EDM Drilling Optimisation Using Stochastic Techniques

Procedia CIRP(2018)

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摘要
EDM (Electric Discharge Machining) drilling is a widely used machining process to create holes in hard to machine materials, such as cooling holes in turbine blades and diesel injectors. In such production applications where a large number of holes are machined, productivity is of high importance, which can be achieved through process optimisation. However, due to the involved complex physical phenomena, optimisation of EDM drilling process is largely based on the manual experimentation, as opposed to mechanistic model based optimisation. In this work, stochastic optimisation algorithm is used to optimise EDM drilling process. The robustness of the algorithm is evaluated for different EDM drilling process disturbances, such as electrode length and electrode shape. The performance of the optimisation algorithm is further evaluated in terms of effect of initial parameters and number of iterations required to converge to the optimal parameter values, to achieve highest material removal rate (MRR). It is found that the optimisation algorithm is able to reach the optimal values after about 40 iterations, where the achieved MRR is at least 10% higher than the MRR obtained by using the high speed strategy from the standard machine technology.
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关键词
EDM,Drilling,Optimisation,Machine learning
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