Integration of fuzzy logic with response surface methodology for thrust force and surface roughness modeling of drilling on titanium alloy

In recent years, a lot of extensive research work has been carried out in drilling operations for achieving better hole quality. Drilling operation is one of the machining processes, and it widely used in aeronautical and automotive industries for assembling the parts. The surface roughness is one of the significant factors in drilling operation because the poor surface finish will affect the material condition during the assembly. The spindle speed and feed rate are the important factors to affect the surface finish. In addition, the detailed analysis of the thrust force is also to be investigated for characterizing the cutting process. However, for examining the machining characteristics more trial runs are required, and it increases the time and cost of the experiment. In this paper, the integration of fuzzy logic (FL) with response surface methodology (RSM) has been introduced to reduce the cost and the time consumption for investigation. The low, middle, and upper levels of spindle speed with low and upper levels of feed rate combinations were examined on cutting force and surface finish through the experimental setup with the systematic manner. The FL model for thrust force and surface finish were obtained from the collected experimental data. The FL model has developed another two combinations of data without experimentation through universal partitioning. The results show that the predicted FL values are within the range of experimental value. Therefore, the FL model values were selected for further investigation with RSM. The result of FL-RSM model values are also within the range of experimental value. The proposed FL-RSM model and FL model are validated with experimental results. Finally, the validated results show that hybrid FL-RSM produces the effective output than the FL model.