Comprehensive analysis on aluminium in sand casting by using intelligent techniques

Autor:	K. Murugu Mohan Kumar, S. Bharathi Raja, G Mahesh, Zhaowei Zhong
Rok vydání:	2020
Předmět:	Materials science business.industry Design of experiments chemistry.chemical_element Mechanical engineering General Medicine Casting law.invention chemistry Aluminium law Nondestructive testing Sand casting Surface roughness Foundry business Material properties
Zdroj:	International Journal of Rapid Manufacturing. 9:281
ISSN:	1757-8825 1757-8817
DOI:	10.1504/ijrapidm.2020.110774
Popis:	Today's foundry intentions are to succeed the cost-effective casting process. As a consequence of this goal, most of the researchers established numerical models for effective outputs. Numerical models of casting parameters have more considerable outputs for the foundry planner. Generally, the sand casting process comprises numerous parameters interdependently. If the parameters are not measured properly, the mould cavity is forced to reach the defects like porosity and blowholes. To overcome these defects, an extensive study on these factors is needed. During solidification, the important parameters like furnace, sand and vent holes affect the material properties. The molten temperature, pouring time and holding time are most significant parameters in sand casting. Aluminium is one of the highly desirable materials in sand casting. In this work, the various furnace parameters are analysed and compared using artificial neural network (ANN) and fuzzy logic models. The hardness and surface roughness are analysed and the work pieces are tested by using NDT techniques.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::aca86b63e78f4548e0a83e5a3cd49f8e https://doi.org/10.1504/ijrapidm.2020.110774 Zobrazit plný text záznamu