Machine Learning-Based Reverse Modeling Approach for Rapid Tool Shape Optimization in Die-Sinking Micro Electro Discharge Machining
Article dans une revue avec comité de lecture
This paper focuses on efficient computational optimization algorithms for the generation of micro electro discharge machining (µEDM) tool shapes. In a previous paper, the authors presented a reliable reverse modeling approach to perform such tasks based on a crater-by-crater simulation model and an outer optimization loop. Two-dimensional results were obtained but 3D tool shapes proved difficult to generate due to the high numerical cost of the simulation strategy. In this paper, a new reduced modeling optimization framework is proposed, whereby the computational optimizer is replaced by an inexpensive surrogate that is trained by examples. More precisely, an artificial neural network (ANN) is trained using a small number of full reverse simulations and subsequently used to directly generate optimal tool shapes, given the geometry of the desired workpiece cavity. In order to train the ANN efficiently, a method of data augmentation is developed, whereby multiple features from fully simulated EDM cavities are used as separate instances. The performances of two ANN are evaluated, one trained without modification of process parameters (gap size and crater shape) and the second trained with a range of process parameter instances. It is shown that in both cases, the ANN can produce unseen tool shape geometries with less than 6% deviation compared to the full computational optimization process and at virtually no cost. Our results demonstrate that optimized tool shapes can be generated almost instantaneously, opening the door to the rapid virtual design and manufacturability assessment of µEDM die-sinking operations.
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Article dans une revue avec comité de lectureSURLERAUX, Anthony; LEPERT, Romain; PERNOT, Jean-Philippe; BIGOT, Samuel (Future Technology Press, 2015)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 ...
Communication avec acteBIGOT, Samuel; PERNOT, Jean-Philippe; SURLERAUX, Anthony; ELKASEER, Ahmed (2013)This paper introduces a new method for simulating the micro-EDM process in order to predict tool wear. The tool and workpiece are defined by NURBS surfaces whose shapes result from an iterative crater-by-crater deformation ...
Article dans une revue avec comité de lectureSURLERAUX, Anthony; PERNOT, Jean-Philippe; ELKASEER, Ahmed; BIGOT, Samuel (Springer Verlag, 2016)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 ...
Article dans une revue avec comité de lectureBIGOT, Samuel; D'URSO, Gianluca; PERNOT, Jean-Philippe; MERLA, Cristina; SURLERAUX, Anthony (Elsevier, 2016)This paper presents a new approach for the recording of the total quantity of energy exchanged during the micro electrical discharge machining (EDM) process. In particular, this approach allows for the estimation of the ...
Communication avec acteSURLERAUX, Anthony; BIGOT, Samuel; PERNOT, Jean-Philippe; D'URSO, Gianluca; MERLA, Cristina (2015)The present paper introduces the use of voxels embedded in an octree structure in order to numerically simulate manufacturing processes. In particular, micro electrical discharge machining (μEDM) is used here as a case ...