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Parameter optimization of electrochemical machining process using black hole algorithm

机译:使用黑洞算法的电化学加工过程参数优化

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Advanced machining processes are significant as higher accuracy in machined component is required in the manufacturing industries. Parameter optimization of machining processes gives optimum control to achieve the desired goals. In this paper, electrochemical machining (ECM) process is considered to evaluate the performance of the considered process using black hole algorithm (BHA). BHA considers the fundamental idea of a black hole theory and it has less operating parameters to tune. The two performance parameters, material removal rate (MRR) and overcut (OC) are considered separately to get optimum machining parameter settings using BHA. The variations of process parameters with respect to the performance parameters are reported for better and effective understanding of the considered process using single objective at a time. The results obtained using BHA are found better while compared with results of other metaheuristic algorithms, such as, genetic algorithm (GA), artificial bee colony (ABC) and bio-geography based optimization (BBO) attempted by previous researchers.
机译:在制造业中需要先进的加工过程,随着机加工部件的更高精度是高精度。加工过程的参数优化为实现所需目标提供最佳控制。本文认为,电化学加工(ECM)工艺被认为使用黑洞算法(BHA)评估所考虑的过程的性能。 BHA考虑了黑洞理论的基本思想,它具有较少的操作参数来调整。两个性能参数,材料去除率(MRR)和过度(OC)是单独认为的,以获得使用BHA的最佳加工参数设置。报告了关于性能参数的过程参数的变化,以便一次使用单个物镜更好地有效地理解所考虑的过程。与其他成群质算法的结果相比,使用BHA获得的结果更好,例如遗传算法(GA),人工蜂殖民地(ABC)和先前研究人员企图的生物地理基于生物地理的优化(BBO)。

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