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Multi-objective optimization of surface grinding process with the use of evolutionary algorithm with remembered Pareto set

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Abstract

In this paper the multi-objective optimization of a surface grinding process making use of an evolutionary algorithm is presented. Such factors as wheel speed, workpiece speed, depth of dressing and lead of dressing are optimized in order to minimize production cost and surface roughness or to minimize production cost and maximize production rate. In the algorithm, the optimization is introduced in Pareto’s sense, all acceptable and non-dominated solutions are remembered, and therefore the final result is not a single solution, but a whole set. The proposed method based on an example chosen from literature is tested, and the results obtained are compared with the results obtained by the use of other methods.

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Authors and Affiliations

  1. Department of Electronics and Computer Science, Technical University of Koszalin, Sniadeckich 2 Street, 75-453, Koszalin, Poland

    A. Slowik

  2. Department of Mechanical Engineering, Technical University of Koszalin, Raclawicka 15-17 Street, 75-620, Koszalin, Poland

    J. Slowik

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  1. A. Slowik
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  2. J. Slowik
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Correspondence to A. Slowik.

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Slowik, A., Slowik, J. Multi-objective optimization of surface grinding process with the use of evolutionary algorithm with remembered Pareto set. Int J Adv Manuf Technol 37, 657–669 (2008). https://doi.org/10.1007/s00170-007-1013-0

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  • DOI: https://doi.org/10.1007/s00170-007-1013-0

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