Optimization of wire electrical discharge machining (WEDM) process parameters using Taguchi method
Optimization of wire electrical discharge machining (WEDM) process parameters using Taguchi method
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DOI：
10.1007/s00170-006-0672-6
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发表时间：
2007-10-01
影响因子：
3.4
通讯作者：
Patnaik, Amar
中科院分区：
文献类型：
--
作者：
Mahapatra, S. S.;Patnaik, Amar
当精度至关重要时，线切割放电加工 (WEDM) 广泛用于导电材料的加工。线切割加工中的粗切削操作被视为一项具有挑战性的操作，因为改进不止一种加工性能衡量标准，即：寻求金属去除率 (MRR)、表面光洁度 (SF) 和切割宽度 (kerf) 以获得精密工件。使用田口的参数设计，影响性能测量的重要加工参数被确定为放电电流、脉冲持续时间、脉冲频率、线速度、线张力和介电流。据观察，用于优化每个性能指标的因素组合是不同的。在本研究中，通过非线性回归分析建立了控制因素与响应（如 MRR、SF 和 kerf）之间的关系，从而建立了有效的数学模型。最后，采用流行的进化方法遗传算法来优化多目标的电火花线切割加工工艺。研究表明，可以调整线切割加工工艺参数，以同时实现更好的金属去除率、表面光洁度和切割宽度。
Wire electrical discharge machining (WEDM) is extensively used in machining of conductive materials when precision is of prime importance. Rough cutting operation in WEDM is treated as a challenging one because improvement of more than one machining performance measures viz. metal removal rate (MRR), surface finish (SF) and cutting width (kerf) are sought to obtain a precision work. Using Taguchi's parameter design, significant machining parameters affecting the performance measures are identified as discharge current, pulse duration, pulse frequency, wire speed, wire tension, and dielectric flow. It has been observed that a combination of factors for optimization of each performance measure is different. In this study, the relationship between control factors and responses like MRR, SF and kerf are established by means of nonlinear regression analysis, resulting in a valid mathematical model. Finally, genetic algorithm, a popular evolutionary approach, is employed to optimize the wire electrical discharge machining process with multiple objectives. The study demonstrates that the WEDM process parameters can be adjusted to achieve better metal removal rate, surface finish and cutting width simultaneously.