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Optimizing Sand Moulding Process through Regression Models and Destructive Testing

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Języki publikacji
EN
Abstrakty
EN
The main objective of the present study is enhanced of the sand moulding process through addressing the sand mould defects and failures, ultimately lead to improve production of the sand castings with well-defined of pattern profiles. The research aimed to reduce the cost and energy expenditure associated with the compaction time of the sand moulding process. Practical destructive tests were conducted to assess properties of the green sand moulds. Linear regression and multi-regression methods were employed to identify the key factors influencing the sand moulding process. The proposed experimental destructive tests and predicted regression methods facilitated measurement of the green sand properties and enabled evaluation of the effective moulding parameters, thereby enhancing the sand moulding process. Factorial design of experiments approach was employed to evaluate effect of parameters of water content and mixing time of the green sand compaction process on the mechanical properties of green sand mould namely the tensile strength, and compressive strength.
Rocznik
Strony
163--168
Opis fizyczny
Bibliogr. 20 poz., tab., wykr., wzory
Bibliografia
  • [16] Dhindaw, B.K., Chakraborty, M. (1974). Study and control of properties and behavior of different sand systems by application of statistical design of experiments In the 41st International Foundry Congress, (pp. 9-14). Belgique.
  • [1] Abdulamer, D. & Kadauw, A. (2019). Development of mathematical relationships for calculating material dependent flowability of green molding sand. Journal of Materials Engineering and Performance. 28(7), 3994-4001. DOI:https://doi.org/10.1007/s11665-019-04089-w.
  • [2] Shahria, S., Tariquzzaman, M., Rahman, H., Al Amin, M., & Rahman, A. (2017). Optimization of molding sand composition for casting Al alloy. International Journal of Mechanical Engineering and Applications. 5(3), 155-161. DOI:10.11648/j.ijmea.20170503.13.
  • [4] Kassie, A. & Assfaw, S. (2013). Minimization of casting defects. IOSR Journal of Engineering. 3(5), 31-38. DOI:10.9790/3021-03513138.
  • [3] Patil, G. & Inamdar, K. (2014). Optimization of casting process parameters using taguchi method. International Journal of Engineering Development and Research. 2(2), 2506-2511.
  • [5] Gadag, S. Sunni Rao, K. Srinivasan, M. et al. (1987). Effect of organic additives on the properties of green sand assessed from design of experiments. AFS Transactions. 42, 179-186.
  • [6] Karunaksr, D. & Datta, G. (2007). Controlling green sand mold properties using artificial neural networks and genetic algorithms- A comparison. Applied Caly Science. 37(1-2), 58-66. DOI:10.1016/j.clay.2006.11.005.
  • [7] Said, R. Kamal, M. Miswan, N. & Ng, S. (2018). Optimization of moulding composition for quality improvement of sand casting. Journal of Advanced Manufacturing Technology. 12(1(1), 301-310.
  • [8] Pulivarti, S. & Birru, A. (2018). Optimization of green sand mould system using Taguchi based grey relational analysis. China Foundry. 15, 152-159. DOI:10.1007/s41230-018-7188-1.
  • [9] Abdulamer, D. (2023). Impact of the different moulding parameters on engineering properties of the green sand mould. Archives of Foundry. 23(2), 5-9. DOI:10.24425/afe.2023.144288.
  • [10] Kumar, S. Satsangi, P. & Prajapati, D. (2011). Optimization of green sand casting process parameters of a foundry by using Taguchi’s method. International Journal of Advanced Manufacturing Technology. 55(1-4), 23-34. DOI:10.1007/s00170-010-3029-0.
  • [11] Murguía, P. Ángel, R. Villa González del Pino, E. Villa, Y. & Hernández del Sol, J. (2016). Quality improvement of a casting process using design of experiments. Prospectiva. 14(1), 47-53. DOI:10.15665/rp.v14i1.648.
  • [12] Abdullah, A. Sulaiman, S. Baharudin, B. Arifin, M. & Vijayaram, T. (2012). Testing for green compression strength and permeability properties on the tailing sand samples gathered from ex tin mines in perak state, Malaysia. Advanced Materials Research. 445, 859-864. DOI:10.4028/www.scientific.net/AMR.445.859.
  • [13] Abdulamer, D. (2021). Investigation of flowability of the green sand mould by remote control of portable flowability sensor. Archives of Materials Science and Engineering, 112(2), 70-76. DOI:10.5604/01.3001.0015.6289.
  • [14] Bast, J., Simon, W. & Abdullah, E. (2010). Investigation of cogs defects reason in green sand moulds. Archives of Metallurgy and Materials. 55(3), 749-755. DOI:10.24425/afe.2023.144288.
  • [15] Montgomery, D.C. (2001). Design and Analysis of Experiments. (5th ed.). John Wiley & Sons, Inc.
  • [17] Abdulamer, D. (2023). Utilizing of the statistical analysis for evaluation of the properties of green sand mould. Archives of Foundry Engineering. 23(3), 67-73, DOI:10.24425/afe.2023.146664, 2023.
  • [18] Parappagoudar, M. Pratihar, D. & Datta, G. (2007). Linear and non-linear statistical modelling of green sand mould system. International Journal of Cast Metals Research. 20(1), 1-13. DOI:10.1179/136404607X184952.
  • [19] Dietert, H. W. Brewster, F. S. & Graham, A. L. (1996). AFS Trans. 74, 101-111.
  • [20] Parappagoudar, M. Pratihar, D. & Datta G. (2005). Green sand mould system modelling through design of experiments. Indian Foundry Journal. 51(4), 40-51.
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2024)
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-dbce5cb9-3135-4f41-84ab-1b0a662e84a1
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