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Genetic Algorithm-Based Optimization For Surface Roughness In Cylindrically Grinding Process Using Helically Grooved Wheels

Author

Listed:
  • ULAŞ ÇAYDAŞ

    (Technology Faculty, Department of Mechanical Engineering, University of Firat, 23119 Elazığ, Turkey)

  • MAHMUT ÇELİK

    (Technology Faculty, Department of Mechanical Engineering, University of Firat, 23119 Elazığ, Turkey)

Abstract

The present work is focused on the optimization of process parameters in cylindrical surface grinding of AISI 1050 steel with grooved wheels. Response surface methodology (RSM) and genetic algorithm (GA) techniques were merged to optimize the input variable parameters of grinding. The revolution speed of workpiece, depth of cut and number of grooves on the wheel were changed to explore their experimental effects on the surface roughness of machined bars. The mathematical models were established between the input parameters and response by using RSM. Then, the developed RSM model was used as objective functions on GA to optimize the process parameters.

Suggested Citation

  • Ulaş Çaydaş & Mahmut Çeli̇k, 2017. "Genetic Algorithm-Based Optimization For Surface Roughness In Cylindrically Grinding Process Using Helically Grooved Wheels," Surface Review and Letters (SRL), World Scientific Publishing Co. Pte. Ltd., vol. 24(Supp02), pages 1-8, November.
    • Handle: RePEc:wsi:srlxxx:v:24:y:2017:i:supp02:n:s0218625x18500312
    DOI: 10.1142/S0218625X18500312
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