IMS 7th International Symposium on Intelligent Manufacturing Systems, Saraybosna, Bosnia And Herzegovina, 1 - 04 November 2010, pp.433-441
The ANN Models are being used in a variety of sectors from industry to economy and from military to health. Simulating the main features of human brain such as learning, classification or generalization; ANN has been widely used among the other artifical intelligence techniques. Since the competition level among the companies is increasing day by day, galvanizing time and cost reduction have also become the primary goals of each company that performs in this sector. When the time increases in Zinc pool in galvanization, cost item also drastically increases. In this study it is tried to forecast galvanizing time and increase efficiency in this way. The material and process parameters which effects the time of galvanize are determined with the help of specialists using brain storming method. The purpose of this study is to find the optimum value for both the “time” and “cost” sides. A model for forecasting galvanizing time is developed and the results are evaluated with regarding to the desired and real values. When we compared the ANN (desired) values with the real data, we observe a good perform. For testing the convenience of these values; hypothesis tests are done and the results showed that there is no significant difference between the desired and real outputs statictically.