Optimization of Aluminum Sand Casting process parameters on RSM and ANN methods

Saravanan S

Article Details

Optimization of Aluminum Sand Casting process parameters on RSM and ANN methods

Authors:

Saravanan S

Publisher:

Kuwait University

Journal:

Journal of Engineering Research Vol.11 Issue 1B, pp.0-0

Document Type:

Article

Publication Date:

1/2023

Document Language:

English

Document ID (Org No.):

2001942569

pISSN:

2307-1885

Abstract:

 Sand casting is one of the best processes to produce a product to satisfy the customer requirements. The prime advantages of choosing the sand casting technique are perfect dimensional geometry, development of pattern is easy, production rate is high, and solidification time is low when compared to other casting techniques. The main purpose of sand casting is to produce a product with better quality in low cost. The properties of the green sand are based on the sand composition and the most important parameters in the preparation of moulding sand are green strength, moisture content and clay content. In this work, the silica oxide is blended in green sand with various compositions for cope box. The various compositions of sand parameters are experimentally investigated by using Response Surface Methodology (RSM). The results of sand parameters are compared with Artificial Neural Network (ANN) analysis. The blending of 9.2% SiO2 with green sand is very suitable for this casting process. The blending of 9.2% SiO2 with green sand is very suitable for this casting process. The effect of SiO2 blending with green sand, the initial raw material is reduced up to 25% of volume without casting defects.The hardness value increased up to 22% and the surface roughness decreased up to 12% by varying the percentage of SiO2 in green sand.

Article Details

Optimization of Aluminum Sand Casting process parameters on RSM and ANN methods

Authors: Saravanan S

Publisher: Kuwait University

Journal: Journal of Engineering Research Vol.11 Issue 1B, pp.0-0

Document Type: Article

Publication Date: 1/2023

Document Language: English

Document ID (Org No.): 2001942569

pISSN: 2307-1885

Issues

Authors:

Saravanan S

Publisher:

Kuwait University

Journal:

Journal of Engineering Research Vol.11 Issue 1B, pp.0-0

Document Type:

Article

Publication Date:

1/2023

Document Language:

English

Document ID (Org No.):

2001942569

pISSN:

2307-1885