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Concrete strength control charts pattern recognition based on Linear Vector Quantization neural networks

Author

Listed:
  • Þebnem KOLTAN YILMAZ
  • M. Mustafa YÜCEL

    (Ýnönü Üniversitesi ÝÝBF Ýþletme Bölümü)

Abstract
The objective in this study is to detect the errors that occur or may occur in the future during the process in which the company’s quality objectives are fulfilled and to show the applicability of the Artificial Neural Networks (ANN) which is one of the Artificial Intelligence (AI) techniques. Thus, it will be able to contribute to the main purposes which make quality control necessary such as to raise the level of quality, reduce operating costs, time savings, raising employees’ motivation and reducing customer complaints. For this purpose, average compressive strength, one of the most important quality indicators, of a company that produces ready-mixed concrete has been used. Linear Vector Quantization (LVQ) type ANN model has been established by using the quality characteristics observation values related to control charts and the parameters related to control charts, and when these two models are compared, it has been found out that the model whose quality characteristics have been constructed using the observation values result in more successful results than that constructed with the model's control charts.

Suggested Citation

  • Þebnem KOLTAN YILMAZ & M. Mustafa YÜCEL, 2015. "Concrete strength control charts pattern recognition based on Linear Vector Quantization neural networks," Eurasian Eononometrics, Statistics and Emprical Economics Journal, Eurasian Academy Of Sciences, vol. 2(2), pages 1-15, October.
    • Handle: RePEc:eas:econst:v:2:y:2015:i:2:p:1-15
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    File URL: http://econstat.eurasianacademy.org/dergi/../dergi//dogrusal-vektor-kuantizasyon-modeli-kullanilarak-yapay-sinir-aglariyla-beton-basinc-dayanimi-kontrol-semalarinda-oruntu-tanima201510.pdf
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    More about this item

    Keywords

    Pattern Recognition in Control Charts (CCPR); Neural Networks; Linear Vector Quantization (LVQ); Concrete Strength; Concrete Quality.;
    All these keywords.

    JEL classification:

    • C02 - Mathematical and Quantitative Methods - - General - - - Mathematical Economics
    • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
    • L15 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Information and Product Quality

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