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Application of Artificial Intelligence to Predict Circularity and Cylindricity Tolerances of Holes Drilled on Marble

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Abstract

High quality marble processing is increasingly needed to ensure surface integrity and meet tight geometric and dimensional tolerances encountered in structural, sculpture and decorative industry. The paper aims at determining optimal drilling parameters for white marble in order to minimize the quality characteristic, namely, the circularity and the cylindricity of holes.

The cutting parameters have an influence on the quality of the machined holes. In order to predict the surface integrity of the parts, a calculation method based on Artificial Neural Networks (ANN) has been developed. An architecture comprising six inputs the rotation speed (N), the feed speed (F), the drill bit diameter (BD), the drill bit height (BH), the number of pecking cycles (P), and the drilling depth (BH) and two outputs (circularity and cylindricity) was used. The choice of cutting parameters has an influence on the convergence of the algorithm. The trained ANNs are monitored as regards the mean square error (MSE).

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Acknowledgements

The authors are grateful to MARBLE TUNIS-CARTHAGE Company for providing the Ishikawa dossier and their assistance throughout the experimental study.

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Correspondence to Amira Abbassi .

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Abbassi, A., Akrichi, S., Ben Yahia, N. (2019). Application of Artificial Intelligence to Predict Circularity and Cylindricity Tolerances of Holes Drilled on Marble. In: Benamara, A., Haddar, M., Tarek, B., Salah, M., Fakher, C. (eds) Advances in Mechanical Engineering and Mechanics. CoTuMe 2018. Lecture Notes in Mechanical Engineering. Springer, Cham. https://doi.org/10.1007/978-3-030-19781-0_16

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  • DOI: https://doi.org/10.1007/978-3-030-19781-0_16

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-19780-3

  • Online ISBN: 978-3-030-19781-0

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