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Inverse Prediction of Critical Parameters in Orthogonal Cutting using Binary Genetic Algorithm

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Intelligent Systems Technologies and Applications 2016 (ISTA 2016)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 530))

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Abstract

An inverse problem is solved for concurrently assessing the rake angle, the chip thickness ratio and the required cutting width in an orthogonal cutting tool, when subjected to a prescribed force constraint. The force components which can be obtained experimentally by mounting either suitable dynamometers or force transducers on a machine tool, are calculated here by solving a forward problem. Due to inherent complexities involved in the calculations of the gradients, genetic algorithm-based evolutionary optimization algorithm is used in the present study. The results of the inverse problem have been compared with those of the forward problem. It is observed that a good estimation of the unknowns is possible. The current study is projected to be of use to decide on the relevant cutting tool parameters and adjusting the cutting process in such a manner that the cutting tool works within the dynamic limits.

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Author information

Authors and Affiliations

  1. Department of Mechanical Engineering, IIT Ropar, Rupnagar, Punjab, 140001, India

    Ranjan Das

Authors
  1. Ranjan Das
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Corresponding author

Correspondence to Ranjan Das .

Editor information

Editors and Affiliations

  1. Dept. of CS, School of Science, University of Salamanca Dept. of CS, School of Science, Salamanca, Spain

    Juan Manuel Corchado Rodriguez

  2. Machine Intelligence Unit, Indian Statistical Institute Machine Intelligence Unit, Kolkata, India

    Sushmita Mitra

  3. and Management – Kerala (IIITM-K), Indian Inst. of Information Technology and Management – Kerala (IIITM-K), Trivandrum, Kerala, India

    Sabu M. Thampi

  4. King Fahd Univ of Petroleum and Minerals , Dhahran, Saudi Arabia

    El-Sayed El-Alfy

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© 2016 Springer International Publishing AG

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Das, R. (2016). Inverse Prediction of Critical Parameters in Orthogonal Cutting using Binary Genetic Algorithm. In: Corchado Rodriguez, J., Mitra, S., Thampi, S., El-Alfy, ES. (eds) Intelligent Systems Technologies and Applications 2016. ISTA 2016. Advances in Intelligent Systems and Computing, vol 530. Springer, Cham. https://doi.org/10.1007/978-3-319-47952-1_43

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  • DOI: https://doi.org/10.1007/978-3-319-47952-1_43

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-47951-4

  • Online ISBN: 978-3-319-47952-1

  • eBook Packages: EngineeringEngineering (R0)

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