MATHEMATICAL MODELLING OF TECHNOLOGICAL PROCESSES AND SYSTEMS
MODELING OF PRODUCTION PARAMETERS OF B4C + ZrO2 COMPOSITES VIA ARTIFICIAL NEURAL NETWORKS METHOD
- 1 Department of Mechanical Engineering, Marmara University, Turkey
- 2 Department of Metallurgy and Materials Engineering, Marmara University, Turkey
- 3 Department of Mechatronics, Selcuk University, Turkey
In this study, the effect of production parameters of B4C + ZrO2 composites on density was modelled by using Artificial Neural Network (ANN). The composites were produced by using powder injection molding method (PIM). In the sintering stage, pressureless sintering method under argon atmosphere was used. As the production parameters, amount of additional (A, wt.%) and sintering temperature (T, ◦C) were defined. The main aim of the study is to obtain the experimental conditions giving maximum density. As a results of this study, the production parameters of hard sintered materials like B4C + ZrO2 could be modelled by using ANN method to optimize and predict because the prediction error is blow percentage of 10%. Therefore, the research and development time and cost can be reduced by using this method.