5軸NC工作機械による主軸傾斜曲面加工法に関する研究 (第1報):—高能率金型加工のため最適割り出し角自動決定方法— Sculpture Surface Machining by Automatically Indexing Tilted Tool Axis on 5-axis Machine Tools (1st report):—Automatic Determination Method of Optimum Indexing Angle for High Efficiency Mold and Die Machining—

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Author(s)

Abstract

Today nearly all die and mold makers use High Speed Cutting or Machining in cavity and core manufacturing. However, finishing processes for injection molding molds and die casting dies are done by EDM because these applications have many thin and deep cavities to be machined. Otherwise, the long solid carbide milling cutters are necessary for machining these molds and dies. To save set-up time and machining time, it is desire to machine by High Speed Cutting or Machining in such machining portions. To solve this problem, mold and die machining by indexing tilted tool axis on 5-axis machining center is proposed in this paper. In the proposed machining process, High Speed Machining is executed on each tilted tool axis. In this machining process, the list of indexing angle should be determined automatically, because the shape of the die and mold is very complex to determine the angle by an operator. Therefore, the main objective of this research is automatic determination method of the list of indexing angle for machining the die and mold. Firstly, we propose the calculation method of optimum indexing angle for required machining surfaces using normal vectors of the surfaces and cutting edge shapes similar to the Gaussian Sphere method. Secondary, we propose the machinable area evaluation method of calculated indexing angle based on inverse offset method with state flag. Finally, we illustrate an example to demonstrate the effectiveness of the proposed methods.

Journal

  • Journal of the Japan Society for Precision Engineering, Contributed Papers

    Journal of the Japan Society for Precision Engineering, Contributed Papers 70(1), 65-69, 2004

    The Japan Society for Precision Engineering

Codes

  • NII Article ID (NAID)
    130002102988
  • Text Lang
    UNK
  • ISSN
    1348-8724
  • Data Source
    J-STAGE 
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