• DocumentCode
    3222362
  • Title

    A Study on Milling Burr Expert System in Micro-machining

  • Author

    Zhu Yunming ; Wang Guicheng ; Fan Shutian ; Wang Zhi ; Pei Hongjie

  • Author_Institution
    Sch. of Mech. Eng., Jiangsu Univ., Zhenjiang
  • Volume
    1
  • fYear
    2008
  • fDate
    20-22 Oct. 2008
  • Firstpage
    965
  • Lastpage
    969
  • Abstract
    Machining burrs are often created on the workpiece edges in micro-milling. Burrs make troubles on production lines in terms of deburring cost, quality of products and automation. To prevent problems caused by burrs in machining, prediction and control of burr size is desirable. Experimental studies show that burr formation in micro-milling is a highly complex process depending on a number of parameters such as material properties, tool geometry and cutting parameters. It is very difficult to establish the relationship between burr sizes and cutting conditions. A web-based micro-milling burr expert system for burr sizes prediction and control has been developed using ASP .NET platform. Burrs types and sizes prediction and cutting conditions optimization for burr controlling which based on the reasoning method of BP neural networks are realized. Operation results show the system is reliable. It provides a new technology for burrs modelling and controlling.
  • Keywords
    Internet; backpropagation; expert systems; micromachining; milling; neural nets; production engineering computing; ASP.NET platform; BP neural networks; Web-based micro-milling burr expert system; burr sizes prediction; machining burrs; material properties; micromachining; tool geometry; Automatic control; Automation; Costs; Deburring; Expert systems; Machining; Material properties; Milling; Production; Size control; artificial neural network; burr; expert system; micro-milling;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Computation Technology and Automation (ICICTA), 2008 International Conference on
  • Conference_Location
    Hunan
  • Print_ISBN
    978-0-7695-3357-5
  • Type

    conf

  • DOI
    10.1109/ICICTA.2008.119
  • Filename
    4659631