1,720,981 research outputs found
Modelling of an innovative cryogenic assisted dieless sheet metal piercing process
Full text linkIn tube piercing, if the internal die is necessary to properly pierce the tube avoiding its crushing, it also represents a bottleneck to a rapid change of the piercing/punching set. In this research, an innovative dieless tube piercing approach has been conceived and studied. The use of a cryogenic fluid to force the material ductile-brittle transition is a way to limit the sheet deformation during the dieless piercing process. The analysis of the innovative cryogenic piercing process was carried out both adopting numerical and experimental methodologies. A finite element FE model of the cryogenic piercing was developed and updated in two stages. First, experimental tensile tests, performed at cryogenic temperatures, were used to characterize some material properties. Secondly, some piercing tests in cryogenic conditions were carried out at different velocities and temperatures to fine update the model. A validation session was executed to assess the model and the process feasibility. It was found that the FE model reproduced the experimental results within a maximum estimation error of 10 % on both the required piercing force and on the deviation from the nominal dimension of the tube cross-section. Although the piercing tests were conducted at quite a low temperature (−80 °C), an extended analysis of the wall fractures confirmed that a proper ductile-to-brittle transition did not occur. Further increasing the punching velocity and especially decreasing the piercing temperature could be the only viable solutions to promote the transition and further reduce tube deformation
A novel harmonic solution for chatter stability of time periodic systems
Full text linkChatter vibrations strongly limit productivity in milling. Due to the presence of rotating parts with asymmetric stiffness and stability enhancement strategies which act through a periodic variation of stiffness, there is growing interest in estimating the stability maps of systems with Linear Time Periodic dynamics together with periodic cutting excitation. Applying Exponentially Periodic Modulated test signals to the dynamic cutting force equation and representing the dynamics of the system through the Harmonic Transfer Function, the innovative Harmonic Solution (HS) and its zero-order approximation were derived in this research. HS is a frequency domain representation of a system described by the combination of two independent periodicities. It is possible to take into account these periodicities together in HS or singularly, resulting in the Zero Order HS or in the well-known Multi-Frequency Solution. This novel formulation can deal efficiently with spindle dependent and independent dynamics and is prone to industrial applications due to its flexibility and efficiency. More specifically, in this work the developed methodologies were used to assess the cutting stability of systems with a periodically modulated stiffness. The accuracy and efficiency of HS were validated by comparison with the results achieved by the use of the semi-discretization method. Results are in agreement with those obtained using semi-discretization. Moreover, admitting a slight precision loss, HS and its zero-order approximation are orders of magnitude faster than semi-discretization, giving reliable stability maps from seconds to a few minutes
Mechanistic force model for double-phased high-feed mills
Full text linkBeing able to predict cutting forces, torque and power in machining applications allows to check their influence on the quality of the product, to assess the feasibility of the process and to compare different operations for sustainability purposes. In this paper, the analytical development of a mechanistic model for cutting forces prediction for high-feed mills is carried out. High-feed cutters are featured by extremely low lead angles, leading to a gradual engagement of the cutter inside the workpiece. This fact prevents the mechanistic literature formulation to accurately compute the undeformed instantaneous chip section of each cutter, and thus to correctly predict the spindle torque and power. A closed analytical formulation for the mechanistic cutting force model, including an improved chip thickness formulation with variable entry and exit angles and double-phased cutter geometry, is presented. Experimental cutting tests using double-phased high-feed mills were carried out on with variable feed rate per tooth, cutting speed and axial depth of cut. The model was assessed by comparing the performances of the literature model and the developed high-feed one in the identification of specific force coefficients — SFC. The identified SFC resulted to belong to two statistically different populations. SFC 95% confidence intervals were found to be significantly narrower with respect to the literature ones. 95% confidence intervals were equal to (1085; 1426) MPa and (970; 2423) MPa for the proposed and literature model, respectively. The validity of the proposed model was assessed in terms of mean forces, mean spindle torque and mean spindle power prediction capabilities. The Root Mean Squared Prediction Error for the proposed model resulted to be remarkably lower (15 N, 0.33 Nm, 29 W) with respect to literature model (41 N, 1.25 Nm, 120 W)
A review of prognostics and health management of machine tools
Full text linkThis paper presents a survey of the applications of prognostics and health management maintenance strategy to machine tools. A complete perspective on this Industry 4.0 cutting-edge maintenance policy, through the analysis of all its preliminary phases, is given as an introduction. Then, attention is given to prognostics, whose different approaches are briefly classified and explained, pointing out their advantages and shortcomings. After that, all the works on prognostics of machine tools and their main subsystem are reviewed, highlighting current open research areas for improvement
Mill condition monitoring based on instantaneous identification of specific force coefficients under variable cutting conditions
Full text linkFollowing the necessity of increased performance and availability requirements for manufacturing systems, research is becoming more and more attracted by monitoring solutions for cutting tools. In this paper, a robust unsupervised strategy for milling tool wear monitoring under variable process parameters and lubrication conditions is presented. The proposed method is completely unsupervised, thus not requiring any kind of training procedure, and is validated on different machine tools. The solution is based upon the online estimation of specific force coefficients (SFC) from instantaneous cutting forces in high-feed milling of Ti6Al4V workpiece. This avoids the need for continuously variable feed per tooth during cutting tests, necessitated for the application of reference literature approach. For this purpose, a novel high-feed mill mechanistic model was conceived and developed. Five run-to-failures were performed in different lubrication conditions – cryogenic and traditional lubrication – with different cutting speeds (50 m/min, 70 m/min and 125 m/min) on two different machine tools. Principal Component Regression was introduced in order to deal with the variability of the estimated coefficients. Self-starting tabular cusum control charts were implemented and demonstrated high accuracy and reliability in the prediction of notch wear phenomena as well as chipping of tool cutting edges for all the cases considered. The solution detected an out-of-control conditions ranging from 166μm to 499μm of maximum flank wear for the analysed tests. The mean prediction error with respect to the 600μm threshold is of −45% with a peak of −72%, whereas reference literature algorithms reach −57% and −66%, respectively. A sensitivity analysis of control chart threshold was performed with reference to the maximum flank wear at the detection point. In a supervised scenario, the threshold can be increased to obtain a less conservative approach: for instance, a mean prediction error of −41% was reached by doubling the threshold
A novel simulation methodology for orthogonal cryogenic machining with CFD spray cooling integration
Full text linkThe performance of cryogenic machining depends on the effectiveness of the heat transfer between the coolant jet and the chip in the cutting area because it affects the material temperature and the mechanical properties of the chip. This is a complex multi-physics problem because the solid deformation depends on the thermal and fluid–dynamic interaction with the cryogenic droplets generated by the atomization of the coolant jet. Within this context, this work applies an innovative methodology based on computational fluid dynamics to simulate the cutting process accounting for the interaction with the cryogenic jet. The proposed approach does not require empirical correlations since it integrates a predictive machining analytical model with Conjugate Heat Transfer CFD simulation and spray modelling to accurately estimate the heat transfer process accounting for the cooling effect of the impinging droplets. Complete Ti6Al4V dry and cryogenic cooled orthogonal cutting simulations were performed and results were compared with literature experimental data and state-of-the-art Finite Element Modelling simulations. The proposed methodology correctly estimates the cutting forces to vary cutting velocity and depth. Average errors in the resultant force estimation are 11.85% in dry and 14.4% in cryogenic cutting. Moreover, the experimental increase of the cutting force due to cooling is better estimated by the proposed approach with respect to FEM simulations. Thanks to the results accuracy and reduced computational costs, the proposed methodology could improve the understanding and the design of this innovative machining technology
Hybrid heterogeneous prognosis of drill-bit lives through model-based spindle power analysis and direct tool inspection
Full text linkAbstract: In the context of Industry 5.0, manufacturing systems are driven by human-centered production processes, assigning high-level supervisory tasks to operators. This necessitates that machines can perform low-level decision-making actions. This paper presents a novel hybrid heterogeneous prognosis algorithm designed to autonomously inspect the cutting edges of drill-bits and to forecast their Remaining Useful Life along with the associated probability density function. The algorithm leverages specific force coefficients from spindle power and feed axis current measurements, as features correlated with tool wear, to detect tool brittle failures. Additionally, flank wear is automatically measured through a specifically conceived image processing algorithm, using thresholding, convolutional filters, and edge detection techniques. Direct tool wear measurements are analyzed by a hybrid prognosis algorithm, fusing particle filter and multi-layer perceptron, to predict drill-bits’ remaining useful lives. The proposed solution offers several advantages. It reduces the need for extensive experimental run-to-failure tests typically required for training standard machine learning algorithms. Instead, it allows for real-time adaptation, even in scenarios involving untested and varying cutting process conditions. Furthermore, it utilizes both indirect wear observations during cutting operations and direct wear observations during setup times (e.g. tool changes, workpiece changes), without interrupting the ongoing process. Exponent of Kronenberg’s models for specific force coefficients was found to be sensitive to tool wear. Prognosis could correctly predict the 67% of end-of-lives with an average prognosis horizon of 30%
Simulation of the effects of cryogenic liquid nitrogen jets in Ti6Al4V milling
Full text linkIn this research, a 3D Finite Element simulation model of Ti6Al4V milling with internal delivery of liquid nitrogen LN2 was developed to understand the effects of the cryogenic jets on the cutting mechanics. The numerical model was thoroughly validated comparing the simulated forces and chip morphologies with the corresponding experimental findings, obtained in different cutting conditions. In both cryogenic and dry conditions, the numerical results were in strong agreement with the experiments. Maximum errors in the average main force estimation and in the distance between chip serrations resulted to be respectively 13 % and 17.6 %. The developed model predicted the forces along other directions within an average error of 13.8 % on their maximum values and 27.7 % on their mean values. Experimental findings showed that the main cutting forces were reduced (on average by 22 %) due to cryogenic cooling, that also produced more damaged and fragmented chips. Moreover, cryogenic cooling averagely reduced (−22 %) the distance between chip serrations. The analysis of the simulation results revealed that cryogenic cooling reduced the tool-chip interface temperature of 150–200 °C due to the simultaneous cryogenic cooling action and to lower (about −35 %) tool-chip friction that limited the associated produced heat that represents at least one-tenth of the overall cutting power
Energy Efficiency of the Vulcanization Process of a Bicycle Tyre
Full text linkThe production of tyres is one of the most energy consuming manufacturing activities in the rubber sector. In the production cycle of a tyre, the curing operation has the maximum energy loss. This is mostly due to the extensive use of steam as a source of heat and pressure in the vulcanization process. To the author’s knowledge, no scientific work is available in the literature where the energy efficiency of a tyre vulcanization press is estimated by means of a comprehensive model of all main components, including the moulds, the press with its heated plates, the bladder and, of course, the tyre. The present work aims at filling this gap. First, the press used for developing the model is described, along with its components and its typical product, a bicycle tyre. The instruments used for measuring flow rates, temperatures and pressures are also listed. Then, a numerical model is presented, that predicts the energy transfers occurring in the vulcanization press during a full process cycle. The numerical model, developed with the software Simcenter Amesim 2021.1, has been validated by means of measurements taken at the press. The results indicate that the amount of energy which is actually consumed by the tyre for its reticulation process amounts to less than 1% of the total energy expenditure. The paper demonstrates that the tyre industry is in urgent need of an electrification conversion of the traditional steam-based processes
Robust tool condition monitoring in Ti6Al4V milling based on specific force coefficients and growing self-organizing maps
Full text linkTool condition monitoring (TCM) is a mean to optimize production systems trying to use cutting tool life at its best. Nevertheless, nowadays available TCM algorithms typically lack robustness in order to be consistently applied in industrial scenarios. In this paper, an unsupervised artificial intelligence technique, based on Growing Self-Organizing Maps (GSOM), is presented in synergy with real-time specific force coefficients (SFC) estimation through the regression of instantaneous cutting forces. The conceived approach allows robustly mapping the SFC, exploiting process parameters and similarity to manage the variability of their estimation due to unmodelled phenomena, like machine dynamics and tool run-out. The devised approach allowed detecting the tool end-of-life in cutting tests with variable lubrication, machine tool and cutting speed, through the adoption of a self-starting control chart running on real-time clustered data. The solution was validated through the comparison of the GSOM framework with respect to the optimized self-starting control chart applied without GSOM clustering. The GSOM reached a root mean squared percentage error (RMSPE) of 13.2% with respect to 56.1% obtained with the analogous control chart in a full-set optimization scenario. When optimised on tests for a unique machine tool and tested on another machine tool, GSOM scored an RMSPE of 34.5%, whereas the optimized control chart scored 64.5%
- …
