To shape advanced engineering materials, many unconventional machining processes have been developed. Electrical discharge machining is such an unconventional machining process which is very popular nowadays but it is limited by poor material removal efficiency. Electrical arc machining is another unconventional machining process which is quite similar to electrical discharge machining and is now gaining attention from research fraternity due to its high material removal efficiency. In the present research, an innovative unconventional machining process known as vibration-assisted electrical arc machining has been developed. The performance of vibration-assisted electrical arc machining has been evaluated during machining of Al–B4C metal matrix composite by considering peak current, flushing velocity of dielectric and tool vibrations as input control factors. The quality characteristics considered were material removal rate, tool wear rate, relative electrode wear rate and surface roughness. It has been observed that vibration-assisted electrical arc machining results in approximately 3000% more material removal rate as compared to conventional electrical discharge machining during machining of Al–B4C metal matrix composite. The effects of various input control factors on output parameters have also been discussed. Further modelling and optimization of the process parameters has also been done by artificial intelligence approach.

中文翻译：

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10% B4C/Al金属基复合材料的振动辅助电弧加工

为了塑造先进的工程材料，人们开发了许多非常规的加工工艺。电火花加工是一种非常规加工工艺，目前非常流行，但受到材料去除效率差的限制。电弧加工是另一种非常类似于电火花加工的非常规加工工艺，由于其材料去除效率高，目前正受到研究界的关注。在目前的研究中，开发了一种创新的非常规加工工艺，称为振动辅助电弧加工。在 Al-B4C 金属基复合材料的加工过程中，通过考虑峰值电流，评估了振动辅助电弧加工的性能，电介质的冲洗速度和工具振动作为输入控制因素。考虑的质量特性包括材料去除率、刀具磨损率、相对电极磨损率和表面粗糙度。据观察，在 Al-B4C 金属基复合材料的加工过程中，与传统的放电加工相比，振动辅助电弧加工的材料去除率提高了大约 3000%。还讨论了各种输入控制因素对输出参数的影响。工艺参数的进一步建模和优化也已通过人工智能方法完成。据观察，在 Al-B4C 金属基复合材料的加工过程中，与传统的放电加工相比，振动辅助电弧加工的材料去除率提高了大约 3000%。还讨论了各种输入控制因素对输出参数的影响。工艺参数的进一步建模和优化也已通过人工智能方法完成。据观察，在 Al-B4C 金属基复合材料的加工过程中，与传统的放电加工相比，振动辅助电弧加工的材料去除率提高了大约 3000%。还讨论了各种输入控制因素对输出参数的影响。工艺参数的进一步建模和优化也已通过人工智能方法完成。