• DocumentCode
    3021442
  • Title

    An Algorithm of Tool-Path Optimization for High-Speed Machining Deep-Cavity Precision Forging Die

  • Author

    Sun, P.Q. ; Chen, L.Q. ; Wang, F.Q. ; Liao, H.W.

  • Author_Institution
    Digital Manuf. Technol. Lab., Huaiyin Inst. of Technol., Huai´´an, China
  • Volume
    4
  • fYear
    2009
  • fDate
    7-8 Nov. 2009
  • Firstpage
    397
  • Lastpage
    401
  • Abstract
    Aiming at the difficulty of maintaining the contour precision of forging die with deep pocket, an optimization algorithm of tool-path generation for high speed machining (abbr. HSM) forging die with deep cavity is proposed in this paper. In terms of measuring errors of pocketing die, a mathematical model correlation to the length of a tool-path, the available length of a cutting tool and the profile errors are characterized. After the calculation of the profile errors that vary with the length of the tool-path, the helix shaped tool-path can be created. Moreover, the optimized tool-path based on the algorithm for machining die with deep cavity is also generated by using the smooth curve as transition tool-path. Depending on the Mikron Duro800 HSM Machine Tool, a precision cavity of forging die for shaping internal-star-wheel parts can be machined. The experimental results indicate that the profile precision based on the optimum algorithm has been improved by IT 1~2.
  • Keywords
    cutting tools; forging; machining; mathematical analysis; measurement errors; optimisation; Mikron Duro800 HSM machine tool; cutting tool; deep cavity precision forging die; high speed machining; internal star wheel parts; mathematical model; measurement errors; profile errors; tool-path optimization; Artificial intelligence; Computational intelligence; Cutting tools; Machine tools; Machining; Manufacturing; Mathematical model; Shape; Space technology; Steel; Algorithm; High speed machining; Optimization; Tool path;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Artificial Intelligence and Computational Intelligence, 2009. AICI '09. International Conference on
  • Conference_Location
    Shanghai
  • Print_ISBN
    978-1-4244-3835-8
  • Electronic_ISBN
    978-0-7695-3816-7
  • Type

    conf

  • DOI
    10.1109/AICI.2009.338
  • Filename
    5376306