D. Umbrello

MODELING OF WHITE AND DARK LAYER FORMATION IN HARD MACHINING OF AISI 52100 BEARING STEEL

In machining of hardened materials, maintaining surface integrity is one of the most critical requirements. Often, the major indicators of surface integrity of machined parts are surface roughness and residual stresses. However, the material microstructure also changes on the surface of machined hardened steels and this must be taken into account for process modeling. Therefore, in order for manufacturers to maximize their gains from utilizing hard finish turning, accurate predictive models for surface integrity are needed, which are capable of predicting both white and dark layer formation as a function of the machining conditions. In this paper, a detailed approach to develop such a finite element (FE) model is presented. In particular, a hardness-based flow stress model was implemented in the FE code and an empirical model was developed for describing the phase transformations that create white and dark layers in AISI 52100 steel. An iterative procedure was utilized for calibrating the proposed empirical model for the microstructural changes associated with white and dark layers in AISI 52100 steel. Finally, the proposed FE model was validated by comparing the predicted results with the experimental evidence found in the published literature.

On the Finite Element Simulation of Thermal Phenomena in Machining Processes

Machining processes are frequently investigated by numerical simulations. Usually 2D analyses are carried out in order to reduce CPU times, considering orthogonal cutting conditions. In this way, the computational time sharply reduces and many process variables may be calculated (i.e. forces, chip morphology, shear angle, contact length). On the other hand, the analysis of thermal aspects involved in machining, for instance the temperature distribution reached in tool, still represents an open problem. Finite element codes are able to simulate a very short process time that is not sufficient to reach steady state conditions. Several approaches have been proposed to overcome this problem: in the paper some of them are applied and critically discussed.

Finite Element Modeling of Microstructural Changes in Hard Turning

The material grain size changes significantly during machining of hardened steels, and this must be taken into account for improved modeling of surface integrity effects resulting from machining. Grain size changes induced during orthogonal cutting of hardened AISI 52100 (62 HRC) are modeled using the Finite Element (FE) method; in particular, a user subroutine involving a hardness-based flow stress model is implemented in the FE code and empirical models are utilized for describing the phase transformation conditions to simulate formation of white and dark layers. Furthermore, a procedure utilizing the Zener-Hollomon relationship is implemented in the above-mentioned user subroutine to predict the evolution in material grain size at different cutting speeds (300, 600, 900 SFPM). All simulations were performed for dry cutting conditions using a low CBN-content insert (Kennametal KD050 grade, ANSI TNG-432 geometry). The model is validated by comparing the predicted results with experimental evidence available in the literature.

DEPENDENCE OF MACHINING SIMULATION EFFECTIVENESS ON MATERIAL AND FRICTION MODELLING

Numerical simulation of cutting processes is still a very difficult matter, although some relevant geometrical simplifications and high-performance codes are used. A large number of technical papers have been focused on the predictive capability of the codes: nevertheless the prediction quality is not very satisfactory if the problem is analyzed in a wide sense. In this paper the simple orthogonal cutting process of a plain-carbon steel is investigated taking into account different process conditions (cutting speed and feed rate). Furthermore, four material constitutive equations and three friction models were implemented and a sensitivity analysis was carried out comparing the numerical predictions and the experimental evidences. The results of this wide analysis are described in the paper.

Evaluation of Present Numerical Models for Predicting Metal Cutting Performance And Residual Stresses

Efforts on numerical modeling and simulation of metal cutting operations continue to increase due to the growing need for predicting the machining performance. A significant number of numerical methods, especially the Finite Element (FE) and the Mesh-free methods, are being developed and used to simulate the machining operations. However, the effectiveness of the numerical models to predict the machining performance depends on how accurately these models can represent the actual metal cutting process in terms of the input conditions and the quality and accuracy of the input data used in such models. This article presents results from a recently conducted comprehensive benchmark study, which involved the evaluation of various numerical predictive models for metal cutting. This study had a major objective to evaluate the effectiveness of the current numerical predictive models for machining performance. Five representative work materials were carefully selected for this study from a range of most commonly used work materials, along with a wide range of cutting conditions usually found in the published literature. The differences between the predicted results obtained from the various numerical models using different FE and Mesh-free codes are evaluated and compared with those obtained experimentally.

Experimental analysis of mechanisms related to white layer formation during hard turning of AISI 52100 bearing steel

Abstract Microstructural phase transformations, commonly named white layer on hard turned components, are becoming one of the most interesting research subjects for the scientific community. Three main theories have been proposed to justify the mechanisms of white layer formation: rapid heating and quenching, which results in sudden microstructural phase transformation; severe plastic deformation, which produces a homogenous structure and/or a very fine grain size microstructure; and surface reaction with the environment. The present work aims to understand which of the above mentioned mechanisms is the main cause of the white layer formation when AISI 52100 hardened steel is machined by cubic boron nitride inserts. For this reason, an experimental campaign was carried out, and several experimental techniques were used in order to analyse the machined surface. In particular, optical and scanning electron microscope were utilised for surface topography characterisation, while microstructural phase composition and chemical characterisation have been performed by means of X-ray diffraction and energy dispersive spectroscopy techniques. The experimental results prove that the white layer is the result of microstructural alteration, i.e. the generation of a martensitic structure.

Experimental and FEM Analysis of Cutting Sequence on Residual Stresses in Machined Layers of AISI 316L Steel

The reliability of a mechanical component depends to a large extent on the physical state of its surface layers. This state includes the distribution of residual stresses induced by machining. Residual stresses in the machined surface and subsurface are affected by the cutting tool, work material, contact conditions on the interfaces, cutting regime parameters (cutting speed, feed and depth of cut), but also depends on the cutting procedure. In this paper, the effects of cutting sequence on the residual stress distribution in the machined surface of AISI 316L steel are experimentally and numerically investigated. In the former case, the X-ray diffraction technique is applied, while in the latter an elastic-viscoplastic FEM formulation is implemented. The results show that sequential cut tends to increase superficial residual stresses. A greater variation in residual stresses is observed between the first and the second cut. Moreover, an increase in the thickness of the tensile layer is also observed with the number of cuts, this difference also being greater between the first and the second cut. Based on these results, the residual stress distribution on the affected machined layers can be controlled by optimizing the cutting sequence.

Experimental Investigation to Optimize Tool Life and Surface Roughness in Inconel 718 Machining

In addition to the cutting conditions, the surface quality is also affected significantly by a worn tool in machining processes. Identification of the desirable tool life so that the surface quality is maintained within a desirable level is an essential task, especially in the machining of hard materials. In this paper, an optimal tool life and surface quality were identified in the turning operation of Inconel 718 Superalloy by means of experimental investigations and intelligent methods. First, the effect of machining time (MT) at the different cutting parameters was widely investigated on the surface roughness using the neural network model. Then, the modified Non-dominated Sorting Genetic Algorithm (NSGA) was implemented to optimize tool life and surface roughness. For this purpose, a new approach was implemented and the MT was taken into account as the input and output parameters during the optimization. Finally, the results of optimization were classified and the suitable states of the machining outputs were found. The results indicate that the implemented strategy in this paper provides an efficient approach to determine a desirable criterion for tool life estimation in machining processes.

Optimal design of tube hydroforming processes: a fuzzy-logic-based approach

Abstract In recent years, tube hydroforming has become an economic and industrially suitable alternative to various traditional stamping processes, in particular for small batch production. In the present paper, an artificial intelligence system based on fuzzy logic was implemented for tube hydroforming process design. The aim was to achieve a process design procedure able to prevent forming defects and guarantee the achievement of the desired final shape of the component. In particular, the process design concerns the internal pressure history and the axial feeding. The fuzzy system is able to provide optimal trajectories for both the controlled parameters, producing a defect-free final part.

Analysis of Surface Integrity in Dry and Cryogenic Machining of AZ31B Mg Alloys

Surface integrity of machined products can have a critical impact on their performance, such as corrosion, wear and/or fatigue resistance. It has been reported that reducing the grain size of AZ31B Mg alloys could significantly enhance its corrosion resistance, which is often the limiting factor for its wide application. Severe plastic deformation (SPD) has proved to be an effective way to induce grain refinement. In this study, the potential of cryogenic machining as a novel SPD method to induce grain refinement on the surface of AZ31B Mg alloys was investigated. The microstructures of the workpiece surface/sub-surface and the machined chips after both dry and cryogenic machining were studied. A surface layer where nanocrystallized grains exist was found in the machined surface under cryogenic conditions. Increasing the edge radius of the cutting tool resulted in a thicker grain refinement layer. In addition to the experimental study, an FE model based on the Johnson-Cook constitutive equation was developed and validated using experimental data in terms of chip morphology and forces. The capability of this model to predict critical deformation parameters for dynamic recrystallization (DRX), such as strain, strain-rate and temperature, was demonstrated. With further development, the model can be used to predict the onset of DRX and the grain size on the machined surface.