Wyniki wyszukiwania - BazTech

Ograniczanie wyników

2 Archives of Foundry Engineering

Powiadomienia systemowe

Sesja wygasła!

Znaleziono wyników: 2

Liczba wyników na stronie

Wyniki wyszukiwania

Wyszukiwano:
w słowach kluczowych: automation of casting process

Sortuj według:

Ogranicz wyniki do:

Influence of the Home Scrap Content on the Service Life of Equipment Used in High Pressure Die Casting of AZ91 Alloy

Konopka Z., Łągiewka M., Zyska A.

Archives of Foundry Engineering

2018

Vol. 18, iss. 2

173--176

The results of estimation of home scrap addition in charge influence on durability and wear of casting instrumentation life in the high-pressure casting technology using the hot chamber machine of alloy of AZ91 are presented. The wear of the following elements of the casting instrumentation so-called "casting set" as: syphon, plunger, sliding-rings, nozzle and injection moulding nozzle was estimated. A wear was estimated quantitative by registering the number of mould injections for different charges to the moment of element damage supervision. A damage had to be at such level that liquidated an element from further exploitation and necessary was an exchange on new or regeneration. In a final result allowed it the detailed determination of durability of the applied rigging elements in dependence on the type of the applied type of melt. It is noticed, that together with the increase of home-scrap participation in the charge wear of pressure machine instrumentation elements increases.

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.