Powder Mixed Electrical Discharge Machining Process Research Articles

Nanopowder-mixed EDM on biodegradable Mg alloy AZ31B for improved surface characteristics and biocompatibility

Powder-mixed electrical discharge machining (PM-EDM) was conducted on biodegradable magnesium (Mg) alloys for biomedical applications. The Mg alloy AZ31B has shown outstanding mechanical properties, similar to human bone, and is lightweight. Efforts were made to enhance the EDM capabilities by a PM-EDM process using nanopowder mixed in the dielectric medium and copper tool electrode amid the machining of Mg alloy AZ31B, followed by investigating surface modification by minimum machining time, morphology, chemistry, topography and wettability of the surfaces. The surface produced by nano PM-EDM operation exhibits minimal cracks and craters, an acceptable range of recast layer thickness (2.4 − 2.7μm), satisfactory corrosion resistance and surface roughness (Ra = 2.87μm) as well as suitable hydrophobic behaviour (CA122q) and bioactivity with Ringer’s solution, suggesting an improvement in the degradation rate. Thus, PM-EDM-induced surface modification suggests the suitability of Mg alloy AZ31B as a biodegradable implant in adults and children.

The evaluation of machining performances and surface roughness of TZM-molybdenum superalloy processed by silicon carbide powder mixed EDM process using RSM and ANOVA

In the present era, the concept of Industry 4.0 plays a significant part in improving the efficiency, quality, and utilization of resources by automation and enabling intelligent operations in manufacturing processes. As a result, there is a requirement to develop an environment that improves efficiency as well as quality in order to accomplish net zero in manufacturing. The objective of powder mixed electric discharge machining (PMEDM) is to enhance the quality of the surface and machining efficiency of traditional electrical discharge machining. The PMEDM method was applied to TZM-molybdenum superalloy in the present investigation by incorporating silicon carbide particles into the dielectric medium. Powder concentration, peak current, pulse on time, pulse off time, and gap voltage were the considered input variables for the investigation. The impacts of the input variables on the surface of the specimen’s roughness and the rate of material removal (MRR) were examined. The experiment model was built using response surface methodology. To find out if the input factors were significant with regard to each response, an analysis of variance (ANOVA) was performed. Powder concentration, pulse current, gap voltage, and pulse on time are found to be the important input variables for both surface roughness and MRR based on ANOVA analysis.

Numerical analysis of the powder mixed electrical discharge machining (PMEDM) process for TZM-molybdenum superalloy using finite element method

The powder mixed electrical discharge machining (PMEDM) process was simulated via finite element analysis in the current study to assess heat behavior and material removal rate. The goal of this paper is to conduct a thorough experimental and thermal examination of electrical discharge machining (EDM) in order to forecast its cutting characteristics and subsequently optimize the output variables using a response surface methodology for simulations and choosing the most suitable set of process variables related to the PMEDM process. This study’s objective is to design a 2D axisymmetrical transient thermal model that might also describe the physics of material removal in a single spark PMEDM operation on a Titanium Zirconium Molybdenum (TZM) superalloy. ANSYS (version 9.1) software is used to perform transient heat transfer simulations to determine the temperature profile with the amount of material removal at different current, pulse on and off times, gap voltages, and fraction of heat that enters the specimen. The PMEDM process produced craters with a lower diameter and depth, which increased the material removal rate and enhanced the surfacing quality. Compared to the conventional EDM process, the inclusion of powder raised the heat flux given to the work material by 10%–12%. It has been determined that with the single spark modeling technique, the temperature significantly dropped in both the radial and depth directions. The computational results are compared with experimental observations for similar machining conditions, and both results agree satisfactorily.

Optimization and comparison of machining characteristics of SKD61 steel in powder-mixed EDM process by TOPSIS and desirability approach

Optimization and comparison of machining characteristics of SKD61 steel in powder-mixed EDM process by TOPSIS and desirability approach

Exploring wide-parametric range for tool electrode selection based on surface characterization and machining rate employing powder-mixed electric discharge machining process for Ti6Al4V ELI

The titanium alloy Ti6Al4V ELI (grade 23) is widely used in biomedical industry because of its engineering attributes. However, it requires surface modifications and has processing challenges because it is difficult to machine nature. Therefore, powder-mixed electric discharge machining process is commonly applied to simultaneously machine the material and carry out surface treatment. The performance of the process is limited by both low cutting efficiency and the formation of a rough surface. In this regard, the current study evaluates SiC powder-mixed electric discharge machining of Ti6Al4V ELI using a range of tool materials such as copper, brass, graphite, and aluminum along with a comprehensive list of process parameters. The surface roughness parameters involving arithmetic roughness, the average peak-to-valley distance, and the highest peak-to-deepest valley distance along with material removal rate are comprehensively studied. Taguchi design of experiments L16 orthogonal array is used to study the process performance with parametric effect analysis, parametric significance analysis, and surface morphological analysis with a scanning electron microscope. Furthermore, the experimental results are optimized against a multi-response optimization matrix using grey relational analysis approach. An optimal compromise between surface attributes and cutting efficiency is identified by Al electrode, pulse current of 14 A, pulse on time of 75 µs, pulse off time of 75 µs, and negative polarity parametric conditions.

Powder mixed electrical discharge machining: One step method to create functional surfaces

The present work proposes a novel single stage technique to establish functional surfaces on machined component through powder mixed EDM process. A comparative analysis on surfaces generated by MoS2 powders of two distinct sizes Ф 40 µm (µP) and 90 nm (nP) mixed into dielectric of EDM is explored. Current (Ip) is chosen as input parameter and its consequence on Rq, Rsk, Rku, recast layer thickness (RCLT) and EDS analysis of AISI 304 machined surface is assessed. The Rq grows in proportion to rise in Ip magnitudes for both µP and nP mixed dielectric. At smaller magnitudes of Ip, a unique combination of negatively skewed and positive kurtosis surfaces are generated in both µP and nP mixed dielectric. The RCLT grows with increasing Ip magnitudes and the deposition of MoS2 on machined surface is perceived through EDS profiles.

Optimization of process conditions of Powder Mixed Electric Discharge Machining of Nickel based Superalloy using Grey Wolf Optimizer algorithm

The Powder-Mixed Electric Discharge Machining (PMEDM) process has been drawing the attention of researchers since it could successfully overcome some of the limitations of the conventional Electric Discharge Machining (EDM) process. There was extensive research carried out on the PMEDM process to explore various possibilities for enhancing the process output. In the present work, an experimental study has been undertaken to investigate the influence of three conductive powders: zinc, cobalt, and molybdenum, while machining Nimonic 75, a nickel-based superalloy, by the EDM process. The work material considered in the study has been widely used in the aerospace industries and in applications involving higher temperatures. The experiments were carried out based on the Response Surface Methodology using the Box–Behnken design. Using the experimental data, regression equations were formed to predict the outcome of the process, which are Material Removal Rate (MRR), Electrode Wear Ratio (EWR), and Surface Roughness (SR). This work attempted to optimize the EDM machining parameters using the Grey Wolf Optimizer (GWO) algorithm combined with the Utility concept. The optimum conditions obtained by the GWO algorithm were: Powder – Molybdenum; Concentration of powder – 5.4 g/L; Discharge current – 4 A; Duty factor – 0.8.

Parameter optimization in the enhancement of MRR of titanium alloy using newer mixing method in PMEDM process

The addition of powders in electrical discharge machining (EDM) reduces the breakdown strength of the liquid dielectric, thereby enhancing the occurrence of early spark, and aids in machinability. Challenges occur in the sustainability of the powder mixed electrical discharge machining (PMEDM) process in terms of homogeneity of the powder-dielectric mixture and adverse effects of these powders on the impellor of the pump, maintaining the concentration of the powder–dielectric mixture for a wide range of powders at varied size. In this investigation, an attempt is made to address these challenges and limitations in performing PMEDM process by developing a newer mixing method for PMEDM. The Taguchi L18 orthogonal array has been selected to study the material removal rate (MRR) of titanium grade 5 alloy. Gap current, duty factor, pressure of the powder mixed dielectric fluid, type of powder, and concentration of the powders have been considered as the process variables. The results found to be satisfying with increase in MRR. The confirmation experiments indicate considerable increase in MRR. This newer system is capable of performing sustainable manufacturing method irrespective of the nature of the powder and the particle size of the additive powders, that are permissible in the inter-electrode gap as it restricts the size of the powder, added in the PMEDM process.

Elucidating Powder-Mixed Electric Discharge Machining Process, Applicability, Trends and Futuristic Perspectives

Since the inception of electric discharge machining (EDM), it has facilitated the production industries, for instance, die & mold, automotive, aerospace, etc., by providing an effective solution for machining hard-to-cut materials and intricate geometries. However, achieving high machining rates and a fine surface finish is an inherent issue with the traditional EDM process. The emergence of the powder mixed electric discharge machining (PMEDM) process has not only provided the opportunity for enhancing productivity and surface finish but also opened a window for its potential application in surface modification/coating of biomaterials. The process incorporates simultaneous machining and coating of bioimplants, i.e., lacking in the already available chemical and physical coating methods while requiring costly post-treatment procedures. This study comprehends the influence of powder characteristics and EDM process parameters on the performance parameters. The impact of tool electrodes and additive powders on the machined and coated surface of commonly used biomaterials. Furthermore, the study depicts the most frequently used methods for optimizing the PMEDM process, future research directions, challenges, and research trends over the past decade.

Soft computing techniques for modelling and multi-objective optimization of magnetic field assisted powder mixed EDM process

Soft computing techniques for modelling and multi-objective optimization of magnetic field assisted powder mixed EDM process

The evaluation of machining performances and recast layer properties of AISI H13 steel processed by tungsten carbide powder mixed EDM process in the semi-finishing process

In the literature, investigations on the electrical discharge machining (EDM) process with Tungsten carbide powder mixed into dielectric fluid, also called PMEDM, are still limited. In this study, machining performances of PMEDM, including material removal rate (MRR) of AISI H13 steel and tool wear rate (TWR), were investigated in the semi-finishing process. Thereafter, recast layer properties of AISI H13 steel, including composition and content of chemical elements, recast layer thickness (RLT), and acreage percentage of micro-cracks on surfaces (APCS), were evaluated and discussed. Quantitative methods of MRR, TWR, RLT, APCS, and the composition and content of chemical elements on machined surfaces have been proposed. The results revealed that machining performances and recast layer properties were influenced by peak current (Ip), pulse on time (Ton), and powder concentration (Cp). MRR and TWR have been changed in an uptrend when Ip, Ton, and Cp increased. The chemical composition of machined surfaces was modified. APCS and RLT formed by PMEDM are notably decreased as compared with EDM, with a reduction of 41.093% and 48.982%, respectively. In addition, the changing trend of machining performances and recast layer properties were also explored.

Multi-Criteria Decision Making in the PMEDM Process by Using MARCOS, TOPSIS, and MAIRCA Methods

Multi-criteria decision making (MCDM) is used to determine the best alternative among various options. It is of great importance as it hugely affects the efficiency of activities in life, management, business, and engineering. This paper presents the results of a multi-criteria decision-making study when using powder-mixed electrical discharge machining (PMEDM) of cylindrically shaped parts in 90CrSi tool steel. In this study, powder concentration, pulse duration, pulse off time, pulse current, and host voltage were selected as the input process parameters. Moreover, the Taguchi method was used for the experimental design. To simultaneously ensure minimum surface roughness (RS) and maximum material-removal speed (MRS) and to implement multi-criteria decision making, MARCOS (Measurement of Alternatives and Ranking according to Compromise Solution), TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution), and MAIRCA (Multi-Attributive Ideal–Real Comparative Analysis) methods were applied. Additionally, the weight calculation for the criteria was calculated using the MEREC (Method based on the Removal Effects of Criteria) method. From the results, the best alternative for the multi-criteria problem with PMEDM cylindrically shaped parts was proposed.

Parametric Optimization of PMEDM Process with Aluminium Oxide Powder Suspended Dielectric for Copper Electrodes

Abstract: Electrical Discharge Machining is a commercially utilized technique for manufacturing of various shapes of materials that serve as the base material in a wide range of industries. This report presents the results of the experimental studies carried out on the influence of Powder Mixed Electrical Discharge Machining (PMEDM) input parameters on the various attributes of EDM process while using EDM oil and vegetable oil as dielectric fluid. The experiments performed under the designed full factorial procedure. Machining features, embracing material tool wear ratio, material removal rate and over cut with Ti-6Al-4V as workpiece are the parameters that were assessed in the study. The EDM input parameters - Peak Current, Duty factor and Gap voltage were studied. The results of this study could be utilized in the selection of optimum process parameters to achieve the desired EDM efficiency, surface roughness, and surface integrity when machining Ti-6Al-4V workpiece. Keywords: Electrical Discharge Machining (EDM), Outer Cut (OC), Tool Wear Ratio (TWR)

Surface modification of bio degradable materials through PMEDM –A research perspective

Biological and biomimetic materials are in high demand for certain applications, and machining them is one of the key challenges. Some researchers have worked together to solve problems related to machining biomedical equipment. In order to improve the material removal rate and surface roughness of the machined surface of biomedical materials by considering several aspects of the machining process. This review discusses the powder mixed electrical discharge machining (PMEDM) method in order to enhance biomedical materials' characteristics, surface morphology, and optimization techniques. By analyzing critical and analytical concerns, the review focuses on the current progress of the PM-EDM process. It highlights future research opportunities for the PMEDM process to meet high-quality standards for biomedical materials and its implications for bio implant design.

The machined performance and recast layer properties of AISI H13 steel processed by powder mixed EDM process: an investigation and comparison in fine-finishing and semi-finishing processes

The machined performance and recast layer properties of AISI H13 steel processed by powder mixed EDM process: an investigation and comparison in fine-finishing and semi-finishing processes

Multi-Objective Optimization of Aluminium Powder-mixed EDM process using GRA and TOPSIS Technique based on Fuzzy AHP approach

Electric discharge machining is an advanced machining technique. Spark is initiated between the tool and work piece interface which has a gap between them. Low material removal rate as well as low surface finish is a major concern of this process. Therefore, Powder mixed electric discharge machining is developed. In PMEDM process, powders like silicon, aluminium, chromium, manganese, etc. are circulated along with dielectric fluid in a particular proportion. In this present study, aluminium powder is mixed in the dielectric fluid. The responses such as material removal rate, tool wear rate and surface roughness are measured by considering current, pulse on time and aluminium powder concentration as process parameters. Response surface methodology along with Fuzzy AHP TOPSIS and Grey relational analysis are used for optimization.

Multi-objective optimization of machining parameters in hybrid powder-mixed EDM process by response surface methodology and normalized fuzzy logic algorithm

Multi-objective optimization of machining parameters in hybrid powder-mixed EDM process by response surface methodology and normalized fuzzy logic algorithm

An investigation on machined performance and recast layer properties of AISI H13 steel by Powder Mixed-EDM in fine-finishing process

Powder-mixed electric discharge machining (PMEDM) has been studied with many different powders. However, limited works have used the tungsten carbide powder in the PMEDM process and investigated its effects on machined performance (MP) and recast layer properties (RLP) of samples. Thus, to fill the missing gaps on the PMEDM. In this paper, an investigation of the effect of main process parameters, including peak current (Ip) and pulse on time (Ton) in fine-finishing process, and powder concentration (Cp) on the MP and RLP of AISI H13 steel was performed. Firstly, the MP – i.e., material removal rate (MRR), and tool wear rate (TWR) was investigated. The results showed that the MRR and TWR have varied in an upward tendency when Ip, Ton, and Cp was increased. At Ip = 2A; Ton = 32 μs; Cp = 60 g/l, the largest change in MRR and TWR is the increase of 132.022% and 132.353% respectively versus the EDM process. And nextly, the RLP – i.e., percentage and composition of chemical elements, recast layer thickness (RLT), and percentage of the surface micro-crack density acreage (PSCDA) was explored, namely that the percentage and composition of chemical elements of machining surfaces were also transformed versus that in the substrate layer of AISI H13 steel, and that on the recast layer of the EDM process. The determined method of the RLT and PSCDA has been proposed. The results of PSCDA and RLT formed by the PMEDM process were notably decreased, down to 52.547% and 65.606% respectively versus that of the EDM process. In addition, this study also investigated, and compared the variation trend of the MRR, the TWR, the percentage and composition of chemical elements, the PSCDA, and the RLT in the fine-finishing process when the powder concentration was added.

Application of Grey-PROMETHEE Method for Parametric Optimization of a Green Powder Mixed EDM Process

Application of Grey-PROMETHEE Method for Parametric Optimization of a Green Powder Mixed EDM Process

Optimizing the powder mixed EDM process of nickel based super alloy

Powder Mixed Electric Discharge Machining has been the main focus of many researchers for quite a long time. The performance of EDM process has been improved significantly by using powder mixed dielectric medium. Numerous researches were undertaken to study the influence of different process parameters involved in the powder mixed EDM by experimenting with different work materials and powder combination. The objective of this work is to conduct experimental study on the powder Mixed EDM of a Nickel based super alloy, Nimonic 75, using three different powders which are graphite, silicon and manganese. The other important process parameters considered are concentration of powder (Cp), peak current (Ip), duty factor (DC). The experiments were conducted based on the Response Surface Methodology (RSM) design. The important measures of performance of EDM process chosen in this study are Material Removal Rate (MRR), Electrode Wear ratio (EWR) and Surface Roughness (SR). Graphite powder yielded highest MRR and silicon powder produced good finish of the components. The influence of powder at higher concentration is not significantly high. Moreover, Higher duty cycle caused the decrease of MRR, EWR and increase of SR. This works also aims to optimize the process parameters using Grey Relational Analysis (GRA) combined with Fuzzy logic method. The optimum conditions identified based on GFRG was powder = Mn; concentration = 3 g/l; discharge current = 4 A and duty cycle = 0.9 It was also estimated that the error in predicting best output of the PMEDM process is below 6%.