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Application of Neural Networks into Prediction of Qualitative Capability of the Preparation Process of Casting Moulds

Jaworski J., Kluz R., Trzepieciński T.

Archives of Foundry Engineering

2014

Vol. 14, iss. 1 spec.

9--12

In the article the problem of assurance of qualitative capability of the preparation process of casting moulds using artificial neural net-works is presented. Using STATISTICA Neural Networks a set of the best networks is found. Obtained results of neural modeling were compared with the results of experimental investigations and classical mathematical modeling. The appropriate architecture of the neural network is chosen that predicts the quality capability of the preparation process of casting moulds with the high precision.

Assurance of Quality Capability of the Preparation Process of Casting Moulds

Jaworski J., Kluz R., Trzepieciński T.

Archives of Foundry Engineering

2013

Vol. 13, iss. 1 spec.

61--64

The article investigates the problem of assurance of the required capability of robotized process of placing of steel inserts in a casting die. Dependence enabling the determination of the repeatability positioning of the robot, which has been verified in experimental tests is presented. A method to determine the most beneficial location in a workspace of the assembly stand ensuring the highest value of multivariate quality capability index MCp is also proposed. In the final part, the results are discussed and conclusions are formulated.