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Multi-objective optimization of green sand mould system using evolutionary algorithms

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Abstract

The quality of cast products in green sand moulds is largely influenced by the mould properties, such as green compression strength, permeability, hardness and others, which depend on the input (process) parameters (that is, grain fineness number, percentage of clay, percentage of water and number of strokes). This paper presents multi-objective optimization of green sand mould system using evolutionary algorithms, such as genetic algorithm (GA) and particle swarm optimization (PSO). In this study, non-linear regression equations developed between the control factors (process parameters) and responses like green compression strength, permeability, hardness and bulk density have been considered for optimization utilizing GA and PSO. As the green sand mould system contains four objectives, an attempt is being made to form a single objective, after considering all the four individual objectives, to obtain a compromise solution, which satisfies all the four objectives. The results of this study show a good agreement with the experimental results.

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Authors and Affiliations

  1. Department of Mechanical Engineering, DVR & Dr. HS MIC College of Technology, Kanchikacherla, Andhra Pradesh, 521180, India

    B. Surekha & Pandu R. Vundavilli

  2. Department of Mechanical Engineering, Rungta College of Engineering & Technology, Bhilai, Chattisgarh, 490024, India

    Lalith K. Kaushik & Abhishek K. Panduy

  3. Department of Mechanical Engineering, Chhatrapati Shivaji Institute of Technology, Durg, Chattisgarh, 491001, India

    Mahesh B. Parappagoudar

Authors
  1. B. Surekha
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  2. Lalith K. Kaushik
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  3. Abhishek K. Panduy
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  4. Pandu R. Vundavilli
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  5. Mahesh B. Parappagoudar
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Correspondence to Pandu R. Vundavilli.

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Surekha, B., Kaushik, L.K., Panduy, A.K. et al. Multi-objective optimization of green sand mould system using evolutionary algorithms. Int J Adv Manuf Technol 58, 9–17 (2012). https://doi.org/10.1007/s00170-011-3365-8

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  • DOI: https://doi.org/10.1007/s00170-011-3365-8

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