• DocumentCode
    1117843
  • Title

    Artificial neural networks in manufacturing: concepts, applications, and perspectives

  • Author

    Huang, Samuel H. ; Zhang, Hong-Chao

  • Author_Institution
    Dept. of Ind. Eng., Texas Tech. Univ., Lubbock, TX, USA
  • Volume
    17
  • Issue
    2
  • fYear
    1994
  • fDate
    6/1/1994 12:00:00 AM
  • Firstpage
    212
  • Lastpage
    228
  • Abstract
    New approaches and techniques are continuously and rapidly introduced and adopted in today´s manufacturing environment. Recently, there has been an explosion of interest in applying artificial neural networks to manufacturing. Artificial neural networks have several advantages that are desired in manufacturing practice, including learning and adapting ability, parallel distributed computation, robustness, etc. There is an expectation that neural network techniques can lead to the realization of truly intelligent manufacturing systems. This paper introduces the basic concepts of neural networks and reviews the current application of neural networks in manufacturing. The problems with neural networks are also identified and some possible solutions are suggested. The aim of the authors is to provide useful guidelines and references for the research and implementation of artificial neural networks in the field of manufacturing
  • Keywords
    learning (artificial intelligence); manufacturing computer control; neural nets; production control; adapting; artificial neural networks; intelligent manufacturing; learning; manufacturing environment; parallel distributed computation; robustness; Artificial neural networks; Computer aided manufacturing; Computer networks; Concurrent computing; Distributed computing; Explosions; Guidelines; Intelligent manufacturing systems; Pulp manufacturing; Robustness;
  • fLanguage
    English
  • Journal_Title
    Components, Packaging, and Manufacturing Technology, Part A, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1070-9886
  • Type

    jour

  • DOI
    10.1109/95.296402
  • Filename
    296402