Forecasting of Zinc Coating Thickness with Artificial Neural Network

Year 2013, Volume: 17 Issue: 1, 61 - 69, 01.04.2013

Tuğçen Hatipoğlu Semra Boran Burcu Özcan Alpaslan Fığlalı

Abstract

Since the competition level among the companies is increasing day by day, meeting customer demands with qualified products and cost reduction are primary goals of each company. And zinc, the main raw material in galvanization sector, is the most important cost item. So it is required to forecast the amount of zinc to be spent. In this study it is tried to forecast the amount of zinc consumption using the artificial neural network (ANN) method. To evaluate the convenience of values hypothesis tests are done; and the results showed that there is no significant difference between the predicted and real outputs statistically

Keywords

Forecasting, Metaheuristics, Artificial Neural Networks, Coating thickness

Yapay Sinir Ağı Yaklaşımıyla Çinko Kalınlığının Tahminlenmesi

Abstract

Since the competition level among the companies is increasing day by day, meeting customer demands with qualified products and cost reduction are primary goals of each company. And zinc, the main raw material in galvanization sector, is the most important cost item. So it is required to forecast the amount of zinc to be spent. In this study it is tried to forecast the amount of zinc consumption using the artificial neural network (ANN) method. To evaluate the convenience of values hypothesis tests are done; and the results showed that there is no significant difference between the predicted and real outputs statistically.

Keywords

Tahminleme, Metasezgisel, Yapay sinir ağları, Kaplama kalınlığı

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