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A Production Control Support System Based on the Concept of an Artificial Pseudo Neural Network

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  • Marek Fertsch
  • Michał Fertsch

Abstract

Purpose: The goal of the paper is to present the concept of a pseudo-neural network developed for production control in an industrial enterprise that produces complex products under discrete production conditions. This paper contains an attempt to use the theoretical basis of artificial neural networks to build a specialized tool. This tool is called a pseudo-network. Design/Methodology/Approach: It is based not on the whole of the theory of artificial neural networks but only on the targeted elements selected for it. The selection criterion is the use of an artificial neural pseudo-network to control production Findings: The concept of artificial pseudo neural network is fully presented in previous works by the authors. Practical Implication: The network is part of the production planning and control system. In this system, the network acts as a subsystem responsible for production control. It cooperates with the production planning subsystem from which it periodically downloads the data on production task covering the assortment of manufactured products, production programs of individual assortment items, production start and end dates as well as its updates. In turn, it reports to the production planning subsystem about the progress of the implementation of the launched production task. Originality Value: The presented approach is original and can be developed to meet requirements of various production systems. It has both cognitive and utilitarian potential.

Suggested Citation

  • Marek Fertsch & Michał Fertsch, 2021. "A Production Control Support System Based on the Concept of an Artificial Pseudo Neural Network," European Research Studies Journal, European Research Studies Journal, vol. 0(Special 5), pages 562-571.
  • Handle: RePEc:ers:journl:v:xxiv:y:2021:i:special5:p:562-571
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    References listed on IDEAS

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    1. Lee, H. C. & Dagli, Cihan H., 1997. "A parallel genetic-neuro scheduler for job-shop scheduling problems," International Journal of Production Economics, Elsevier, vol. 51(1-2), pages 115-122, August.
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    More about this item

    Keywords

    Artificial Intelligence; artificial neural networks; artificial pseudo neural networks; production control.;
    All these keywords.

    JEL classification:

    • M2 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Economics
    • L11 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Production, Pricing, and Market Structure; Size Distribution of Firms

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