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Parametric Optimization of Permeability of Green Sand Mould Using ANN and ANFIS Methods

  • Prafulla Kumar Sahoo
  • Sarojrani Pattnaik
  • Mihir Kumar SutarEmail author
Conference paper
Part of the Lecture Notes in Mechanical Engineering book series (LNME)

Abstract

In foundry industries, various additives are used to increase the sand mould properties such as green strength and permeability number. In the present paper, camphor has been used as additive to enhance the mould’s permeability so as to improve the casting quality. The optimum quantity of camphor that can be added to the sand mixture was found to be 1 wt%. Further, prediction of green sand mould permeability number has been done using both artificial neural network (ANN) and adaptive neuro-fuzzy interference system (ANFIS). The models were built using experimental data as per Taguchi’s L27 orthogonal array (OA). The predicted permeability numbers by both models were found to be very close to that of experimental values; however, the predictability of ANFIS model was found to be better than ANN model as the error percent was less in former case.

Keywords

ANN ANFIS OA Permeability Camphor 

References

  1. 1.
    Orumwense, F.F.O.: Moulding properties of synthetic sand mixtures. A Comp. Study. Scand. J. Metall. 31, 100–106 (2002)CrossRefGoogle Scholar
  2. 2.
    Surekha, B., Kaushik, L.K., Pandey, A.K., Vundavilli, P.R.: Parappagoudar multi-objective optimization of green sand mould system using evolutionary algorithms. Int. J. Adv. Manuf. Techol. 58, 9–17 (2012)CrossRefGoogle Scholar
  3. 3.
    Baker, S.G.: Building the foundation for green sand. Mod. Cast. 95, 26–29 (2005)Google Scholar
  4. 4.
    Beeley, P.R.: Foundry man 73, xix–xvi (1980)Google Scholar
  5. 5.
    Ihom, A.P., Ogbodo, J.N., Allen, A.M., Nwonye, E.I., Iiochionwu, C.: Analysis and prediction of green permeability values in sand moulds using multiple linear regression model. Afr. J. Eng. Res. 2, 8–13 (2014)CrossRefGoogle Scholar
  6. 6.
    Brown, J.R.: Foseco Foundryman’s Handbook. 10th Edn. Pergamon Press Plc. pp. 10–68 (1994)Google Scholar
  7. 7.
    Heine, R.W., Loper Jr., C.R., Rosenthal, P.C.: Principles of Metal Casting, 2nd edn, pp. 100–150. Tata Mcgraw-Hill Publishing Company Ltd, New Delhi (1967)Google Scholar
  8. 8.
    Chavan, T.K., Nanjundaswamy, H.M.: Effect of variation of different additives on green sand mold properties for olivine sand. Int. J. Res. Eng. Adv. Technol. 1(4), 2320–8791 (2013)Google Scholar
  9. 9.
    Seidu, O.S., Kutelu, B.J.: Effects of additives on some selected properties of base sand. J. Minerals Mater Charact. Eng. 2, 507–512 (2014)Google Scholar
  10. 10.
    Shehu, T., Bhatti, R.S.: The use of yam flour (starch) as binder for sand mould production in nigeria. World Appl. Sci. J. 16(6), 858–862 (2012)Google Scholar
  11. 11.
    Ameen, H.A., Hassan, K.S.: Effect of the sand mould additives on some mechanical properties of carbon steel ck45 casts. J. Eng. 4(17), 729–739 (2017)Google Scholar
  12. 12.
    Solenicki, G., Budic, I., Ciglar, D.: Determination of thermal conductivity in foundry mould mixtures. Metalurgija 49(1), 3–7 (2010)Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  • Prafulla Kumar Sahoo
    • 1
  • Sarojrani Pattnaik
    • 1
  • Mihir Kumar Sutar
    • 1
    Email author
  1. 1.Mechanical Engineering DepartmentVeer Surendra Sai University of TechnologyBurlaIndia

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