Papers by Keyword: In-Process Monitoring

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Authors: Manabu Enoki, Satoshi Nishinoiri
Abstract: An AE measurement system that uses a laser interferometer has been developed to evaluate microfractures at elevated temperatures in various materials. This technique has the advantage that it can estimate the temperature where microfractures were generated. The results give useful information to control process conditions. AE during sintering ceramics and thermal spying of ceramic powder on metal substrates were successfully detected by this laser AE measurement system. Effect of process conditions on damage process was discussed from the detected AE behaviour during in-process monitoring.
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Authors: Takashi Onishi, Kazuhito Ohashi, Kohei Higashi, Takahiro Iguchi, Shingo Yamashita, Hajime Isa, Shinya Tsukamoto
Abstract: In superfinishing, a fine surface can be obtained by transiting the machining states from the cutting action to the finishing one. In this study, we propose an advanced machine control system in superfinishing. The superfinishing stone is retracted automatically when the proposed system detects improvement in the surface roughness of the workpiece. The suitable machining time is determined by monitoring the machining force ratio measured with a force sensor. With machining experiments, we confirm that the finished surface roughness can be controlled by adjusting the threshold value of the machining force ratio to retract the superfinishing stone during machining.
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Authors: Takashi Onishi, Kazuhito Ohashi, Kohei Higashi, Yohei Morinaka, Shinichi Banno, Takakazu Kitagawa, Shinya Tsukamoto
Abstract: Superfinishing is widely used as a final finishing method for sliding surfaces of bearings. In superfinishing, a fine finished surface can be obtained by transiting the machining states from the cutting action to the finishing one as the tool loading is encouraged. To obtain good machining conditions, it is necessary to judge the transition of the machining state reliably. However, it is difficult to judge the transition of the machining states. In this study, we focused on the change of the dynamic component of the machining force, which was applied to the oscillation direction of the superfinishing stone, during machining process. With machining experiments, the relationship between the declination of the dynamic machining force and the transition of the machining state was confirmed.
592
Authors: Bo Di Cui, Jian Liang Guo
Abstract: Accurate predictive modeling is an essential prerequisite for optimization and control of production in modern manufacturing environments. For slender bar turning operations, dimensional deviation is one of the most important product quality characteristics due to the low stiffness of part. In this study, radial basis function neural network is employed to investigate dimensional errors in slender bar turning. The relationship between cutting parameters and dimensional errors is firstly described by the proposed model. Simulation is provided to investigate the effects of cutting parameters on dimensional errors. Further, real-time predictive model based on radial basis function neural network is developed to perform the dimensional error monitoring during slender bar turning process. Experiments verify that the proposed in-process predictive system has the ability to monitor efficiently dimensional errors within the range that they have been trained.
549
Authors: Hong Seok Park, Ngoc Hien Tran
Abstract: In recent years, due to the hard competitiveness through globalization most manufacturing companies have focused on manufacturing higher value added products with low production costs. So, it is inevitable to apply the advanced technology to carry out it in effective and efficient way. Monitoring and control of machining processes are becoming increasingly important for keeping a consistent quality of machined parts. The paper presents in-process sensing and control techniques with applying information science for the next generation of quality control that eliminates the need for expensive post-process inspection. In this research, a machining process of machine tool is considered in terms of a quality oriented control. The self-optimizing control is proposed for enabling intelligent process monitoring and control which can detect the cutting conditions and status of machining operations. To prove the proposed self-optimizing control system, self-monitoring and self-adjusting, the machining process related to the tool condition such as tool wear was considered in this paper. The most crucial and determining factor to successful maximization of the manufacturing processes in any typical metal cutting process is tool wear. The evolutionary algorithm was developed to diagnose the tool wear. If the amount of tool wear is out of the allowed limit, the new cutting parameters should be generated and adjusted autonomously according to affecting the quality of the machined part through the tool wear.
152
Authors: Ryo Koike, Yasuhiro Kakinuma, Tojiro Aoyama
Abstract: Detection of a tool fracture is necessary to ensure cutting accuracy and to avoid a tool breakage because tool fracture is one of the significant prediction signals of the tool breakage. For monitoring the tool condition, generally additional sensors are used. However using these sensors causes high cost and increase of failure rate. In this paper, a novel sensor-less detection method of tool fracture in drilling process is proposed on the basis of a disturbance observer theory. It is applied to the x-y stage of the machine tool. The proposed method requires no external sensor because it uses only the servo information of the spindle control system. Since structures of normal drills with two floats are symmetrical with respect to a point, theoretically the cutting force in the x and y directions does not work. When the drill is fractured, its structure becomes asymmetry so that unbalanced forces would exert in the x and y directions at intervals of the spindle speed. Therefore, it is possible to detect a tool fracture by the frequency analysis of estimated disturbance force with a wavelet transform. The experimental results show that the proposed method is available for detection of the small tool fracture effectively.
439
Authors: Naoto Hagino, Seiji Komiya, Jinichi Endou, Masao Ishihama
Abstract: The servo press has high potential for producing high precision mechanical parts. However, small gaps between dies and workpieces tend to exist even in servo press stamping, and the potential of the servo press has not yet been fully utilized. The reason for this is conventional presses do not have feedback control systems, and the lack of a suitable method of sensing contact information in real time causes deterioration in the accuracy of products. If slide motion could be controlled by contact information, the small gaps could be removed. To solve this problem, the authors have developed a method of monitoring the contact states between dies and workpieces during the stamping process. The method uses ultrasonic wave reflection and transmission at the contact surfaces and was proved to be able to monitor contact pressure by using a simple geometry experimental die apparatus. Finite-difference time-domain (FDTD) numerical simulation was conducted in this study to obtain better understanding of wave propagation through dies and workpieces. The results obtained from this FDTD simulation visualized wave propagation that could not be experimentally measured. Some of the major results obtained are as follows. 1) When a thin metal sheet is pressed between dies that have inclined stamping surfaces, ultrasonic elastic waves are reflected and transmitted multiple times. 2) Modal conversion occurs at the die-workpiece boundary in such a way that normal waves with an inclined incident angle are transformed into normal and shear waves. 3) Elastic waves sent out from an ultrasonic transducer are mixtures of normal waves with flat wave fronts along the propagation path axis, normal waves with circular or spherical wave fronts expanding from both sides of the transducer, and shear waves. These results brought about much useful information for setting ultrasonic transducers and analyzing collected signals.
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