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IJAT Vol.12 No.6 pp. 947-954
doi: 10.20965/ijat.2018.p0947
(2018)

Paper:

Customized End Milling Operation of Dental Artificial Crown Without CAM Operation

Isamu Nishida, Ryo Tsuyama, Ryuta Sato, and Keiichi Shirase

Kobe University
1-1 Rokko-dai, Nada-ku, Kobe, Hyogo 657-8501, Japan

Corresponding author

Received:
May 7, 2018
Accepted:
July 4, 2018
Published:
November 5, 2018
Keywords:
intelligent machine tool, CAM-CNC integration, cutting force simulation, dental artificial crown
Abstract

A new methodology to generate instruction commands for real-time machine control instead of preparing NC programs is developed under the CAM-CNC integration concept. A machine tool based on this methodology can eliminate NC program preparation, achieve cutting process control, reduce production lead time, and realize an autonomous distributed factory. The special feature of this methodology is the generation of instruction commands in real time for the prompt machine control instead of NC programs. Digital Copy Milling (DCM), which digitalizes copy milling, is realized by referring only to the CAD model of the product. Another special feature of this methodology is the control of the tool motion according to the information predicted by a cutting force simulator. This feature achieves both the improvement in the machining efficiency and the avoidance of machining trouble. In this study, the customized end milling operation of a dental artificial crown is realized as an application using the new methodology mentioned above. In this application, the CAM operation can be eliminated for the NC program generation, and tool breakage can be avoided based on the tool feed speed control from the predicted cutting force. The result shows that the new methodology has good potential to achieve customized manufacturing, and can realize both high productivity and reliable machining operation.

Cite this article as:
I. Nishida, R. Tsuyama, R. Sato, and K. Shirase, “Customized End Milling Operation of Dental Artificial Crown Without CAM Operation,” Int. J. Automation Technol., Vol.12, No.6, pp. 947-954, 2018.
Data files:
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Last updated on Dec. 13, 2018