Authors: G. Mahesh; K. Murugu Mohan Kumar; S. Bharathi Raja; Z.W. Zhong
Addresses: Saranathan College of Engineering, Tamil Nadu, India ' SASTRA University, Tamil Nadu, India ' Indra Ganesan College of Engineering, Tamil Nadu, India ' School of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore
Abstract: 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.
Keywords: aluminium; sand casting; design of experiment; DOE; artificial neural network; ANN; FUZZY; non-destructive test; NDT.
International Journal of Rapid Manufacturing, 2020 Vol.9 No.4, pp.281 - 293
Received: 12 Apr 2019
Accepted: 07 Jun 2019
Published online: 25 Sep 2020 *