Research of Design and Simulation for the Small Modular Machine Tool

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Machine tool is the basic equipment of machinery industry, playing very important role in today's manufacturing, and its variety, quality and processing efficiency directly affects economic benefits and the technology level of the mechanical industry production. The modular machine tool is widely used in the industry, and its production efficiency is increased by several times or even several times than the common machine tool, with such processing methods of multi-axis, multi-knife and multi-process. This paper designs the small combined machine with a set of turning, milling, drilling and grinding by PTC's 3D software, namely Pro/Engineer. At last, the technique of the interference analysis and visual simulation has been carried on, verifying the feasibility of the machine design. The machine tool is mainly used to meet the needs of processing the small parts in scientific research, teaching unit or small repair industry, not only improving the machining efficiency, but also saving space and processing costs.

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3-9

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October 2014

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© 2014 Trans Tech Publications Ltd. All Rights Reserved

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[1] Petter Olofsgard, AmosNG, Philip Moore. Distributed virtual manufacturing for development of modular machine systems (J). Journal of Advanced Manufacturing Systems, 2002, 1(2): 141-158.

Google Scholar

[2] Won SooYun, Jeong HoonKo, Dong WooCho. Development of a virtual machine tool (J). International Journal of the Korean Society of Precision Engineering, 2003, 4 (2): 71-76.

Google Scholar

[3] Liu Tien-I, WaqqasH. A knowledge-based system of high speed machining for the manufacturing of products (J). International Journal of Knowledge-based and Intelligent Engineering Systems, 2010(4): 185-199.

DOI: 10.3233/kes-2010-0200

Google Scholar

[4] J. vander Geer, J.A.J. Hanraads, R.A. Lupton, The art of writing a scientific article (J). Sci. Commun. 163(2000): 51-59.

Google Scholar

[5] Li Yueqin, Guo Zhiqiang. The computer design system of auxiliary combination machine (J) based on Pro /E. Machine tool & hydraulics, 2008, 36 (7): 147-149.

Google Scholar

[6] Ren Xiaozhong, Li Chunmei. The modularization design of aggregate machine tool based on UG (J). Based on the tractor and agricultural transport vehicles, 2007, 34 (2): 28-29.

Google Scholar

[7] Zhang Man bin, Cao Xinguo. the design and implementation of combination machine project CAD system(J). Journal of Hebei University of Technology, 1999, 28 (4): 44-47.

Google Scholar

[8] Meng Xianghui, Jiang Zuhua, Huang Gang. On the module identification for Product family development (J). The International Journal of Advanced Manufacturing Technology, 2007, 35(1-2): 26-40.

Google Scholar

[9] S.K. Ong, L. Jiang, A.Y.C. Nee. An Internet-Based Virtual CNC Milling System (J). International Journal of Advanced Manufacturing Technology, 2002, 20(1): 20-30.

DOI: 10.1007/s001700200119

Google Scholar

[10] IsikFiliz. An Entropy-based Approach for Measuring Complexity in Supply Chains (J). International Journal of Production Research, 2009, 48(12): 3681-3696.

DOI: 10.1080/00207540902810593

Google Scholar

[11] Sivadasans, Efstathiouj, Calineseua. Advances on Measuring the Operational Complexity of Supplier-customer Systems (J). European Journal of Operational Research, 2006, 171(1): 208-226.

DOI: 10.1016/j.ejor.2004.08.032

Google Scholar

[12] Hao Yongtao. Research on Auto-reasoning Process Planning Using a Knowledge Based Semantic Net (J). Knowledge-Based System, 2006, 19(8): 755-764.

DOI: 10.1016/j.knosys.2006.06.001

Google Scholar

[13] GelenbeE, LiuPX, LaineJ. Genetic algorithms for autonomic route discovery. Proceedings of the IEEE Workshop on Distributed Intelligent Systems: Collective Intelligence and Its Applications (06), Jun1-16, 2006. Los Alamitos, CA, USA: IEEE Computer Society, 2006: 371-376.

DOI: 10.1109/dis.2006.32

Google Scholar

[14] Bonnie RM, Victoria Y. Agent learning in the multi-agent contracting system (J). Decision Support Systems, 2008, 45 (1): 140-149.

DOI: 10.1016/j.dss.2007.12.013

Google Scholar