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Genetic Algorithm Based Prediction of an Optimum Parametric Combination for Minimum Thrust Force in Bone Drilling

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Recent Advances in Information and Communication Technology

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 265))

Abstract

Drilling operation on bone for screw insertion to fix the broken bones or for the fixation of implants during orthopaedic surgery is highly sensitive. It demands for minimum drilling damage of bone for proper fixation and quick recovery postoperatively. The aim of the present study is to find out an optimum combination of bone drilling parameters (feed rate and spindle speed) for minimum thrust force during bone drilling using genetic algorithm (GA). Central composite design is employed to carry out the bone drilling experiments and based on the experimental results, a response surface model was developed. This model is used as a fitness function for genetic algorithm (GA). The investigation showed that the GA technique can efficaciously estimate the optimal setting of bone drilling parameters for minimum thrust force value. The suggested approach can be very useful for orthopaedic surgeons to perform minimally invasive drilling of bone.

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Author information

Authors and Affiliations

  1. Department of Mechanical Engineering, Indian Institute of Technology Patna, Patna, India

    Rupesh Kumar Pandey & Sudhansu Sekhar Panda

Authors
  1. Rupesh Kumar Pandey
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  2. Sudhansu Sekhar Panda
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Corresponding author

Correspondence to Rupesh Kumar Pandey .

Editor information

Editors and Affiliations

  1. Faculty of Information Technology, King Mongkut's University of Technology North Bangkok, Bangkok, Thailand

    Sirapat Boonkrong

  2. Lehrgebiet Kommunikationsnetze, University of Hagen, Hagen, Germany

    Herwig Unger

  3. Faculty of Information Technology, King Mongkut's University of Technology North Bangkok, Bangkok, Thailand

    Phayung Meesad

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Pandey, R.K., Panda, S.S. (2014). Genetic Algorithm Based Prediction of an Optimum Parametric Combination for Minimum Thrust Force in Bone Drilling. In: Boonkrong, S., Unger, H., Meesad, P. (eds) Recent Advances in Information and Communication Technology. Advances in Intelligent Systems and Computing, vol 265. Springer, Cham. https://doi.org/10.1007/978-3-319-06538-0_11

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  • DOI: https://doi.org/10.1007/978-3-319-06538-0_11

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-06537-3

  • Online ISBN: 978-3-319-06538-0

  • eBook Packages: EngineeringEngineering (R0)

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