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Accuracy and reliability of the numerical results is one of the most important challenges in the scientific community for finite element modeling (FEM) of cutting processes. It becomes more essential in machining of difficult-to-cut materials such as nickel-based alloys where high thermo-mechanical loads are induced into the workpiece. In this paper, new strategies were adopted to improve accuracy of FE modeling of cutting process of Inconel718 superalloy. Firstly, a novel hybrid strategy was established to simultaneously calibrate controllable simulation parameters. It was implemented based on the design of experiment, intelligent systems and FEM of cutting process. Using validation with experimental results, a great improvement was obtained for prediction of cutting forces, maximum temperature, and chip geometry compared with numerical results obtained previously by conventional calibration procedure. At the second stage of the paper, a grain size-based flow stress was developed by implementation of advanced FORTRAN user-subroutine in FE code to take into account the effect of changes in material properties during the chip formation. According to the results, implementation of grain size based flow stress has a significant effect on enhancement of simulation accuracy. Finally, it can be concluded that, the innovated strategies presented in this paper provide fundamental and useful approaches to improve precision in modeling of other manufacturing processes. [ABSTRACT FROM AUTHOR]

There is currently a lack of knowledge in the manufacturing of high complexity aerospace components. Impellers or blade-integrated disks (blisks) are expensive, and manufacturers tend to prefer reliability over productivity. Thus, manufacturing times are higher than they should be. These challenging parts need to be machined using new advanced tools for several reasons, such as requirement of 1) special and complex tool paths, 2) smoother cutting forces, and 3) good accessibility. Circle-segment or oval-form cutters have recently demonstrated their usefulness and adaptability in the machining of profile and free-form surface operations, and are becoming a solution for a wide range of applications and materials. However, machinists who use them know very little about such tools. In fact, there has been a lack of real-world modelling applications. This paper proposes for the first time a geometrical model that allows the prediction of the surface topography in flank-milling operations using circle-segment end mills. This time-domain model includes the most important mechanical and kinematical parameters during cutting: the tool geometry, feed rate, radial immersion, and tool runout. Tool orientation angles commonly used in 5-axis operations are also included. The developed model was positively verified against experimentally measured values in a milled wall made of aluminium Al7075T. This knowledge-based tool is useful for manufacturing companies and suppliers interested in optimizing and controlling their production parameters. [ABSTRACT FROM AUTHOR]

To achieve a certain measurable performance in cutting machines, the machine parameters need to be optimized. Several constraints determine the possible values that these parameters can take. Although parameters are usually assumed to be deterministic, in practice, it is common to find variations on the characteristics of the products or the processes. Modeling machining parameters as stochastic factors provides a more realistic representation of cutting operations. Moreover, multiple operational objectives are of interest, in many real situations, these multiple objectives are conflicting. Consequently, the problem of setting the parameters becomes a trade-off situation. This paper presents a novel Simulation-based Multi-Objective Optimization (SimMOpt) solution procedure. The procedure is divided into two phases: (1) finding initial solutions and, (2) using a simulated annealing-based method for finding neighboring solutions. In the first phase, non-linear goal programming is used for finding high quality initial solutions. The second phase incorporates Pareto Archive Evolution Strategy (PAES) and hypotheses testing for searching near-optimal solutions for a set of stochastic parameters (i.e., cutting speed, feed rate, and depth of cut) in metal cutting operations. Three objectives are optimized (i.e., operation time, operation cost, and quality of the product). The results from implementing this procedure are analyzed and compared to a baseline methodology based on the Multi-Objective Simulated Annealing (MOSA) algorithm. The analysis demonstrates that the proposed method outperforms the Genetic Algorithm (GA), which was the benchmark algorithm, in terms of the solution quality of all the objectives. More importantly, the solutions from using the SimMOpt procedure outperform those obtained from using an enhanced MOSA-based approach (i.e., 4.71% improvement in the hypervolume approximation). [ABSTRACT FROM AUTHOR]

Inconel 718 is commonly used in structural critical components of aircraft engines due to its properties at high temperatures. In order manufacture the final part, these components have to be machined, so the final surface integrity obtained after machining becomes a key issue. Residual stresses, which are included in surface integrity, are an important issue. Although much of the research carried out on machining induced residual stresses has been empirical, finite element modelling appears to be a complementary solution to gain understanding of it. However, some of the major drawbacks still need to be solved before it can become a reliable tool for industry, such us the identification of input parameters and computational cost. This paper deals with the study of machining induced residual stresses. An orthogonal cutting 2D finite element model was used and a sensitivity analysis was conducted to determine the influence of model input data on the predicted residual stresses. The results obtained from the sensitivity analysis showed that material constitutive law was the most relevant input data when predicting residual stress fields. Importantly the material behaviour at a high heating rate in adition to high strain rate must be considered. [ABSTRACT FROM AUTHOR]

Previous published works on the optimization of parameters in orthogonal cutting process have used a single tool. The parameters considered in these works are: surface roughness, power consumption, deformed chip shape, and temperature in the workpiece. This paper is on the optimization of machining parameters with multiple cutting tools. This is required to reduce the cutting forces and temperature while machining AISI 1045 steel. In this study, this has been achieved by using a combination of statistical tools including Taguchi matrix, signal to noise ratio, and analysis of variance (ANOVA). The effects of varying cutting speed, feed rate, depth of cut, and rake angle in orthogonal cutting process have been considered. The Finite Element (FE) simulations have been carried out with a general purpose commercial FE code, ABAQUS, and statistical calculations have been performed with Minitab. Results show that for optimum cutting forces, feed rate and depth of cut are the most important factors while for lower temperatures, cutting speed and rake angle play a significant role. It is concluded that carbide cutting tools is a better option as compared to uncoated cemented carbide cutting tool for machining AISI 1045 steel as it results in lower cutting forces and temperatures. [ABSTRACT FROM AUTHOR]

Grinding is an important means of realizing precision and ultra-precision machining of workpiece surface. The surface patterning of workpiece directly affects its mechanical properties such as friction, wear, contact stiffness, fitting property. Therefore, prediction of the geometry of the workpiece surface is very important to evaluate the workpiece quality to perform mechanical function accurately. In this paper using MATLAB simulation, prediction for the geometry pattern of the workpiece according to the developed shape of the grinding wheel dressed by thread cutting was studied. The model for the geometry of the grinding wheel surface was first developed and subsequently, a new simulation model for surface pattern by grinding process was established. The simulation results could be used to optimize the grinding process and to improve the workpiece surface quality or predict the surface pattern by given grinding parameters. [ABSTRACT FROM AUTHOR]

Residual stress affects component performance, and the existence of pre-stress changes the residual stress of machined surfaces as well, emphasizing the importance of studying the evolution of residual stress in sequential cutting. This paper reports a numerical investigation of the machining-induced residual stress profile of sequential cuts for orthogonal cutting of AISI 304, considering the effects of edge radius and cutting depth. A Coupled Eulerian-Lagrangian (CEL) model is employed for the first time to stably simulate the evolution of residual stress of multiple sequential cuts. The effectiveness of the proposed method is verified by comparing the chip formation and surface residual stress between simulated and experimental results. The cutting force and cutting temperature, as well as mechanical and thermal loads, are extracted to explain the generation and evolution of residual stress in sequential cutting. It is found that the residual stress on the machined surfaces will decrease during sequential cutting, and a stable value can be reached after approximately six sequential cuts. With the progress of sequential cutting, a larger honed tool edge radius and cutting depth will lead to a slower reduction of residual stress. [ABSTRACT FROM AUTHOR]

Abstract: This paper appraises two major chip formation techniques in finite element (FE) simulation of machining. The first one considers chip formation as a wedge indentation process, while the second one considers chip separation due to ductile fracture. The first technique has been implemented in an Arbitrary Lagrangian–Eulerian (ALE) simulation of machining and the chip formation is assumed to be due to plastic flow. Therefore, the chip is formed by continuous remeshing of the workpiece. In the updated Lagrangian (UL) simulation as an implementation of the second technique, the Johnson–Cook (J–C) damage criterion is used where elements in the sacrificial layer are deleted, as the accumulated damage in such elements exceeds the predefined critical value. The experimental data of the Assessment of Machining Models (AMM) effort for orthogonal cutting is used as a source to verify the models. It is found that predictions of the first technique for strains and temperatures within the deformation zones are not satisfactory and the predicted resistance of workpiece material to cutting is unrealistically high. Instead, the results obtained by second technique are shown to be more reasonable with less computational cost and less possibility of software crash. However, in the case of calculating the field variables the major differences are located in the material separation affected zones; the two thin boundary layers on the cut surface and underside of the chip. [Copyright &y& Elsevier]

Abstract: This paper introduces a derivation and simulation technique of instantaneous stiffness for 6–6 Stewart platforms (hexapods) with the interest in increasing machining accuracy of the new type hexapod machines. It clearly expresses that high non-linearity of motions and driving forces of the parallel mechanisms results in the asymmetric stiffness matrix, and the change in geometry and the loading are the significant factors to the asymmetry. Also, based on the theoretical calculation the simulations for the hexapod machining cycles numerically and illustratively present the instantaneous stiffnesses and deflections of the end-effector (tool tip). Therefore, this work can provide a theoretical principle and an application tool for the anticipation and the evaluation for hexapod machining performance, design optimisation and machining accuracy control, etc. [Copyright &y& Elsevier]

• Model of High Speed Machining (HSM) of Ti6Al4V titanium alloy based on CEL approach • Constitutive model of Ti6Al4V titanium alloy including the state of stress • Prediction of serrated chips using CEL approach for a wide range of cutting speeds • Simulation of material side flow using CEL approach is for the first time achieved • Cyclic variation of the forces and of the characteristics of the machined surface The accuracy of a machining model depends on the capability of this model to describe the physical phenomena associated to the real machining system. This includes the material constitutive model and the approach used to describe the field flow of the material in cutting. In this paper, a model of high speed machining (HSM) of Ti6Al4V titanium alloy is developed. This cutting model includes the proposed constitutive model considering the influence of strain hardening, strain-rate, temperature, and state of stress (e.g., stress triaxiality and Lode parameter) in the material plasticity and damage. Finite Element Method (FEM) using Coupled Eulerian-Lagrangian (CEL) approach is used to simulate the cutting model. A sensitivity analysis of the influence of the mesh topography on the chip geometry and cutting force is performed resulting in the determination of the optimal element size and element orientation. Simulation results obtained using the CEL approach are compared with those obtained using the Lagrangian one. Moreover, simulated cutting force and chip geometry obtained using the proposed constitutive model are compared with those obtained using the Johnson-Cook (J-C) model, and experimental data. Both chip geometry and cutting force predicted by the proposed constitutive model is closer to the experimental one than the J-C constitutive model. The CEL approach combined with the proposed constitutive model can simulate material side flow, which results in a larger width of chip compared to the width of cut, and in the formation of lateral burr on the workpiece. It also permits simulating the cyclic variation of the plastic strain and topography of the machined surface along the cutting direction, observed experimentally. [ABSTRACT FROM AUTHOR]

• The Downhill-Simplex-Algorithm is applicable to the inverse material parameter determination • Selection of the optimization parameters influences the determined results • Adaptive Downhill-Simplex-Algorithm reduces the computational effort • Uniqueness of Johnson-Cook material model parameters is not given for machining simulations Modeling the machining process by means of simulation techniques became more and more popular within the last decades. The increasing use of simulation techniques can be attributed to the enhancing computational performance. To accurately model the machining process, different input models are required. Among them, the material model has a crucial impact on the quality of the simulated results. To determine the underlying material model parameters, an inverse procedure has been established, where the material model parameters are adjusted within a chip formation simulation until a reasonable match between simulations and experiments is achieved. However, the procedure of the inverse determination requires high computational efforts and is not robust. This paper presents a novel approach to determine material model parameters inversely from FE-machining simulations by means of the Downhill-Simplex-Algorithm. An effect study was conducted to investigate the influence of the initial simplex, the boundary conditions, and the underlying parameters of the Downhill-Simplex-Algorithm. Further, the validated procedure has been extended to consider multiple cutting conditions and an adaptive step-size has been implemented into the algorithm. The results of the procedure were validated by re-identification of process observables from the target simulations and it was aimed to re-identify the material model parameters of the target simulations. Based on the algorithm, a robust and systematical method has been developed to determine material model parameters inversely from the machining process. [ABSTRACT FROM AUTHOR]

Residual stress has become more important than ever with the increasing performance requirement of components especially for those applied in safety-critical areas. As the machining process is fundamentally correlated with the acquired component properties, it is essential to fully understand the formation mechanism of residual stresses in the cutting process and its influence on the performance of the component. This paper presents results based on numerical and experimental analysis on the effect of tool geometry on thermal-mechanical load and residual stresses in orthogonal machining Inconel718 alloy. The Coupled Eulerian-Lagrangian (CEL) method is used to simulate the effect of tool geometry on temperatures, forces, equivalent plastic strains, and residual stresses. The local normal/tangential stress is introduced to determine the degree of the tensile plastic deformation induced by the tool. It is observed that a negative rake angle and a sharp edge radius tool tend to generate more compressive stress on the machined surface than the ones generated with positive rake angle tools and/or lager edge radius. Besides, an increase in flank wear produces less magnitude of compressive stress in subsurface due to a decreased local normal stress caused by increased flank contact length. [ABSTRACT FROM AUTHOR]