MATHEMATICAL MODELLING OF TECHNOLOGICAL PROCESSES AND SYSTEMS
PRODUCTION OF BORON CARBIDE BASED SANDBLASTING NOZZLE BY USING LOW PRESSURE POWDER INJECTION MOLDING METHOD AND MODELING OF PRODUCTION PARAMETERS VIA ARTIFICIAL NEURAL NETWORK
In this study boron carbide based sandblasting nozzles were produced by Low Pressure Powder Injection Molding (LPPIM) method, and wear behaviors of the nozzles were examined. The addition powder, addition ratio and sintering temperature were used as input parameters while density, micro hardness and wear rate were used as output parameters in the experimental design. This study consists of 3 steps: 1) production of standard samples and characterization, 2) modeling of proses parameters using Artificial Neural Network (ANN) method, 3) selection of nozzle material and production of nozzle, and testing. As a results of this study, ANN method can be used for modeling of process parameters of powder injection molding since the average value of the prediction error is below 7%, and boron carbide based products can be produced by using LPPIM method.