Machining Process Parameters Research Articles

Experimental investigation of longitudinal torsional composite ultrasonic vibration assisted turning of CuCr1Zr alloy

CuCr1Zr alloy plays an important role in aerospace, energy, electronics and other fields. Due to its excellent properties, the cutting of CuCr1Zr alloy has also become one of the research hotspots. In order to obtain better machining quality at lower cost, a kind of machining system of longitudinal torsional composite ultrasonic vibration assisted turning (LT-UAT) is designed in this paper. The combination of longitudinal vibration and torsional vibration is realized by using vibration mode conversion screw (VMCS). The turning experiments of CuCr1Zr alloy with and without ultrasonic vibration are carried out, and the effects of process parameters on surface quality and chip shape (CS) are studied. The results show that lower surface roughness (SR), better surface topography (ST) and CS can be obtained when the LT-UAT of CuCr1Zr alloy with reasonable process parameters. The optimal combination of process parameters (OCPP) is ultrasonic amplitude of 45 µm, cutting speed of 30 m/min, cutting depth of 0.1 mm, and feed speed of 0.1 mm/rev. When selecting process parameters in actual machining, the closer to the above OCPP, the better. This research helps to promote the development of ultrasonic machining technology, and also promotes the application of CuCr1Zr alloy in more fields.

Electric discharge machine process parameters optimization for additively manufactured copper–graphene tool

Electric discharge machine process parameters optimization for additively manufactured copper–graphene tool

Characterisation of defects following MicroCT sampling inspection of specimens produced by electron beam powder bed fusion

ABSTRACT With the maturation of metal additive manufacturing (AM) technologies, and the evolution of the machine capabilities, the discussions in literature are pivoting towards reliability and quality of the components produced. There is still much concern amongst stakeholders in the medical, aerospace and automotive industries about whether metal AM parts will meet many of the strict quality requirements. Following a Systems-V approach to quality assurance verification, this work focused on the characterisation of defects detected by µCT sampling scans of Ti-6Al-4V specimens produced via electron beam powder bed fusion (EB-PBF). Pore characteristics were classified by volume, surface area, diameter, compactness, sphericity, spatial distribution and orientation. From a statistical analysis of these attributes, a covariance matrix was established that revealed defect dependencies important to consider for manufacturing quality components in EB-PBF. Due to the sampling method employed, the results were combined with machine process parameters to predict the expected levels of porosity for the entire specimens with good agreement. Thus, this work provides evidence in support of quality verification by µCT sampling methods.

OPTIMIZATION OF A NONCONVENTIONAL MACHINING PROCESS USING MULTI-CRITERIA SELECTION METHODS

Determining the optimal parameters for a process technology requires a full analysis of all the principles and factors that influence it. Nonconventional technologies are more and more present in modern manufacturing processes, so determining the values of the technological and economic parameters is vital. In this paper, multi-criteria methods (ELECTRE, TOPSIS) were used to determine the importance of the criteria and to establish the best combination of parameters (discharge time, off time, average lateral spark gap, lateral roughness, frontal roughness, velocity of erosion) in an electrical discharge machining process with massive electrode for C120 steel at 85V voltage. The dimensions of the depressions in a steel piece depending on the energy or duration of the pulses, and the influence of the moving speed of the semi-finished product on productivity can be also determined. Various multi-criteria decision-making methods are available to help the designers in choosing the decisive course of actions. In the discrete form of multi-criteria decision-making problems, the work flow is confronted with a decision-matrix formed from the information of some alternatives on different criteria. A software application was created that allows the user to enter only the desired parameters and the criteria that must be strictly respected, and the program will choose in a very short time the optimal combination of the available values.

PARAMETRIC OPTIMIZATION OF ABRASIVE WATER JET MACHINING PROCESS USING COPRAS AND VIKOR METHODS

Abrasive Waterjet Machining (AWJM) is one of the widely used non-traditional machining process to cut the hard materials like aluminium metal matrix composites (AMMCs) and the materials which are very difficult to machine using conventional machining due to their high hardness and tendency to cause tool wear. Present work two popular multi criteria decision making (MCDM) techniques Complex Proportional Assessment (COPRAS) AND VIseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) Methods have been used to optimize the AWJM machining process parameters for the machining of AMMCs. Both equal weight and standard deviation methods are used to find the weight of three response parameters like material removal rate, surface roughness and kerf width. From the results it is observed that there is a strong correlation between the weight calculation and the MCDM techniques which shows the robustness of the techniques. It is also noticed that machining with highest traverse speed and with out silicon carbide (SiC) is giving good response paramètres. However machining with low traverse speed is giving worst response parameters.

Investigating and Multi-Objective Optimizing WEDM Parameters for Al6061/Mg/MoS2 Composites Using BBD and NSGA-II.

This study aims to optimize the Wire Electrical Discharge Machining (EDM) process parameters for aluminum 6061 alloy reinforced with Mg and MoS2 using the Box-Behnken (BBD) design and the non-dominated sorting genetic (NSGA-II) algorithm. The objective is to enhance the machining efficiency and quality of the composite material. The Box-Behnken (BBD) design was utilized to design a set of experiments with varying levels of process parameters, comprising pulse-on time, servo volt, and current. The material removal rate and surface roughness were considered as machining responses for optimization. These responses were measured and used to develop a mathematical model. The NSGA-II, a multi-objective optimization algorithm, was then applied to search for the optimal combination of process parameters that simultaneously maximizes the material removal rate and minimizes the electrode wear rate and surface roughness. The algorithm generated and evolved a set of Pareto-optimal solutions, providing a trade-off between conflicting objectives. The results of the optimization process were analyzed to identify the optimal process parameters that lead to improved machining performance. The study revealed optimal Wire Electrical Discharge Machining (WEDM) parameters for Al6061/Mg/MoS2 composites using NSGA-II. The optimized parameters, including a pulse-on time (Ton) of 105 µs, servo voltage (SV) of 35 V, and peak current (PC) of 31 A, resulted in a Material Removal Rate (MRR) of 7.51 mm3/min and a surface roughness (SR) of 1.97 µm. This represents a 15% improvement in the MRR and a 20% reduction in the SR compared to non-optimized settings, demonstrating the efficiency of the BBD-NSGA-II approach.

Optimization strategy of computer numerical control machining process parameters in biomanufacturing mold

With the rapid development of biomanufacturing technology in the medical and pharmaceutical fields, the demand for high-precision and high-quality molds has surged. When Computer numerical control (CNC) machining biomanufacturing molds, the optimization of process parameters becomes the key to improve efficiency and quality. The purpose of this study is to explore the optimization strategy of CNC machining process parameters to achieve the best surface quality, dimensional accuracy and machining efficiency. Through literature review, the spindle speed, feed speed and cutting depth are selected as the key parameters, and the multi-objective optimization model is constructed by response surface method, which is solved by genetic algorithm. The experiment shows that the process parameters of CNC system in mold manufacturing are cutting speed 100 (m/min), feed rate 0.2 (mm/rev) and cutting depth 0.5 (mm), which will effectively reduce the manufacturing cost, and effectively control the alarm times within 35 times in different processing equipment, greatly reduce the risk. The optimization strategy can significantly improve the surface quality and productivity of the mold and reduce the cost. The comparative analysis verifies the effectiveness of the method, which provides new theoretical and technical support for CNC machining in the field of biomanufacturing.

Multi-objective optimization in EDM of functionally graded Fe-Al using grey relational analysis

Abstract Functionally Graded Materials (FGMs) are multipurpose materials with a specific goal of managing changes in structural, thermal, or functional qualities. They feature a spatial variation in microstructure and/or composition. The current work prepared three layers of sample with different chemical compositions of Fe-Al FGM (50 Al-50 Fe, 45 Al-55 Fe, and 40 Al-60 Fe) at. % produced by powder metallurgy, then studied the machining behavior of these samples. The literature on the machining behavior of FGM was reviewed, and the influence of electrical discharge machine (EDM) process parameters such as voltage (V), current (I), pulse-on time, and pulse-off time on performance characteristics (material removal rate (MRR), tool wear rate (TWR), and surface roughness (Ra)) was investigated. The optimal machining settings for Fe-Al FGM samples will be ascertained by use of Grey Relational Analysis (GRA), which is based on the Taguchi approach, after an experimental investigation of the L18 orthogonal array design of trials. The GRA findings verify that V 140 volts, Ip10 A, Ton 100 μs, and Toff 75 μs is the optimal combination of process parameters. It has been found that the voltage is more significantly affected than the rest of the input parameters to obtain greater material removal rate (MRR) and lower tool wear rate (EWR) and surface roughness (Ra) through the response table. According to the study, choosing the right process parameters can improve the multi-performance feature.

Machining performance analysis of wire-EDM for machining of titanium alloy using multi-objective optimization and machine learning approach

This study investigates the multi-objective optimization of process parameters in wire electrical discharge machining (WEDM) using titanium alloy grade 5 and zinc-coated brass microwire. The novelty lies in the comprehensive investigation of the effects of varying pulse on time (Ton), wire tension (WT), and wire feed rate (WF) on output responses, including surface roughness (SR), surface crack density (SCD), corner diameter (CD), and kerf width (KW). The Box-Behnken design, a sophisticated response surface methodology (RSM) technique, is employed to efficiently explore the complex relationships and interdependencies between these input and output parameters. The study's novel approach incorporates machine learning algorithms, including decision tree, light gradient boosting machine (LightGBM) and random forest, to predict the characteristics of the laser-cut components based on the input parameters. The contour plots generated provide valuable insights into the underlying patterns and associations between input and output features, aiding in the understanding of the WEDM process. The results reveal that the optimized values for SR, SCD, CD, and KW are obtained at specific machining conditions: Ton of 10 μs, WF of 3.79 m/min, and WT of 8 gf. Among the machine learning algorithms employed, random forest outperforms the others in predicting KW, SR, SCD and CD, exhibiting significantly lower mean squared error (MSE) and mean absolute error (MAE) values. This study contributes to the field of WEDM by providing a comprehensive analysis, incorporating advanced experimental design techniques and machine learning algorithms, which can aid in process optimization and quality control in manufacturing applications.

Study on ultrasonic-assisted abrasive flow polishing of internal flow channels in additive manufacturing

By studying the movement of ultrasonically assisted abrasives, combined with simulation experiments of abrasive flow in internal flow channels, the study on ultrasonic assisted abrasive flow machining of internal flow channels in additive manufacturing is carried out. Simulations were performed on the channels of AlSi10Mg aluminum alloy printed components, yielding the optimal process parameters for abrasive flow machining: a processing pressure of 10 MPa, abrasive particle size of 270 mesh, and abrasive concentration of 60%. By comparing the surface morphology of the combined straight and curved flow channels before and after applying ultrasonically assisted abrasive flow machining, it was evident that the application of ultrasonic assistance yielded superior removal of surface defects on additive manufacturing parts. However, its ability to remove the spheroidization effect in deeper concave areas is limited. The efficiency of abrasive flow machining and the surface quality of the parts were enhanced with the incorporation of ultrasonic vibration. Under the optimal polishing process parameter combination of an ultrasonic frequency of 20 kHz, a tool head amplitude of 30 μm, and a processing time of 360 s, the surface roughness (Ra) of the straight section reduced to 0.165 5 μm, while the surface roughness (Ra) of the curved section reduced to 0.371 8 μm.

Optimization of wire electrical discharge machining process parameters on Inconel 690 superalloy via Taguchi technique

The research work deals with the improvement of wire electrical discharge machining process parameters for Inconel 690 super alloy. The goal of optimization is to achieve a maximum material removal rate (MRR) and a minimum surface roughness (SR). Brass wire is employed as the electrode, and Pulse on time (PON), Pulse off time (POF), Wire tension (Wt) and Wire feed (Wf) were selected as the process variables. The investigations were modelled based on Taguchi L16 orthogonal array. The results revealed that maximum MRR was obtained when PON=12 µs, POF=57 µs, Wf=6 m/min, Wt=9 g, and a minimum SR was obtained when PON=12 µs, POF=60 µs, Wf= 9 m/min and Wt=7 g. The optimum condition for machining by grey relational grade and its rank order method are found to be PON=12 µs, POF=59 µs, Wf=7 m/min and Wt=10 g. Whereas on using grey-Taguchi technique, the optimum parameters are found to be PON=12 µs, POF=58 µs, Wf=6 m/min and Wt=10 g. Analysis of variance was utilized to determine the input parameter's influence on the performance parameter and it was found that PON has high significance in maximizing the MRR and minimizing the SR.

Precision Electrochemical Micro-Machining of Molybdenum in Neutral Salt Solution Based on Electrochemical Analysis

Molybdenum is an important material in modern industry, widely used in extreme environments such as rocket engine nozzles and microelectrodes due to its high melting point, excellent mechanical properties, and thermal conductivity. However, as a difficult-to-machine metal, traditional machining methods struggle to achieve the desired microstructures in molybdenum. Electrochemical machining (ECM) offers unique advantages in manufacturing fine structures from hard-to-machine metals. Studies have shown that molybdenum exhibits a fast corrosion rate in alkaline or acidic solutions, posing significant environmental pressure. Therefore, this study investigates the electrochemical machining of molybdenum in neutral salt solutions to achieve high-precision microstructure fabrication. First, the polarization curves and electrochemical impedance spectroscopy (EIS) of molybdenum in NaNO3 solutions of varying concentrations were measured to determine its electrochemical reaction characteristics. The results demonstrate that molybdenum exhibits good electrochemical reactivity in NaNO3 solutions, leading to favorable surface erosion morphology. Subsequently, a mask electrochemical machining technique was employed to fabricate arrayed microstructures on the molybdenum surface. To minimize interference between factors, an orthogonal experiment was used to optimize the parameter combination, determining the optimal machining process parameters. Under these optimal conditions, an array of micro-groove structures was successfully fabricated with an average groove width of 110 μm, a depth-to-width ratio of 0.21, an aspect ratio of 9000, and a groove width error of less than 5 μm.

Optimizing EDM for titanium alloys: an in-depth comparison of five MCDM techniques

This experimental study investigates the effect of the cutting parameters of the Electrical Discharge Machining (EDM) process of Ti-6Al-4V alloy material on surface roughness (Ra), cutting time (t) and Material Removal Rate (MRR) then solve the Multiple Objective Optimization Problem using separate Multi-Criteria Decision-Making (MCDM) methods namely Entropy-Weighted TOPSIS (E-TOPSIS), MOORA, SAW, VIKOR, and WPM. Focusing on nine 3-levels variants including Operating Voltage (OV), Pulse-On Time (Ton), Pulse-Off Time (Toff), Short-Circuit Off Time (AFF), Secondary Voltage (SV), Feed Rate (WF), Tension (WT), Water Pressure (WL) and Material Cutting Speed (F). Due to the large number of variants studied, the Taguchi L27 experimental design was chosen to reduce the number of experiments while still ensuring reliability in assessing the impact of technological parameters on responses in the study. The optimization results from the different methods indicated two distinct optimal outcomes. According to the E-TOPSIS, MOORA, and SAW, the optimal result is a Ra of 3.27 µm, a t of 7.37 min, and an MRR of 7.45 mm3/min. This result suggests a balanced and harmonious optimization among all criteria. On the other hand, the figures VIKOR and WPM methods are 2.87 µm, 9.57 min, and 5.74 mm3/min, respectively. These results indicate a higher priority for certain criteria, reflected in the lower Ra, longer cutting time, and a smaller MRR in comparison to the figures for the remaining MCDM methods. The different optimal results achieved by various methods highlight that each method is suited to and excels with different sets of values. Therefore, in each specific research or production process, comparing and choosing results calculated by different methods provides a comprehensive view, aiding in making appropriate decisions

Optimization of Machining Parameters in Wire Electric Discharge Machining Inconel 600 Using Regression analysis

In this investigation, Inconel 600 is used as the workpiece material, which is typically applied in aerospace products, chemical processing equipment, furnace parts etc., due to its good resistance to stress and wear resistance. In this work, the effect of machining parameters of Wire Electric Discharge Machining (WEDM) process is investigated. Molybdenum wire electrode of 0.1mm diameter and de-ionized water dielectric medium are used for machining. Voltage, Pulse on-time, Pulse Off-time, Peak Current and Bed speed are considered as the machining parameters. Recast layer thickness is considered as the response parameter. The type of design of experiments considered for this work is Taguchi’s L18 orthogonal array. Analysis of variance is indicating the percentage contribution of each machining parameters on response parameters. The optimum combination of machining parameters yielded minimum Recast layer thickness 4.11μm.

Optimization of process parameters in micro electrochemical machining using TOPSIS technique with Analytical Hierarchy Process (AHP)

Electro-chemical machining (ECM) is one of the extensively used unconventional machining processes employed in industries to machine difficult-to-machine materials such as super alloys, titanium alloys, stainless steel, etc It does not impart any mechanical stresses on the workpiece. The primary requirement of the work material used in this process should be electrically conductive materials. In favour of these characteristics, Hastelloy C276 is used as a work material because it exhibits excellent physical properties over cast iron. Generally, the quality of machining mostly relies on the electrolyte (mmol L−1), feed rate (mm/rev), and duty ratio. These credential parameters are considered in this present work to enhance the machining quality, such as circularity, taper angle, and metal removal rate (MRR). The Taguchi L9 orthogonal array is used to learn machining behaviour under various circumstances. And this time, an Analytic Hierarchy Process (AHP) is used to allocate the weight for each response in the TOPSIS multi-criteria decision-making method. According to the findings, sodium nitrate (NaNo3) has a higher metal removal rate than sodium chloride (NaCl) and sodium bromide (NaBr). It will, however, result in a low-quality hole. The taper angle is inversely proportional to the feed rate.

Enhancing machining efficiency in hybrid metal matrix composites through EDM parameter optimization via grey relational analysis

In summary, this study utilized stir casting to develop three distinct aluminium hybrid composites incorporating boron carbide and alumina. These composites were identified as Al7075 + 12%B4C + 6%Al2O3, Al7075 + 6%B4C + 6%Al2O3, and Al7075 + 6%B4C + 12%Al2O3. The novelty of this research lies in the unique combination of materials and their proportions, offering enhanced properties yet unexplored in this specific configuration. The research focused on machining these composite materials using EDM and employed a Taguchi L27 orthogonal array design to plan the machining tests. Key process parameters considered were gap voltage (V), duty cycle (%), current (A), and different percentages of reinforcement content. This aspect adds a significant novel dimension to the study, as the impact of EDM machining parameters on hybrid composites with this particular composition has not been extensively explored previously. The study applied Grey Relational Analysis to evaluate the impact of EDM machining process parameters on critical output responses, specifically material removal rate (MRR) and tool wear rate (TWR). SEM images revealed redeposited molten material, craters, and surface cracks, emphasizing the importance of controlling discharge energy and current levels for desired surface quality. An optimal configuration was identified peak current 2 A, pulse duration 100 μs, duty factor 20%, Composition 2 for improved surface attributes. These qualitative and quantitative insights inform process optimization strategies for EDM machining of aluminium hybrid composites.

Multi-Objective Optimization of Pulse Electrochemical Machining Process Parameters by CRITIC-TOPSIS

Multi-Objective Optimization of Pulse Electrochemical Machining Process Parameters by CRITIC-TOPSIS

Study and optimization of process parameters for deformation machining stretching mode

Monolithic thin-structure parts with intricate geometric designs are employed in a variety of aeronautical, medical, marine, and automotive applications, which include the moldlines of the fuselage, turbine blades, impellers, avionic shelves, irregular fins, prostheses, bone and joint support, and skull plates. The deformation machining process is the solution to this challenging and difficult-to-manufacture high-quality components with intricate narrow geometries at competitive prices. The aim of the present study is to assess the effect of process parameters of the deformation machining process wherein a thin, floor-like structure is created by milling and is then formed using a single-point incremental forming tool. Investigation involves the design and development of tooling required for the process followed by feasibility checking of the process. To examine the impact of different process parameters on the process response, the experiments were carried out using the design of experiments. The findings of this study indicate that different process parameters, including spindle speed, tool diameter, incremental step depth, and feed rate, have a substantial impact on the process response, like thickness, surface finish, and hardness. Uneven and non-uniform surface patterns during SEM indicate that it is needed to examine the impact of process parameters. This research involves the feasibility study of a new hybrid technique of deformation machining. Conventionally, a metallic structure is produced by joining various components through welding or by fastening. These methods require additional expenditure on equipment, storage, floor space, human resources, etc., with higher lead time. Joining increases weight and reduces fatigue strength. The creation of monolithic structures can eliminate all these disadvantages.

Study on formation of exit edge defects in the milling process by using the combined theory of the energy conservation and orthogonal cutting mechanism

1 In the milling process, due to machining materials and process parameters, the material at the edge of the part may break due to shear forces instead of cutting properly, resulting in the irregular pit (defect) at the exit edge. This seriously affects the surface quality of the workpiece. It is vital to understand the forming mechanism of the exit edge defect (EED) before one tries to eliminate or reduce the size of the EED and furthermore to improve the machining accuracy. Therefore, focusing on the milling process at exit edge of a workpiece, this paper presents a novel theoretical model to study the forming principle of the EED and predict the corresponding size. First, the forming process of the EED is separated into two stages. The beginnings of them are symbolized by the initial- and the fracture-negative shear planes. Then, the initial-negative shear plane which is defined by the initial negative shear angle is found. Furthermore, the location of the fracture-negative shear plane is defined using the fracture negative shear angle to study the EED. For the next step, the concentration force of Flamant-Boussinesq problem combined with the yield strength of the material is introduced to obtain the initial negative shear angle. Additionally, using the energy conservation theory, the negative fracture shear angle is calculated. Based on these, the mechanism of the EED is illustrated. Besides, the size (including length and depth) of the EED is predicted based on the geometric relationship between the initial and the fracture negative shear angle. Finally, the correctness of the theoretical model is verified by simulation and experiments. This study provides a promising step to reducing/eliminating the hazards of edge defects.

Analisa Kekasaran Permukaan Baja ST 37 Hasil Proses Milling Vertikal Akibat Variasi Proses Permesinan dan Media Pendingin

Minimum surface roughness in the machining process affects the quality of a material. Likewise with the results of the Vertical Milling process. One of the things that influences surface roughness in the milling process is the selection of machining parameters. Apart from selecting machining process parameters, another thing that influences surface roughness is the presence of coolant. The aim of this research is to determine the surface roughness results of ST37 steel due to variations in cutting speed, feed speed and coolant discharge during the vertical milling process. Data testing uses multiple linear regression. The research results show that the influence of the feeding speed parameter has the greatest influence and the smallest influence is on the coolant discharge, where the results of the regression test results are Ra = 100.636 *(v)-0.577 *(vf)0.159 *(q)-0.245 with a value R Square is 0.846 or 84.6%.