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Neural networks and their applications in component design data retrieval

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Abstract

Neural networks have gained increased importance in the past few years. One of the basic characteristics of neural networks is the property of associative memory. In this paper we study the possibility of using the ideas of neural networks and associative memory in the manufacturing domain, with specific reference to design data retrieval in group technology. A two-layer feed-forward perceptron with backpropagation is simulated on a Vax-8550 to train example parts. The complete scheme along with the simulation results are explained and future directions indicated.

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Authors and Affiliations

  1. Industrial and Management Systems Engineering Department, The Pennsylvania State University, 16802, University Park, PA

    Sagar V. Kamarthi & Soundarr T. Kumara

  2. Electrical Engineering Department, The Pennsylvania State University, 16802, University Park, PA

    Francis T. S. Yu (Professor)

  3. Industrial and Management Systems Engineering Department, The Pennsylvania State University, 16802, University Park, PA

    Inyong Ham (Professor)

Authors
  1. Sagar V. Kamarthi
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  2. Soundarr T. Kumara
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  3. Francis T. S. Yu
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  4. Inyong Ham
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Kamarthi, S.V., Kumara, S.T., Yu, F.T.S. et al. Neural networks and their applications in component design data retrieval. J Intell Manuf 1, 125–140 (1990). https://doi.org/10.1007/BF01472509

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