Multi-objective optimization of cortical bone machining using numerical and statistical approaches

Cutting of bone is a common practice in the surgery to treat the fracture in bones. There is a need to conduct a detailed study to analyse the influence of traditional cutting parameters on the overall cutting performance of bone. The intricate and resource-intensive nature of bone machining has led researchers to seek more efficient tools to aid in the optimization process. Finite Element Method (FEM) simulations have emerged as a viable solution for such challenges. By combining FEM simulations with grey relational analysis (GRA), researchers can reduce the associated costs and improve the overall optimization process. The current study utilized the hybrid concept where finite element assisted orthogonal cutting simulations were performed on the cortical bone. Design of experiment was conducted using Taguchi orthogonal L09 experiments. The four controlling parameters were rake angle, edge radius, cutting speed and undeformed chip thickness. Output responses of forces, power, chip compression ratio and coefficient of friction were minimized, whereas shear angle was maximized. Finite element simulations provided the essential parameters such as deformed chip thickness and cutting forces, that were used to calculate the chip compression ratio, shear angle and total power in each condition. In addition, grey relational analysis (GRA) was conducted to get the meaning results of this work. It is rarely found in the literature that orthogonal cutting of cortical bone was studied with the above-mentioned techniques in combination. The optimal parameters for the optimized performance were rake angle of 20°, edge radius of 5 µm, cutting speed of 25 mm/s and undeformed chip thickness of 0.1 mm. The usage of the said optimal parameters results in a Grey Relational Grade improvement of 0.2828 in comparison to the referenced first experimental run. The percentage contribution of rake angle, undeformed chip thickness, cutting speed and edge radius is 79.58%, 17.18%, 2.33% and 0.90% respectively. The current study is helpful for the audience working in the biomedical and custom-made cutting tools manufacturing sectors.