A CutFEM method for Stefan-Signorini problems with application in pulsed laser ablation

In this article, we develop a cut finite element method for one-phase Stefan problems, with applications in laser manufacturing. The geometry of the workpiece is represented implicitly via a level set function. Material above the melting/vaporisation temperature is represented by a fictitious gas phase. The moving interface between the workpiece and the fictitious gas phase may cut arbitrarily through the elements of the finite element mesh, which remains fixed throughout the simulation, thereby circumventing the need for cumbersome re-meshing operations. The primal/dual formulation of the linear one-phase Stefan problem is recast into a primal non-linear formulation using a Nitsche-type approach, which avoids the difficulty of constructing inf-sup stable primal/dual pairs. Through the careful derivation of stabilisation terms, we show that the proposed Stefan-Signorini-Nitsche CutFEM method remains stable independently of the cut location. In addition, we obtain optimal convergence with respect to space and time refinement. Several 2D and 3D examples are proposed, highlighting the robustness and flexibility of the algorithm, together with its relevance to the field of micro-manufacturing

Computer-aided Micro-EDM die-sinking tool design optimisation

This paper describes a new efficient method for computer aided optimisations of micro EDM die sinking tools, which can be used for design optimisation and performance verification in the digital domain. This would facilitate the integration and re-configurability of the micro EDM die sinking process in high value products manufacturing chains. An EDM simulation tool which makes use of voxels embedded in a voxel octree to represent the geometries is introduced and its application to a new Micro-EDM die-sinking tool shape optimisation is then described. Simulation results obtained with simple shapes are then discussed highlighting the capabilities of the new optimisation method and potential areas of improvement are proposed

Iterative surface warping to shape craters in micro-EDM simulation

This paper introduces a new method for simulating the micro-EDM process in order to predict both the tool’s wear and the workpiece’s roughness. The tool and workpiece are defined by NURBS patches whose shapes result from an iterative crater-by-crater deformation technique driven by physical parameters. Through hundreds of thousands of local surface warping, the method is able to compute the global as well as the local shapes of the tool and workpiece. At each step, the warping vector and function are computed so as to be able to generate a spherical crater whose volume is also controlled. While acting very locally to simulate the real physical phenomenon, not only the method can evaluate the tool’s wear from the overall final shape at a low resolution level, but it can also estimate the workpiece’s roughness from the high resolution level. The simulation method is validated through a comparison with experimental data. Different simulations are presented with an increase in computation accuracy in order to study its influence on the results and their deviation from expected values

Iterative surface warping to shape craters in micro‐EDM simulation

This paper introduces a new method for simulat- ing the micro-EDM process in order to predict both the tool’s wear and the workpiece’s roughness. The tool and workpiece are de ned by NURBS patches whose shapes result from an iterative crater-by-crater deformation technique driven by physical parameters. Through hundreds of thousands of local surface warping, the method is able to compute the global as well as the local shapes of the tool and workpiece. At each step, the warping vector and function are computed so as to be able to generate a spherical crater whose volume is also controlled. While acting very locally to simulate the real physical phenomenon, not only the method can evaluate the tool’s wear from the overall nal shape at a low resolu- tion level, but it can also estimate the workpiece’s roughness from the high resolution level. The simulation method is validated through a comparison with experimental data. Dif- ferent simulations are presented with an increase in compu- tation accuracy in order to study its in uence on the results and their deviation from expected values

A movel hybrid Bees Regression Convolutional Neural Network (BA-RCNN) applied to porosity prediction in selective laser melting parts

Convolutional Neural Network (CNN) is a Deep Learning (DL) technique used for image analysis. CNN can be used in manufacturing, for predicting the percentage of porosity in the finished Selective Laser Melting (SLM) parts. This paper presents a new approach based on Regression Convolutional Neural Network (RCNN) for assessing the porosity which was better than the existing image binarization method. The algorithms were applied to artificial porosity images that were similar to the real images with a 0.9976 similarity index. The RCNN yielded a prediction accuracy of 75.50% compared to 68.60% for image binarization. After the RCNN parameters were optimized using the Bees Algorithm (BA), the application of the novel Bees Regression Convolutional Neural Network (BA-RCNN) improved the porosity prediction accuracy further to 85.33%. When three noise levels were used to examine its sensitivity to noise, the novel hybrid BA-RCNN was found to be less sensitive to noise

Estimating the exchanged energy distribution in micro-EDM

This paper presents a new approach for the recording of the total quantity of energy exchanged during the micro Electro Discharge Machining (EDM) process. In particular, this approach allows for the estimation of the percentage of energy absorbed by the two electrodes (tool and workpiece) using a combination of theoretical models and experimental results, thanks to an advanced discharges measuring approach. The validity of several theoretical crater models was then assessed. Using this approach, the process was analysed for two electrode shapes and two sets of machining parameters. The preliminary results appears to fit those presented in the literature