Intelligent modeling of cutting force in bone micromilling process by fuzzy logic

Bone micromilling is widely used in orthopedic, spine, skull, knee joint replacement, and orthopedic surgeries to cut bone and make holes in tissue. The application of tools with a smaller diameter in the bone micromilling compared to conventional milling causes a significant reduction in force and also the length of the treatment period. In this article, in the form of an experimental study, an intelligent model for predicting bone micromilling force has been obtained based on the fuzzy inference system. For this purpose, first, an experiment design method has been used to extract a group of practical experiments. Then, based on the obtained results and approximation capability of fuzzy systems, an accurate model for predicting the cutting force has been established founded on the input values of tool rotation speed, feed rate, tool diameter, cutting depth and cutting direction. By examining the obtained results, it can be seen that the fuzzy model has been able to accurately approximate the resulting force of the bone micromilling process based on the considered inputs; The mean absolute percentage error and coefficient of determination for the data of the test section were calculated as 11.22% and 0.93%, respectively. Using the data of this research, surgeons with full knowledge can set the best values of the input variables of the micromilling process without worrying about causing damage and cracks in the bone tissue with the maximum possible operating speed.