1,721,011 research outputs found
Continuous multi-angle variation (CMAV) for faster roundness correction in centreless grinding
Full text linkThis paper presents a new methodology to improve roundness process of the centreless grinding based on classic stability diagrams and relative rounding mechanism. This study has shown that it is not always convenient to have a fixed setup angle. Based on simulation results, it is suggested to consider the raw workpiece profile before selecting these parameters accordingly to the type of raw workpiece roundness error (odd or even lobed). It was found that changing the setup angles from an initial appropriate point to a final point results in better simulated and experimented roundness. This changing was simulated with two methods, continuous and multistep, but the best results were achieved by the first one. Furthermore, a new support blade design for through feed centreless grinding is presented for application of the above-mentioned method
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
The effect of pressure on the surfaces generated by waterjet: Preliminary analysis
No full textThe pressure fluctuation in the waterjet (WJ) process is due to the mechanism of high pressure generation, characterized by a cyclical working, and to physical causes (water compressibility at the exercise pressures). This phenomenon cannot, at present, be removed; however, it can be dampened, depending on the selected constructive system, by installing a pulsation attenuator below the intensifier or by conveniently phasing the pumping cycles of more intensifiers in parallel. In this paper, the effects of the pressure on the WJ process have been investigated. The pressure signals generated by a double-acting reciprocating intensifier pump system have been analysed; the effects of the pressure fluctuation and of the pressure signal form on the cutting quality have been studied through the acquisition of the roughness profiles of the surface of various materials (rubber, polycarbonate, plasticine) generated by waterjet
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%
Investigation of the influence of the AWJ-specific energy on the cutting kerf profile on aluminium 6082
Full text linkThis study introduces the abrasive waterjet specific energy as a novel physical quantity to characterize the taper ratio in abrasive waterjet cutting. Said quantity was defined as a proper combination of the most influential control factors. A series of abrasive waterjet cutting experiments on aluminium 6082, were conducted, according to the design of experiments methodology. For each experimental run, the width of the kerf profile was measured and characterized in terms of taper ratio. The effect of the abrasive waterjet specific energy and the main process parameters on the measured quantities were investigated. Results showed that inside the experimental range of the process parameters, the abrasive waterjet specific energy correlates well with the taper ratio. As a conclusion, different combinations of the control factors (water pressure, abrasive mass flow rate, feed rate), corresponding to the same level of abrasive waterjet specific energy, produced the same cutting kerf geometry as well as the same taper ratio. This result gives freedom to the waterjet users in selecting the best parameter combination according to some criteria (e.g., time or cost) for achieving the target AWJ-specific energy and the consequent kerf quality
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%
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
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