Quantitative Feeder Design for Metal Castings

P. Madhan Kumar; Elizabeth Jacob; S. Savithri; G.S. Suneeth

doi:10.4028/www.scientific.net/MSF.830-831.49

Paper Titles

The Effect of Magnesium on the Modifying Efficiency of Strontium in A356 Alloy
p.34

Processing and Characterization of Inconel 625 Nickel Base Superalloy
p.38

Experimental Study on the Effect of Mechanical Stirring in Semisolid Processing of Aluminum Alloys at Thixo-Temperatures
p.41

Computer Simulation of Low Pressure Casting Process Using Flow 3D^TM
p.45

Quantitative Feeder Design for Metal Castings
p.49

Computer Simulation of Centrifugal Casting Process Using FLOW-3D
p.53

Synthesis and Characterization of Nanostructured Tungsten-30 Atomic % Chromium Produced by Mechanical Attrition and Hydrogen Sintering
p.59

Effect of Equal Channel Angular Pressing on Densification Behavior of Al 5083 Alloy Powder
p.63

AlN-TiB₂ Based Self-Lubricating Ceramic Insert Fabricated by Spark Plasma Sintering for Dry Turning Applications
p.67

HomeMaterials Science ForumMaterials Science Forum Vols. 830-831Quantitative Feeder Design for Metal Castings

Quantitative Feeder Design for Metal Castings

Abstract:

Casting simulation packages are used to check a design for its castability. A better starting design should need fewer simulation cycles to arrive at a defect-free component thus cutting computation and manpower costs. Quantitative design of the feeding system is done by an analysis of the solidification pattern of the 3D model of the cast component. A clustering algorithm uses the solidification time/temperature data from the simulation to divide the casting into 3D feeding sections. The sections are created by following hotspots surrounded by areas of decreasing solidification time. Feeders are built by the feeder design module of AutoCAST casting design software. The initial simulation as well as the efficacy of the rigging is tested through the advanced simulation module FLOW+ of AutoCAST X. An industrial case study illustrates the software pipeline in a virtual foundry trial.

You might also be interested in these eBooks

Advanced Materials and Manufacturing Processes for Strategic Sectors

View Preview

Info:

Periodical:

Materials Science Forum (Volumes 830-831)

Pages:

49-52

DOI:

https://doi.org/10.4028/www.scientific.net/MSF.830-831.49

Citation:

Cite this paper

Online since:

September 2015

Authors:

P. Madhan Kumar, Elizabeth Jacob, S. Savithri, G.S. Suneeth

Keywords:

Feeder Design, Feeding Section, Solidification Simulation, Yield

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

References

[1] E. Jacob, Dundesh S. Chiniwar, Savitri S., Manoj M., R. Sasikumar, Simulation-based feeder design for metal castings, Indian Foundry Journal, 59(12) (2013), 39-44.

Google Scholar

[2] Elizabeth Jacob, M. Manoj, Roschen Sasikumar, Volume segmentation by post-processing data from simulation of solidification in the metal casting process, International Journal of Modeling, Simulation, and Scientific Computing, (2013).

DOI: 10.1142/s1793962313410055

Google Scholar

[3] Campbell J, Castings, Butterworth-Heinemann, Oxford, (2003).

Google Scholar

[4] E. Jacob, R. Sasikumar, B. Praveen and V. Gopalakrishna, Intelligent design of feeders for castings by augmenting CAD with Genetic Algorithms, Journal of Intelligent Manufacturing, (2004) 15( 3), pp.299-305.

DOI: 10.1023/b:jims.0000026568.93342.35

Google Scholar

[5] Advanced Reasoning Technologies, AutoCAST Software User Manual and Case Studies, http: /www. autocast. co. in.

Google Scholar

[6] Ravi B., Metal Casting, Computer-Aided Design and Analysis, Prentice-Hall India, (2005).

Google Scholar