Improper selection of cutting parameters leads to regenerative chatter and loss in productivity. In the present work, a methodology has been proposed to select a proper combination of input cutting parameters for stable turning with improved metal removal rate. Chatter signals generated during the turning of Al6061-T6 have been acquired using a microphone. Stability lobes diagram has been plotted to access the stability regime. Further, to study the effect of feed rate on stability, the recorded signals have been processed using local mean decomposition signal processing technique, followed by the selection of dominating product functions using Fourier transform. The decomposed signals have been used to evaluate the new output parameter, that is, chatter index. Prediction models of chatter index and metal removal rate have been developed. Moreover, these prediction models have been optimized using multi-objective genetic algorithm for ascertaining the optimal range of cutting parameters for stable turning with higher metal removal rate. Finally, obtained stable range has been validated by performing more experiments.

切削参数选择不当会导致再生颤振和生产率下降。在当前的工作中，已经提出了一种方法来选择输入切削参数的适当组合，以稳定的车削并提高金属去除率。在Al6061-T6转向期间产生的颤动信号已使用麦克风获取。绘制了稳定瓣图以访问稳定状态。此外，为了研究进给速度对稳定性的影响，已使用局部均值分解信号处理技术对记录的信号进行了处理，然后使用傅立叶变换选择了主要乘积函数。分解后的信号已用于评估新的输出参数，即颤振指数。建立了颤振指数和金属去除率的预测模型。此外，这些预测模型已使用多目标遗传算法进行了优化，以确定切削参数的最佳范围，以便在较高的金属去除率的情况下进行稳定的车削。最后，通过进行更多的实验验证了获得的稳定范围。