selected for the performance measures of the material removal rate (MRR), surface roughness (SR), and tool wear rate (TWR) of Nitinol SMA. The significance of the design variables on all the output measures was analyzed through an analysis of variance (ANOVA). The regression model term has significantly impacted the developed model terms for all the selected measures. In the case of individual variables, Al₂O₃ powder concentration (PC), T_off, and T_on had significantly impacted MRR, TWR, and SR measures, respectively. The influence of EDM variables were studied through main effect plots. The teaching-learning-based optimization (TLBO) technique was implemented to find an optimal parametric setting for attaining the desired levels of all the performance measures. Pursuant to this, the optimal parametric settings of current at 24 A, PC at 4 g/L, T_off at 10 µs, and T_on of 4 µs have shown optimal input parameters of 43.57 mg/min for MRR, 6.478 mg/min for TWR, and 3.73 µm for SR. These results from the TLBO technique were validated by performing the experiments at the optimal parametric settings of the EDM process. By considering the different user and application requirements, 40 Pareto points with unique solutions were generated. Lastly, scanning electron microscopy (SEM) performed the machined surface analysis. The authors consider this to be very beneficial in the nano-powder-mixed EDM process for appropriate manufacturing operations.

Parametric Optimization and Influence of Near-Dry WEDM Variables on Nitinol Shape Memory Alloy

Nitinol-shape memory alloys (SMAs) are widely preferred for applications of automobile, biomedical, aerospace, robotics, and other industrial area. Therefore, precise machining of Nitinol SMA plays a vital role in achieving better surface roughness, higher productivity and geometrical accuracy for the manufacturing of devices. Wire electric discharge machining (WEDM) has proven to be an appropriate technique for machining nitinol shape memory alloy (SMA). The present study investigated the influence of near-dry WEDM technique to reduce the environmental impact from wet WEDM. A parametric optimization was carried out with the consideration of design variables of current, pulse-on-time (T_on), and pulse-off-time (T_off) and their effect were studied on output characteristics of material removal rate (MRR), and surface roughness (SR) for near-dry WEDM of nitinol SMA. ANOVA was carried out for MRR, and SR using statistical analysis to investigate the impact of design variables on response measures. ANOVA results depicted the significance of the developed quadratic model for both MRR and SR. Current, and T_on were found to be major contributors on the response value of MRR, and SR, respectively. A teaching–learning-based optimization (TLBO) algorithm was employed to find the optimal combination of process parameters. Single-response optimization has yielded a maximum MRR of 1.114 mm³/s at T_on of 95 µs, T_off of 9 µs, current of 6 A. Least SR was obtained at T_on of 35 µs, T_off of 27 µs, current of 2 A with a predicted value of 2.81 µm. Near-dry WEDM process yielded an 8.94% reduction in MRR in comparison with wet-WEDM, while the performance of SR has been substantially improved by 41.56%. As per the obtained results from SEM micrographs, low viscosity, reduced thermal energy at IEG, and improved flushing of eroded material for air-mist mixture during NDWEDM has provided better surface morphology over the wet-WEDM process in terms of reduction in surface defects and better surface quality of nitinol SMA. Thus, for obtaining the better surface quality with reduced surface defects, near-dry WEDM process is largely suitable.

Multi-Response Optimization of Al2O3 Nanopowder-Mixed Wire Electrical Discharge Machining Process Parameters of Nitinol Shape Memory Alloy

Shape memory alloy (SMA), particularly those having a nickel-titanium combination, can memorize and regain original shape after heating. The superior properties of these alloys, such as better corrosion resistance, inherent shape memory effect, better wear resistance, and adequate superelasticity, as well as biocompatibility, make them a preferable alloy to be used in automotive, aerospace, actuators, robotics, medical, and many other engineering fields. Precise machining of such materials requires inputs of intellectual machining approaches, such as wire electrical discharge machining (WEDM). Machining capabilities of the process can further be enhanced by the addition of Al₂O₃ nanopowder in the dielectric fluid. Selected input machining process parameters include the following: pulse-on time (T_on), pulse-off time (T_off), and Al₂O₃ nanopowder concentration. Surface roughness (SR), material removal rate (MRR), and recast layer thickness (RLT) were identified as the response variables. In this study, Taguchi's three levels L₉ approach was used to conduct experimental trials. The analysis of variance (ANOVA) technique was implemented to reaffirm the significance and adequacy of the regression model. Al₂O₃ nanopowder was found to have the highest contributing effect of 76.13% contribution, T_on was found to be the highest contributing factor for SR and RLT having 91.88% and 88.3% contribution, respectively. Single-objective optimization analysis generated the lowest MRR value of 0.3228 g/min (at T_on of 90 µs, T_off of 5 µs, and powder concentration of 2 g/L), the lowest SR value of 3.13 µm, and the lowest RLT value of 10.24 (both responses at T_on of 30 µs, T_off of 25 µs, and powder concentration of 2 g/L). A specific multi-objective Teaching-Learning-Based Optimization (TLBO) algorithm was implemented to generate optimal points which highlight the non-dominant feasible solutions. The least error between predicted and actual values suggests the effectiveness of both the regression model and the TLBO algorithms. Confirmatory trials have shown an extremely close relation which shows the suitability of both the regression model and the TLBO algorithm for the machining of the nanopowder-mixed WEDM process for Nitinol SMA. A considerable reduction in surface defects owing to the addition of Al₂O₃ powder was observed in surface morphology analysis.

A Comparative Study on the Structure and Quality of SLM and Cast AISI 316L Samples Subjected to WEDM Processing

Additive manufacturing technologies are increasingly used in the production of semi-finished workpieces intended for further processing. This entails the need to investigate the machinability and final properties of such products. Comparative research on wire electrical discharge machining (WEDM) processes performed with two kinds of AISI 316L stainless steel workpieces is presented in this paper. The first workpiece was made by selective laser melting (SLM), while the second one was casting. Both working materials were cut with current values ranging from 8 to 72 amps. A comparison of roughness, structure and chemical composition of machined surfaces was performed between the two kinds of specimens. For the SLM sample, parameters of the cutting process that provide relatively low surface roughness (Ra ≤ 10 µm) with the simultaneous maximization of the process efficiency were determined. It was found that in the case of applying high current values (72 amp.), more favorable properties of the treated surface were obtained for the SLM sample than for the cast one.

Multi-Response Optimization of Abrasive Waterjet Machining of Ti6Al4V Using Integrated Approach of Utilized Heat Transfer Search Algorithm and RSM

Machining of Titanium alloys (Ti6Al4V) becomes more vital due to its essential role in biomedical, aerospace, and many other industries owing to the enhanced engineering properties. In the current study, a Box–Behnken design of the response surface methodology (RSM) was used to investigate the performance of the abrasive water jet machining (AWJM) of Ti6Al4V. For process parameter optimization, a systematic strategy combining RSM and a heat-transfer search (HTS) algorithm was investigated. The nozzle traverse speed (T_v), abrasive mass flow rate (A_f), and stand-off distance (S_d) were selected as AWJM variables, whereas the material removal rate (MRR), surface roughness (SR), and kerf taper angle (θ) were considered as output responses. Statistical models were developed for the response, and Analysis of variance (ANOVA) was executed for determining the robustness of responses. The single objective optimization result yielded a maximum MRR of 0.2304 g/min (at T_v of 250 mm/min, A_f of 500 g/min, and S_d of 1.5 mm), a minimum SR of 2.99 µm, and a minimum θ of 1.72 (both responses at T_v of 150 mm/min, A_f of 500 g/min, and S_d of 1.5 mm). A multi-objective HTS algorithm was implemented, and Pareto optimal points were produced. 3D and 2D plots were plotted using Pareto optimal points, which highlighted the non-dominant feasible solutions. The effectiveness of the suggested model was proved in predicting and optimizing the AWJM variables. The surface morphology of the machined surfaces was investigated using the scanning electron microscope. The confirmation test was performed using optimized cutting parameters to validate the results.

Integration of Fuzzy AHP and Fuzzy TOPSIS Methods for Wire Electric Discharge Machining of Titanium (Ti6Al4V) Alloy Using RSM

Titanium and its alloys exhibit numerous uses in aerospace, automobile, biomedical and marine industries because of their enhanced mechanical properties. However, the machinability of titanium alloys can be cumbersome due to their lower density, high hardness, low thermal conductivity, and low elastic modulus. The wire electrical discharge machining (WEDM) process is an effective choice for machining titanium and its alloys due to its unique machining characteristics. The present work proposes multi-objective optimization of WEDM on Ti6Al4V alloy using a fuzzy integrated multi-criteria decision-making (MCDM) approach. The use of MCDM has become an active area of research due to its proven ability to solve complex problems. The novelty of the present work is to use integrated fuzzy analytic hierarchy process (AHP) and fuzzy technique for order preference by similarity to ideal situation (TOPSIS) to optimize the WEDM process. The experiments were systematically conducted adapting the face-centered central composite design approach of response surface methodology. Three independent factors-pulse-on time (Ton), pulse-off time (Toff), and current-were chosen, each having three levels to monitor the process response in terms of cutting speed (VC), material removal rate (MRR), and surface roughness (SR). To assess the relevance and significance of the models, an analysis of variance was carried out. The optimal process parameters after integrating fuzzy AHP coupled with fuzzy TOPSIS approach found were Ton = 40 µs, Toff = 15 µs, and current = 2A.

Experimental Investigations and Pareto Optimization of Fiber Laser Cutting Process of Ti6Al4V

In the current study, laser cutting of Ti6Al4V was accomplished using Taguchi’s L9 orthogonal array (OA). Laser power, cutting speed, and gas pressure were selected as input process parameters, whereas surface roughness (SR), kerf width, dross height, and material removal rate (MRR) were considered as output variables. The effects of input variables were analyzed through the analysis of variance (ANOVA), main effect plots, residual plots, and contour plots. A heat transfer search algorithm was used to optimize the parameters for the single objective function including higher MRR, minimum SR, minimum dross, and minimum kerf. A multi-objective heat transfer search algorithm was used to create non-dominant optimal Pareto points, giving unique optimal solutions with the corresponding input parameters. For better understanding and ease of selection of input parameters in industry and by scientists, a Pareto graph (2D and 3D graph) is generated from the Pareto points.

The Effect of Powder Composition on the Microstructure and Corrosion Resistance of Laser Cladding 60NiTi Alloy Coatings on SS 316L

Two kinds of 60NiTi powders were prepared by pure Ni mixed with Ti powders, and 55NiTi alloy powder with pure Ni powder and both the powders were fully mixed by alcohol ball milling. Two kinds of coatings (denoted as 60Ni-40Ti and 55NiTi-5Ni) were prepared on a 316L stainless steel substrate by laser cladding. The microstructure, microhardness and electrochemical behavior of the prepared coatings were investigated extensively. The results show that 55NiTi-5Ni has a typical dendritic eutectic structure, but 60Ni-40Ti tends to form a eutectic network structure. The main phases in both coatings are (Ni, Fe)Ti and (Ni, Fe)3Ti; however, the (Ni, Fe)Ti phase is dominant in 55NiTi-5Ni, but the (Ni, Fe)3Ti phase is more prevalent in 60Ni-40Ti. The microhardness was significantly improved with the 316L stainless steel substrate, and the microhardness of 55NiTi-5Ni is slightly higher than 60Ni-40Ti. The corrosion resistance of the two coatings in 3.5 wt% NaCl solution also leads to significant improvements compared with the substrate, and the corrosion resistance of 55NiTi-5Ni was also increased. These different behaviors and characteristics might be related to the different microstructures. Uniform and fine eutectic structure in 55NiTi-5Ni coating lead to better performance, which is also conducive to the formation of the dense oxide film to improve corrosion resistance.

Synthesis and Characterization of Mechanical Properties and Wire Cut EDM Process Parameters Analysis in AZ61 Magnesium Alloy + B4C + SiC

Wire Cut Electric Discharge Machining (WCEDM) is a novel method for machining different materials with application of electrical energy by the movement of wire electrode. For this work, an AZ61 magnesium alloy with reinforcement of boron carbide and silicon carbide in different percentage levels was used and a plate was formed through stir casting technique. The process parameters of the stir casting process are namely reinforcement %, stirring speed, time of stirring, and process temperature. The specimens were removed from the casted AZ61 magnesium alloy composites through the Wire Cut Electric Discharge Machining (WCEDM) process, the material removal rate and surface roughness vales were carried out creatively. L 16 orthogonal array (OA) was used for this work to find the material removal rate (MRR) and surface roughness. The process parameters of WCEDM are pulse on time (105, 110, 115 and 120 µs), pulse off time (40, 50, 60 and 70 µs), wire feed rate (2, 4, 6 and 8 m/min), and current (3, 6, 9 and 12 Amps). Further, this study aimed to estimate the maximum ultimate tensile strength and micro hardness of the reinforced composites using the Taguchi route.

Special Issue of the Manufacturing Engineering Society 2020 (SIMES-2020)

The Special Issue of the Manufacturing Engineering Society 2020 (SIMES-2020) has been launched as a joint issue of the journals "Materials" and "Applied Sciences". The 17 contributions published in this Special Issue of Materials present cutting-edge advances in the field of Manufacturing Engineering, focusing on additive manufacturing and 3D printing; advances and innovations in manufacturing processes; sustainable and green manufacturing; manufacturing of new materials; manufacturing systems: machines, equipment and tooling; robotics, mechatronics and manufacturing automation; metrology and quality in manufacturing; Industry 4.0; design, modeling and simulation in manufacturing engineering. Among them, this issue highlights that the topic "advances and innovations in manufacturing processes" has collected a large number of contributions, followed by additive manufacturing and 3D printing; sustainable and green manufacturing; metrology and quality in manufacturing.

Parametric Optimization and Effect of Nano-Graphene Mixed Dielectric Fluid on Performance of Wire Electrical Discharge Machining Process of Ni55.8Ti Shape Memory Alloy

In the current scenario of manufacturing competitiveness, it is a requirement that new technologies are implemented in order to overcome the challenges of achieving component accuracy, high quality, acceptable surface finish, an increase in the production rate, and enhanced product life with a reduced environmental impact. Along with these conventional challenges, the machining of newly developed smart materials, such as shape memory alloys, also require inputs of intelligent machining strategies. Wire electrical discharge machining (WEDM) is one of the non-traditional machining methods which is independent of the mechanical properties of the work sample and is best suited for machining nitinol shape memory alloys. Nano powder-mixed dielectric fluid for the WEDM process is one of the ways of improving the process capabilities. In the current study, Taguchi's L16 orthogonal array was implemented to perform the experiments. Current, pulse-on time, pulse-off time, and nano-graphene powder concentration were selected as input process parameters, with material removal rate (MRR) and surface roughness (SR) as output machining characteristics for investigations. The heat transfer search (HTS) algorithm was implemented for obtaining optimal combinations of input parameters for MRR and SR. Single objective optimization showed a maximum MRR of 1.55 mm³/s, and minimum SR of 2.68 µm. The Pareto curve was generated which gives the optimal non-dominant solutions.

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

Servicing aircraft engines sometimes requires manufacturing only a single piece of a given part. Manufacturing a turbine disc using traditional methods is uneconomical. It is necessary to use a different machining method recommended for small lot production. One of the proposed methods is WEDM (wire electrical discharge machining). The article presents the results of the research on finishing WEDM of Inconel 718 turbine disc fir tree slots. The influence of infeed, mean gap voltage, peak current, pulse off-time, and discharge energy on the shape accuracy, surface roughness, microcracks, and the white layer thickness were determined. Mathematical models were developed based on the DoE (Design of Experiment) analysis. The statistical significance of the models was verified with the ANOVA (Analysis of Variance) test. The machining parameters control methods that allow achieving the required shape accuracy, surface roughness, and surface layer condition were presented. The obtained surface roughness was Ra = 0.84 μm, the shape accuracy of the slot in the normal-to-feed direction was Δd = 0.009 μm, the profile shape accuracy was Δr = 0.033 μm, and the thickness of recast (white) layer was approximately 5 μm.