Title

Parametric Analyses on Compressive Strength of Furan No Bake Mould System Using ANN

Journal title

Archives of Foundry Engineering

Yearbook

2016

Issue

No 4

Authors

Acharya, S.G. ; Vadher, J.A.

Keywords

compressive strength ; ANN ; FNB mould ; Matlab version: R2015a version 8.3 ; Parameters

Divisions of PAS

Nauki Techniczne

Publisher

The Katowice Branch of the Polish Academy of Sciences

Date

2016

Type

Artykuły / Articles

Identifier

DOI: 10.1515/afe-2016-0074 ; eISSN 2299-2944

Source

Archives of Foundry Engineering; 2016; No 4

References

Patil (2014), Prediction of casting defects through Artificial Neural Network Of Engineering And Technology, International Journal Science, 2, 245. ; Gresovnik (2012), Application of artificial neural networks to improve steel production process Proceedings of the International Conference Artificial Intelligence and, Soft Computing, 249. ; Zych (2013), Bench Life of Moulding and core sands with chemical binders - A new Ultrasonic Investigation Method of Foundry Engineering, Archives, 13, 117. ; LaFay (2012), Application of No - Bake sodium silicate binder systems Foundry of Metalcasting, American Society International Journal, 19. ; Surekha (2013), Application of Response Surface Methodology for modeling the properties of Chromite - based resin bonded sand cores of, International Journal Mechanics, 7, 443. ; Acharya (2015), Experimental investigations on modern furan no bake system to obtain quality casting Researchgate International conference on Advances in Materials and Product, Science. ; Saikaew (2012), Optimization of molding sand composition for quality improvement of iron castings Clay, Applied Science. ; Hosadyna (2011), Influence of the hardener type on the sulphur diffusion from the moulding sand to the casting surface of Foundry Engineering, Archives, 11, 47. ; Qing (2013), No - bake S - containing Mold - DI metal interactions : Consequences and Potential application Foundry, American Society, 13. ; Basheera (2000), Artificial neural networks : fundamentals computing design and application of Microbiological, Journal Methods, 43, 3.