Simulation Of Machining Process Research Articles

Implementation of a cutting forces model through virtual simulation of machining process

Implementation of a cutting forces model through virtual simulation of machining process

Thermal simulation of microelectrode machining process during block electrical discharge grinding

Electrical discharge machining is widely used in aerospace industries, semiconductor applications, micro-electromechanical systems, and other fields of the machining of micro-holes, micro-shafts, and micro-structures due to non-contact stress during the electrical discharge machining process. In the electrical discharge machining process, the machining precision of electrical discharge machining depends on the dimensional precision of the tool electrode, therefore, the machining process of microelectrode has attracted growing concern. In this study, a thermal model of the microelectrode machining process was proposed to simulate the formation process of microelectrode based on the temperature distribution during block electrical discharge grinding of the microelectrode process. According to the microelectrode machining process, the thermal model considers the main influential factors such as random distribution of discharge points, time-dependent discharge channel radius, Gauss heat source, phase transformation latent heat, etc. Through the thermal simulation analysis, the temperature distribution and the dynamic spark-erosion process of the microelectrode based on random repetitive spark discharges were obtained during block electrical discharge grinding of the microelectrode. Besides, it is found that the maximum temperature value and discharge crater volume of the electrode surface fluctuate and gradually decrease with the increase of discharge times. In addition, the effect of pulse width on the machining process of microelectrode was investigated by numerical simulation and block electrical discharge grinding of microelectrode experiment. The results indicated that the crater volume and the maximum temperature value on the surface of the microelectrode increased with the increase of pulse width. The formation process of microelectrode was considered a significant indicator to determine the machining precision and machining efficiency of the electrical discharge machining process.

Numerical modeling of cutting force and chip formation during water Jet Assisted Machining of Ti17 based on SPH/FEM method

In this paper, we conduct a numerical simulation of a water jet-assisted machining process for a titanium alloy Ti17, with a focus on addressing the Fluid-Structure Interaction (FSI) problem arising during lubricated machining. The proposed coupling strategy employs the Smoothed Particle Hydrodynamics (SPH) free mesh method, coupled with an ordinary Lagrangian mesh. The SPH method is utilized to model the water jet, while the Lagrangian Finite Element Method (FEM) is employed to represent the workpiece and the tool. The hydrodynamic behavior of water is captured using the linear Huguenot form of the Mie-Greisen equation of state. Additionally, the Johnson-Cook constitutive law is applied to describe the thermoviscoplastic behavior of the titanium alloy. It is essential to note that thermal and mechanical effects were decoupled in this study. The investigation focuses on cutting force and chip morphology under two distinct cutting regimes: Dry Machining (DM) and Water Jet Assisted Machining, specifically with conventional lubrication (CL). The numerical simulations are compared with experimental results found in the literature, with an emphasis on cutting force and chip morphology. The obtained simulation results exhibit a favorable correlation with the experimental data. All numerical simulations were conducted using ABAQUS version 6.14.

Finite element simulation of electric discharge machining process during machining of NiTi, NiCu and BeCu alloys

Advanced alloys, in addition to high strength, nonmagnetic qualities, high fatigue strength, corrosion resistance and non-sparking properties, also exhibit good wear resistance, corrosion resistance and good fatigue strength. As a result, conventional machining presents machining issues. However, electrical discharge machining provides a practical solution. With experimental validation, the current study is concerned with developing an electrical discharge machining model. In this study a single discharge finite element model was developed and simulated a three-dimensional axis symmetrical model using analysis software. The material removal rate was calculated using the temperature profile. A validation experiment was carried out to verify the numerical results. In the comparison of numerical and experimental results, an average error of 6.189 % was obtained. This shows that the finite element model results are in good agreement with experimental results. Further finite element can mimic the experimental conditions accurately and predict the material removal rate.

IMFREE: A versatile software tool for modelling machining processes with particle methods

The current state-of-the-art for the simulation of machining process is the application of the FEM (finite element method). Nevertheless, the cost of FEM analyses for such problems is high due to their complex multi-physics nature, mesh regeneration issues, and small time-length scales. In contrast, particle methods are an alternative numerical approach well-suited for large deformations as in material's chip formation. In this work, the key features and simulation capabilities of iMFREE are presented, which is a massively parallel and robust particle-based code for machining simulations developed at the ETH Zürich. Various applications of iMFREE are shown, where the efficiency is demonstrated in orthogonal cutting simulations for the optimisation of material removal rates, a chip formation study, the inverse identifications of friction law parameters and material constitutive law parameters. Further, the applicability to single and multiple grain grinding simulations of Ti6Al4V and silicon is shown.

Simulation of high-speed machining processes by multi-edge mills

Based on the results of the numerical experiment by finite element analysis (FEA) the mill design having the initial tooth profile in the form of a trapezoid located along two intersecting spiral lines with angles of inclination of 14 and 71 degrees. As a result, about 70 cutting protrusions – are formed on the cylindrical surface, i.e., the total number of cutting edges in the cutting dynamics can be up to 280 blades. A model and methods for determining the geometric and kinematic parameters of cutting milling the required shape, dimensions and quality of the surface of the detail are proposed. The roughness at optimal cutting modes correspond to the Ra = 1.25-0.63 μm, which is comparable to grinding processing. The shape of individual chip elements can be described as spherical, its dimensions do not exceed 20 μm, and larger chip agglomerates have submicron and nanostructural fragmentation. Due to the increase of edges on the surface of new design mill increase the efficiency and intensity of deformation processes too (the number of single cutting cycles is up to 4000-6000 s-1). This is also in good agreement with the numerical estimates by the FEA method.

Digital twin-enabled machining process modeling

Considering the new generation of information technology, the digitalization and intellectualization of the machining process have become the major core in intelligent manufacturing. The complex and diverse requirements, as well as the processing sites force the machining sequence to move towards cyber-physical integration. This paper presents a multidimensional modeling approach for machining processes, by introducing Digital Twin (DT) technology. The method is oriented towards the design and execution phases of the machining process and is used to support intelligent machining. The working mechanism of modeling, simulation, prediction and control of machining process is described based on the interpretation of the modeling and application methods of machining process design, inspection process, fault diagnosis and quality prediction, as based on digital twin technology. Finally, key components of diesel engines are targeted as test objects, demonstrating increased material removal rate by 5.1%, reduced deformation by 22.98% and 30.13%, respectively, verifying the effectiveness of the applied framework and the proposed method.

Assessment and validation of SPH modeling for nano-indentation

Nano-indentation tests are important techniques in material science. Over the past two decades, many numerical approaches have been proposed to model and simulate the nano-indentation process. In this paper, the possibility of modeling the process using a meshless numerical technique, known as smooth particle hydrodynamics (SPH), is explored. In particular, the SPH modeling of nano-indentation is conducted using the ANSYS/LS-DYNA software using three different published studies as benchmarks. More specifically, SPH results reported by Guo et al. (J Semicond 36:083007, 2015) when nano-indenting a KPD crystal were used first to verify the validity of the SPH model established in this work. Following this, the outcomes of further SPH simulations were found to compare well against finite element modeling and experimental results reported in Dao et al. (Acta Mater 49:3899–3918, 2001) and Karimzadeh et al. (Comput Mater Sci 81:595–600, 2014) for both micro- and nano-indentation, respectively. These observations suggest that SPH is a technique with the potential to be considered more widely by researchers investigating high strain, or strain rate, deformation phenomena on the nanoscale. For example, the presented research on the development of a SPH-based nano-indentation model lays the foundations toward formulating a comprehensive model for the accurate simulation of nanoscale tool-based machining processes.

Understanding the Mechanism of Abrasive-Based Finishing Processes Using Mathematical Modeling and Numerical Simulation

Recent advances in technology and refinement of available computational resources paved the way for the extensive use of computers to model and simulate complex real-world problems difficult to solve analytically. The appeal of simulations lies in the ability to predict the significance of a change to the system under study. The simulated results can be of great benefit in predicting various behaviors, such as the wind pattern in a particular region, the ability of a material to withstand a dynamic load, or even the behavior of a workpiece under a particular type of machining. This paper deals with the mathematical modeling and simulation techniques used in abrasive-based machining processes such as abrasive flow machining (AFM), magnetic-based finishing processes, i.e., magnetic abrasive finishing (MAF) process, magnetorheological finishing (MRF) process, and ball-end type magnetorheological finishing process (BEMRF). The paper also aims to highlight the advances and obstacles associated with these techniques and their applications in flow machining. This study contributes the better understanding by examining the available modeling and simulation techniques such as Molecular Dynamic Simulation (MDS), Computational Fluid Dynamics (CFD), Finite Element Method (FEM), Discrete Element Method (DEM), Multivariable Regression Analysis (MVRA), Artificial Neural Network (ANN), Response Surface Analysis (RSA), Stochastic Modeling and Simulation by Data Dependent System (DDS). Among these methods, CFD and FEM can be performed with the available commercial software, while DEM and MDS performed using the computer programming-based platform, i.e., “LAMMPS Molecular Dynamics Simulator,” or C, C++, or Python programming, and these methods seem more promising techniques for modeling and simulation of loose abrasive-based machining processes. The other four methods (MVRA, ANN, RSA, and DDS) are experimental and based on statistical approaches that can be used for mathematical modeling of loose abrasive-based machining processes. Additionally, it suggests areas for further investigation and offers a priceless bibliography of earlier studies on the modeling and simulation techniques for abrasive-based machining processes. Researchers studying mathematical modeling of various micro- and nanofinishing techniques for different applications may find this review article to be of great help.

100th Anniversary Issue of the Manufacturing Engineering Division Paper A Review of Advances in Modeling of Conventional Machining Processes: From Merchant to the Present

Abstract This paper presents a review of recent advances in modeling and simulation of conventional metal machining processes, which continue to dominate a significant part of all machining processes, and in recent years, the need for predictive models for machining processes has grown in importance in the digital manufacturing age. Significant advances have been made in modeling the mechanics of cutting in conventional machining, driven by industrial need and enabled by rapid advances in computational power. The paper surveys the state-of-the-art in analytical and numerical modeling of conventional metal machining processes with a focus on their ability to predict useful performance attributes including chip geometry, forces, temperatures, tool wear, residual stress, and microstructure. Also included in the review is a discussion of the industrial use of modeling and simulation tools for conventional machining. Additionally, the practical applicability, implementation benefits, and methodological limitations of conventional machining process modeling have been examined. The paper concludes with a summary of future research directions in modeling and simulation of conventional metal machining processes.

A parametric numerical study of ASB-assisted chip formation in high-speed machining of Ti-6Al-4V

ABSTRACT The present study aims at studying the influence of some parameters on the numerical results obtained from the simulation of the high-speed machining process using a commercial finite element computation code, namely Abaqus-Exp. Starting from models available by default in the computation code, comparisons are made between full and weak thermo-mechanical coupling, and the influence of the fracture strain and inelastic heat fraction values is studied. The high-strength Ti-6Al-4 V titanium alloy is taken as an example. Continuous, serrated and segmented chips are reproduced at low, moderate and high cutting speeds and the differences observed between experimental and numerical results are discussed.

Multi-spark simulation of the electrochemical discharge machining (ECDM) process

Multi-spark simulation of the electrochemical discharge machining (ECDM) process

Simulasi Gaya Pemotongan pada Proses Bubut dengan Software Third Wave Advantedge

The cutting force that reacts to cutting tool and workpieces will result deflection. Deflection is the cause of product deviation and vibration sources that can shorten the life of the cutting tool. Simulation of machining process is carried out to get an estimate of cutting force in some machining process conditions., then compare it to the experiments. The research aims to find out the influence of spindle rotary speed, feed rate and depth of cut on cutting forces in turning process with cutting tool HSS and workpiece Al 6061. This research uses three-dimensional simulation method using Third Wave AdvantEdge software. Following by comparison between the simulation with the experiments results. The simulation was in accordance to the experiments in term of the magnitude of the forces, from the biggest they are tangential, axial, and radial force respectively. Cutting force will decrease with increased spindle turning speed. Cutting force will increase with the rising feed rate and depth of cut. However, the simalution still highly deviate from the experiments at the rate of 71%, 44.3%, and 21.3% for axial, radial and tangential forces respectively. The possible cause of these high errors relates to forces measuring method in experiments.

The Influence of 5g on the Development of Electronic Information Engineering

With the rapid development of the times, our quality of life is also rising rapidly. At present, our technology has undergone a round of rapid development and achieved certain results. The era of artificial intelligence based on computer technology has come, and our life begins to embrace and contain this new technology, so modern life is the era of artificial intelligence. So, the new technology has brought many changes. For example, in Information Engineering, we can replace manual operation with preset programming to increase efficiency and reduce error rate. So, how to program is a difficult problem. Therefore, this paper studies the influence of 5g on the development of electronic information engineering. In order to better carry out the experiment, we first set the general direction and overall tone of the experiment we need to do after consulting a large number of literatures. Then we borrowed a period of time from the laboratory to conduct real experiments. But before that, we also carried out simulation experiments to reduce errors, and then conducted real experiments (in this case, we used interactive system to model and calculate the number) According to the rationality, the experimental results are obtained. The experimental results show that after the improvement of artificial intelligence, 5g can increase the reliability of NC programming and the simulation of machining process.

An Investigation on High-Resolution Temperature Measurement in Precision Fly-Cutting.

The loads acting on a workpiece during machining processes determine the modification of the surface of the final workpiece and, thus, its functional properties. In this work, a method that uses thermocouples to measure the temperature in precision fly-cutting machining with high spatial and temporal resolution is presented. Experiments were conducted for various materials and machining parameters. We compare experimental measurement data with results from modern and advanced machining process simulation and find a good match between experimental and simulation results. Therefore, the simulation is validated by experimental data and can be used to calculate realistic internal loads of machining processes.

Transient simulation of electrochemical machining processes for manufacturing of surface structures in high‐strength materials

AbstractElectrochemical machining (ECM) is a method for removing metal by anodic dissolution. At the interface between the workpiece surface and an electrically conductive fluid (electrolyte), the material is dissolved locally without direct physical contact to the cathodic tool. Due to the force‐free nature of the process, ECM is used for machining high‐strength or hard materials, such as titanium aluminides, Inconel, Waspaloy, and high nickel, cobalt, and rhenium alloys. However, determining suitable process parameters remains challenging due to their interacting effects on working distances during the machining process. Therefore a simulation‐based approach to process design substantially reduces resource and time investment to achieve the desired geometry of the finished part. This methodology requires data about the materials electrochemical properties, such as removal velocity and current efficiency, which have to be obtained experimentally. In this study, a methodology for acquiring and processing this data as well as the development of multiphysics simulation models is presented exemplarily for manufacturing a centrifugal impeller with a diameter of 14 mm consisting of the nickel alloy Inconel 713C for use in turbomachinery.

In-process identification of machine tool dynamics

An accurate description of the machine tool dynamics is essential in machining process simulation, chatter avoidance, and model-based monitoring. However, the standard practice of experimental modal analysis of an idle machine tool does not always provide an accurate representation of its dynamics under operating conditions. This paper proposes a modified transmissibility function-based operational modal analysis (TOMA) that assumes consistent mode shape for the spindle assembly to monitor the changes in natural frequency and damping ratio of the spindle. The transmissibility function-based solution considers only the relative vibrations between two sensors mounted on the spindle housing while the machine is excited by the cutting forces during machining. Experimental application of the Mode Shape Compensated TOMA was successfully demonstrated in multiple milling tests.

Cutting parameter optimization of Al-6063-O using numerical simulations and particle swarm optimization

Machining process simulations are commonly used by manufacturing industries to accurately predict machining force, time, and the performance of engineering components. Determination of optimal conditions of machining parameters is fundamental as it directly affects the material properties, surface finish quality, and the cutting tool life, among other objectives. In this work, we propose a multi-objective particle swarm optimization (PSO) algorithm, in order to determine the optimal machining parameters; i.e., rake angle (α), velocity (V ), and cutting feed (f ) using finite element (FE) simulation of orthogonal cutting. We evaluate the optimality of the problem for three objectives: (i) minimize the cutting force, (ii) maximize the microstructure refinement, and (iii) maximize material removal rate (MRR) in machining of Aluminum 6063. Minimum cutting force, higher refinement, and higher MRR are desirable in order to achieve enhanced cutting tool life, higher strength of the material, and higher machining performance, respectively. First, we develop the input-output relationships as well as the in-process parameter correlations using response surface methodology (RSM) and artificial neural network (ANN). Next, we use the particle swarm optimization technique combined with weight aggregation method to solve the multi-objective PSO (MOPSO) problem resulting in Pareto optimal solutions. Finally, we compare three machining conditions from the Pareto front in which one of the objective functions is optimized and the results show that a trade-off point can be drawn among the low cutting force, high microstructure refinement, and high MRR. A sample condition from the Pareto front is created experimentally resulting in good agreement with the model output. The optimization models can potentially enable the achievements of the desired objectives through the integration of the MOPSO algorithm with most of the available finite element simulations of machining.

Multi-time scale simulation of pulse electrochemical machining process with multi-physical model

To determine the relationship between the pulse current and the physicochemical properties of multi-time scales, a method of multi-time scale simulation is introduced to investigate multi-time scale evolution of temperature and void fraction in PECM process. A multi-time scale iterations method is introduced to reduce computation time of multi-time scale simulation. Simulation results indicate that the method is efficient and pulse current can make the PECM process more stable. Experimental results show that the multi-time scale simulation results can well match the actual machining results, especially in the middle section of the workpiece.

Finite Element Analysis of Friction Stir Welded 6082-T6 Aluminum Alloy’s Residual Stress

The existing finite element simulations of friction stir welding are mostly static analysis or simulation of a certain machining process. A new dynamic model is proposed, in order to simulate the whole process of friction stir welding, it is based on the thermoelastic-plastic method, Johnson-Cook constitutive equation and penalty contact algorithm. The residual stress of aluminum plate after friction stir welding is obtained by using this model. The results obtained by this model are close to the results gained by experimental verification. This model can simplify the simulation of friction stir welding process, and the results gained can be greater.