Bone drilling and implantation are important in orthopaedic surgery, dentistry and also fracture treatment. In many cases, due to the rise in temperature during bone drilling (higher than 47 C) and low conductivity of bone, thermal necrosis occurs. There is also risk of drill fracture due to the excessive thrust force. Despite many studies on the effect of different parameters on bone drilling temperature and force, there is still no clarity about the influence of the tool rotational speed and feed rate on the temperature and force responses. The aim of this study was to test and optimise the conditions in high-speed bone drilling, process force and temperature simultaneously. The results demonstrated that high-speed drilling is a suitable method for decreasing process temperature and force, and the rotational speed, feed rate and tool diameter were the most important factors in the high-speed bone drilling processes. Using a statistical method to model and optimise the process, a second-order model was developed to predict the behaviour of process temperature and thrust force in high-speed drilling. The optimised values were a rotational speed of 11778 rpm, feed rate of 50 mm/min and tool diameter of 2 mm, where the process force and temperature were 15.85 N and 33.4 C, respectively. Therefore, in high-speed bone drilling, the process thrust force and temperature decline, and the low effect of feed rate on temperature enables an increase in the speed of operation in robotic surgery.

Currently, in the world of orthopedic surgeries, bone drilling is prevalent to hold broken bones and for bone implantation. Increase of bone temperature higher than 47 °C leads to a notorious phenomenon named thermal necrosis, which eventuates in cellular death of the bone tissue. Consequently, there is a chance for a loose implant after the operation. In this paper, for the first time, a 3D thermo-mechanical finite element (FE) model of a high-speed bone drilling process was introduced to study process force and temperature. Then comparing experimental results with numerical ones, the influence of the rotational speed and feed rate on both process force and the temperature was investigated. This study revealed that in high-speed drilling of the bone with a raise in rotational speed, due to different chip deformation and reduced chip thickness, both process force and temperature reduce remarkably. According to experimental and numerical findings, the optimum bone drilling setting was achieved with a tool diameter of 2 mm, the rotational speed of 12,000 rpm, and feed rate of 50 mm/min in which force and temperature were 14.11 N and 32.45 °C, respectively. The findings of this study can be an excellent help for robotic surgeries in order to decrease drilling force and temperature and ultimately squeezing of the recovery period.

Selective laser melting (SLM) is a prevalent additive manufacturing (AM) technique for the fabrication of metallic components. A modified GTN (Gurson-Tvergaard-Needleman) model was developed, based on the understanding of the SLM process and SLM-manufactured parts, in order to characterize void growth and void shear mechanism to predict the ductile fracture behavior of SLM-fabricated Ti6Al4V alloys under uniaxial stress states. The effect of the number of hidden layers and neurons, as a basic parameter of an artificial neural network (ANN), on predicting parameter relation accuracy was investigated. In this study resulted due to the complex relation among GTN fracture parameters and fracture displacement, defining more hidden layers in ANN improves the accuracy of predicting the damage and fracture behavior of SLM-fabricated Ti6Al4V alloys under uniaxial stress states; however, forecasting maximum force is achieved accurately by fewer hidden layers in comparison with fracture displacement needing to higher layers to predict precisely. Furthermore, the system R 2 -value reaches higher accuracy more than 0.99 for both maximum force and fracture displacement based on selected hidden layers and neurons.

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