Volume 20, Issue 4 (April 2020)                   Modares Mechanical Engineering 2020, 20(4): 987-997 | Back to browse issues page

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1- Mechanical Engineering Department, Mechanical Engineering Faculty, Shahid Rajaee Teacher Training University, Tehran, Iran
2- Mechanical Engineering Department, Mechanical Engineering Faculty, Shahid Rajaee Teacher Training University, Tehran, Iran , m.sheikhi@sru.ac.ir
3- Mechanical Engineering Department, Mechanical Engineering Faculty, Arak University, Arak, Iran
Abstract:   (2349 Views)
Cortical bone milling is used in orthopedic surgeries such as knee replacement, otological, spinal cord, and hip replacement. The cutting forces created by the cutting tool during cortical bone milling in order to control the wear of the tool as well as applying allowable force to the bone to prevent fracture should be controlled. In this paper, the effective parameters in the bone milling including cutting speed, feed rate, cutting depth and tool diameter has been investigated using the response surface method in order to predict the cutting forces. In this method, a second-order linear regression equation can be presented in order to predict the behavior of the bone milling process precisely. Also, Sobel's sensitivity analysis method was used to study the effect of input parameters on the behavior of cutting force. In this research, the behavior of different input parameters and the effect of their interactions on the machining force has been evaluated and analyzed. The components of cutting force were measured and investigated in three directions of feed, perpendicular to the feed and perpendicular to the bone surface. The results show that the mathematical model governing the problem has a proper function within the range of the defined parameters and it can provide a good prediction of force behavior. The minimum cutting force can be achieved in a rotational speed of 1500 rpm, feed of 12 mm/min, tool diameter of 2 mm, and cutting depth of 0.2 mm. Also, about the sensitivity of the force behavior based on the input parameters variation in the range of experiments, the greatest effect was related to the cutting depth with 36.3% of the effect, and feed rate with 28.4% of the effect, the diameter of the tool with 27.5% of the effect and the rotational speed with 7.8% of the effect.
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Article Type: Original Research | Subject: Biomechanics
Received: 2019/05/12 | Accepted: 2019/08/4 | Published: 2019/04/18

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