Mechanical Engineering Journal
Online ISSN : 2187-9745
ISSN-L : 2187-9745
Volume 3 , Issue 6
Showing 51-52 articles out of 52 articles from the selected issue
Design, Manufacturing, Information and Systems
  • Xiaoqi SONG, Weiming HE, Tohru IHARA
    2016 Volume 3 Issue 6 Pages 15-00534
    Published: 2016
    Released: December 15, 2016
    [Advance publication] Released: November 09, 2016
    JOURNALS FREE ACCESS

    Built-up edge (BUE) formation in machining maintains a profound effect on the cutting operation, such as cutting forces, cutting temperatures, tool wear, tool life, cutting vibration, surface roughness and the geometric dimensions of machined products and so on. Recently, attempts have been made to use BUE as the tool cutting edge/wedge to optimize machining, extend the tool life, etc. In order to have a clearly understanding of BUE formation, cutting experiments were performed on aluminum alloy A6063-T5 and low carbon steel STKM11A using the cemented carbide tool over a wide range of cutting speeds. The cutting speed of BUE formation spans just a small range of the cutting speed under low cutting speed and disappears with increasing the cutting speed, which is found to be ascribed to the decrease of cutting force and thermal effects that caused by increasing cutting speed. Further microscopic observations reveal that the temperature, plastic shear and shear rate in secondary shear zone are significantly related to BUE formation, which increases with increasing the cutting speed. Since the chip thickness ratio is an important parameter to characterize the chip plastic deformation, the relationship between the chip thickness ratio and BUE formation is considered. In this work, a new theoretical damage model is developed to predict the evolution of BUE formation, in which the reduction of material properties due to the thermal effects had been considered. And the model validation is performed by comparing the experimental results with the simulations for aluminum alloy A6063-T6 and low carbon steel STKM-11A, which clearly shows that the proposed analytical BUE formation model is able to predict the periodic evolution of BUE formation. Not only the cycle time can be predicted, but also it makes a more clearly understanding of the evolution of BUE formation mechanism and its effects.

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  • Naoaki TSUDA, Hiroumi FUNATSU, Noboru ISE, Yoshihiko NOMURA, Norihiko ...
    2016 Volume 3 Issue 6 Pages 15-00472
    Published: 2016
    Released: December 15, 2016
    [Advance publication] Released: December 05, 2016
    JOURNALS FREE ACCESS

    Currently, we cannot afford to spend much time for instructing usages of crutches for crutch users. However, we should carefully observe the methods of the patients' using crutches whether the methods are appropriate or not because inappropriate methods can raise a secondary accident such as falling. Therefore, it is desirable that patients are instructed readily on the proper method of using crutches when they start to use crutches. When considering the way of crutch walks, we took notice of the before/after body acceleration ratio, that is, the ratio between the accelerations before and after the gait mode-change as an important measure: from previous researches, it was found that there is a relationship between the body parts motions and the before/after body acceleration ratio of crutch users. Furthermore, it is desirable to get the before/after body acceleration ratio, without attaching any sensing devices onto the crutch user's body because the attached sensing devices may disturb a smooth walk. In order to meet the need, the authors proposed an estimation model of the before/after body acceleration ratio from the thigh motions without using any accelerometers. In this paper, as a measuring device, Kinect sensor was employed: although Kinect sensor is easy-to-use of, its measuring accuracy is not as precise as that of standard motion capturing systems. Firstly, the measuring accuracy of Kinect sensor was confirmed. Secondly, participants' crutch walk motions were practically measured by Kinect sensor. Then, the proposed estimation model was applied to the measured motions, and the effectiveness of the estimation model of the before/after body acceleration ratio was discussed. As a result, it was found that there was a high correlation between the estimated before/after body acceleration ratio and the measured one, and the before/after body acceleration ratio of a crutch user was successfully estimated by using the proposed method without an accelerometer nor a motion capturing system.

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