記述言語：英語   掲載種別：研究論文（学術雑誌）   出版者・発行元：Fuji Technology Press Ltd.  

Recently, there has been an increased demand for precise monitoring of the milling process using machine tools through a simple and cost-effective method. Accurate estimation of cutting forces is highly effective for this monitoring, and one approach is the modeling of tool spindles and tables of a machine tool. To model machine structures, well-known methods involving the use of impulse hammer response or structural analysis exist. However, the complex modeling is hard to achieve when using the impulse response. Moreover, it is often considerably difficult to achieve the modeling with structural analysis because the preparation of the accurate model and highly complicated calculations are required. Therefore, in this study, we propose a new monitoring method to identify model parameters of the machine structure and estimate cutting forces. First, a simplified assumed structure is prepared based on locations where sensors can be mounted. Next, measurement data during actual milling process are collected through the acceleration sensors mounted on the tool spindle and the dynamometer for the cutting force attached to the table. Subsequently, model parameters are identified from these data using machine learning. A 3-axis NC milling machine was used to evaluate the application range of the model parameters by changing cutting conditions, milling direction, cutting tools, and materials. The model parameters identified using the proposed method were equivalent to those using the impulse response. Furthermore, even in cases where the impulse response was difficult to identify, suitable model parameters were identified using machine learning. Finally, we confirmed that the proposed method can accurately achieve in-process monitoring of cutting forces in the X, Y, and Z directions.

DOI： 10.20965/ijat.2024.p0026

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担当区分：筆頭著者,　責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）   出版者・発行元：Fuji Technology Press Ltd.  

Vertically articulated industrial robots are suitable for machining purposes owing to their advantages over multi-axis machine tools, such as larger workspace, easier installation, and lower cost. However, the rigidity and positioning accuracy of industrial robots are inferior to those of machine tools, which renders it difficult to maintain the robot posture required for machining operations. This study focuses on improving the accuracy of robot machining based on posture optimization by exploiting the kinematic redundancy of a six-axis vertically articulated robot. To decrease positioning errors caused by static and dynamic external forces during machining, this study proposes a path generation method for a redundant joint that simultaneously considers the static and dynamic rigidity of the machining robot. The relationships between the static and dynamic mechanical characteristics of the machining robot and the redundant angle are illustrated using two maps: a static stiffness map and a natural frequency map. Using these two maps in the proposed path generation method, the redundant angle that can be selected for the robot posture with arbitrary mechanical characteristics is selected. Experimental results confirm that the proposed path generation method can control the priority of reducing static positioning error and vibration amplitude by changing the weight coefficients. In addition, the proposed method can improve positioning accuracy compared with conventional trajectory generation methods for redundant robots.

DOI： 10.20965/ijat.2023.p0494

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担当区分：筆頭著者   掲載種別：研究論文（学術雑誌）   出版者・発行元：Elsevier BV  

DOI： 10.1016/j.cirp.2023.04.070

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掲載種別：研究論文（学術雑誌）   出版者・発行元：Elsevier BV  

DOI： 10.1016/j.ijmachtools.2022.103862

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掲載種別：研究論文（学術雑誌）   出版者・発行元：Fuji Technology Press Ltd.  

The demands for machining by industrial robots have been increasing owing to their low installation cost and high flexibility. A novel trajectory generation algorithm for high-speed and high-accuracy machining by industrial robots is proposed in this paper. Linear interpolation in the workspace and smooth trajectory generation at the corners are important in industrial machining robots. Because industrial robots are composed of rotational joints, the joint space has a nonlinear relationship with the workspace. Therefore, linear interpolation in the joint space, which has been widely used in conventional machine tools, does not guarantee linear interpolation in the actual machining workspace. This results in the degradation of the machining surface. The proposed trajectory generation algorithm based on the decoupled approach can achieve linear interpolation in the workspace by separating the position commands into Cartesian coordinates and the orientation commands into spherical coordinates. In addition, a novel corner smoothing method that generates a smooth and continuous trajectory from discrete commands is proposed in this paper. The proposed kinematic local corner smoothing generates a smooth trajectory by using a 3-segmented constant jerk profile at the corners in the joint space. The sharp corners can thereby be replaced by smooth curves. The resulting cornering error is controlled by varying the cornering duration. The simulation results demonstrate the effectiveness of the proposed kinematic smoothing algorithm in achieving linear tool motion in straight sections and in generating smooth trajectories at corner sections within the user-defined tolerance.

DOI： 10.20965/ijat.2021.p0621

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記述言語：日本語  

開催地：福岡   国・地域：日本国  

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記述言語：日本語  

開催地：福岡   国・地域：日本国  

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記述言語：日本語  

開催地：ニュージャージー   国・地域：アメリカ合衆国  

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記述言語：日本語  

開催地：ニュージャージー   国・地域：アメリカ合衆国  

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記述言語：日本語  

開催地：奈良   国・地域：日本国  

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受賞区分：出版社・新聞社・財団等の賞  受賞国・地域：日本国

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受賞国・地域：アメリカ合衆国

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種別：その他

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種別：講演会

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種別：セミナー・ワークショップ

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