Investigation on laser beam and micro electro discharge machining based hybrid micromachining

Abstract

This research aims to develop a sequential hybrid micromachining technique that combines the advantages of laser beam micromachining (LBMM) and micro electro-discharge machining (µEDM). LBMM has the disadvantage of low machining quality, although laser machining offers a very fast processing time. While micro µEDM takes a longer time and has a slower material removal rate (MRR), the final product is of higher quality than laser-machined parts. This research shows that the sequential machining process (LBMM followed by µEDM) improves quality of the machined product with a faster processing time. In the process the LBMM is used to machine a pilot feature, and µEDM is then used to complete the feature. In the first stage of this research, we conducted experiments on stainless steel (type SS304) to determine how different input parameters of LBMM (laser power, scanning speed, and pulse frequency) affected the performance of the finishing technique, that is, the µEDM in this case. In this 1-D machining or micro-hole drilling, it was observed that the output performance of µEDM was significantly influenced by the laser input parameters, particularly scanning speed and power. The results of our research indicate that the µEDM finishing time can be significantly increased by using a higher laser scanning speed at a lower laser power during the pilot machining. However, the processing time for the EDM operation is shortened if the pilot hole drilling is done at a slower scanning speed and with a higher laser power. Our findings verify that the LBMM-based sequential machining technique leads to a significant reduction in machining time, tool wear, and instability (in terms of short circuit/arc) when compared to a purely µEDM process. The results of the experiment show that the input and output parameters of the sequential process have strong relationships. Because of this, a dual-stage modeling approach based on ANNs was developed to forecast the results of the sequential process. To evaluate the output performance of LBMM- µEDM based sequential process, in first step the laser parameters were varied and the µEDM input parameters was constant. In the second step, both the laser input parameter and the µEDM input parameters were altered in the subsequent phase of the research. The dual-stage modeling method was used, and this time the µEDM input parameters (voltage, capacitance, and EDM speed) were not kept the same. Root Mean Square Errors (RMSEs) were calculated for each data set and each output parameter (i.e., µEDM time, machining instability/short circuit count, and tool wear) to figure out the model accuracy. Average RMSE was calculated to be 0.050 (95% accuracy), 0.040 (96% accuracy), and 0.110 (89% accuracy) for the previously mentioned parameters. In this study's final phase, 3-D hybrid micromachining (milling) was tested using Response Surface Methodology (RSM) to identify the significant factors influencing this sequential hybrid micromachining. It was observed that laser milling input parameters (scanning speed, power, frequency, and loops) affecting significantly on the output responses of µEDM milling time, tool wear and machining instability (short circuit/arc count).