Modeling of Temperature in Orthopaedic Drilling Using Fuzzy Logic

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Bone drilling is a common procedure to produce hole for screw insertion to fixate the fracture devices and implants during orthopaedic surgery. A major problem which is encountered during such a procedure is the increase in temperature of the bone due to the plastic deformation of chips and the friction between the bone and drill. This increase in temperature can result in thermal osteonecrosis which may delay healing or reduce the stability and strength of the fixation. In the present work, prediction of temperature in drilling of polymethylmethacrylate (PMMA) (as a substitute for bone) is carried out using fuzzy logic. The effectiveness of the fuzzy model is compared with the experimental results. Good agreement is observed between the predictive model values and experimental values which indicates that that the developed model can be effectively used to determine the temperature in the bone drilling.

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1313-1318

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December 2012

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© 2013 Trans Tech Publications Ltd. All Rights Reserved

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[1] T. Udiljak, D. Ciglar, S. Skoric, Investigation into bone drilling and thermal bone necrosis, Advances in Production Engineering and Management 2 (2007) 103-112.

Google Scholar

[2] H.T. Hillery, I. Shuaib, Temperature effects in drilling of human and bovine bone, Journal of material processing technology 92-93 (1999) 302-308.

DOI: 10.1016/s0924-0136(99)00155-7

Google Scholar

[3] R.A. Eriksson, T. Albrektsson, B. Magnusson, Assesment of bone viability after heat trauma. A histological, histochemical and vital microscopic study in the rabbit , Scand J Plast Reconstr Surg 18 (1984) 261–268.

DOI: 10.3109/02844318409052849

Google Scholar

[4] A.R. Moritz, F.C. Henriques, Studies of Thermal Injury II. The Relative Importance of Time and Surface Temperature in the Causation of Cutaneous Burns, Americam Journal of Pathology 23 (1947) 695-720.

Google Scholar

[5] J. Lundskog, Heat and Bone Tissue, Scandinavian Journal of Plastic and Reconstructive Surgery supplementum 9 (1972).

Google Scholar

[6] R.A. Eriksson, T. Albrektsson, Temperature threshold levels for heat-induced bone tissue injury: a vital-microscopic study in the rabbit, Journal of Prosthetic Dentistry 50 (1983) 101-7.

DOI: 10.1016/0022-3913(83)90174-9

Google Scholar

[7] R.A. Eriksson, T. Albrektsson, The effect of heat on bone regeneration: An experimental study in the rabbit using bone growth chamber, Journal of Oral and Maxillofacial surgery 42 (1984) 705-711.

DOI: 10.1016/0278-2391(84)90417-8

Google Scholar

[8] R.A. Eriksson, T. Albrektsson, B. Albrektsson, Heat caused by drilling cortical bone. Temperature measured in vivo in patients and animals, Acta Orthopaedic scandinavica 55 (1984(a) 629-641.

DOI: 10.3109/17453678408992410

Google Scholar

[9] G. Augustin, S. Davila, K. Mihoci T. Udiljak, D.S. Vedrina, A. Antabak, Thermal Osteonecrosis and Bone Drilling Parameters Revisited, Arch Orthop Trauma Surg 128 (2008) 71-77.

DOI: 10.1007/s00402-007-0427-3

Google Scholar

[10] F.G. Pallan, Histological change in bone after insertion of skeletal fixation pins, Journal of oral surgery, Anesthesia and Hospital Dental Services 18 (1960) 400-408.

Google Scholar

[11] B. Latha, V.S. Senthilkumar, Analysis of thrust force in drilling glass fibre- reinforced plastic composites using fuzzy logic. Materials and Manufacturing processes 24: 4 (2009) 509-516.

DOI: 10.1080/10426910802714688

Google Scholar

[12] S.V. Wong, M.A. Hamouda A.M. S El Baradie, Development of a fuzzy based expert system for metal cutting data selection, Int J Flexi Automat Integr Manuf 5 (1997) 79–104.

Google Scholar

[13] V. Kalidindi, Optimization of drill design and coolant systems during dental implant surgery, MS thesis, University of Kentucky, (2004).

Google Scholar

[14] T. Ueda, A. Wada, K. Hasegawa, Y. Endo, Y. Takikawa, T. Hasegawa, T. Hara, Design optimization of surgical drills using the Taguchi method, Journal of biomechanical science and engineering (2010) Vol. 5, No. 5.

DOI: 10.1299/jbse.5.603

Google Scholar

[15] L. Zadeh, Fuzzy sets. Information and Control 8 (1965) 338–353.

Google Scholar

[16] B. Latha, V. S. Senthilkumar, Modeling and Analysis of Surface Roughness Parameters in Drilling GFRP Composites Using Fuzzy Logic. Materials and Manufacturing Processes 25: 8 (2010) 817-827.

DOI: 10.1080/10426910903447261

Google Scholar

[17] S. Ramesh, L. Karunamoorthy, K. Palanikumar, Fuzzy Modelling and Analysis of Machining Parameters in Machining Titanium alloy, Materials and Manufacturing Processes 23 (2008) 439-447.

DOI: 10.1080/10426910801976676

Google Scholar

[18] J.L. Lin, K.S. Wang, B.H. Yan, Y.S. Tarng, Optimization of the electrical discharge machining process based on the Taguchi method with fuzzy logic, Journal of Materials Processing Technology 102 (2000) 48–55.

DOI: 10.1016/s0924-0136(00)00438-6

Google Scholar

[19] D.C. Montgomery, Design and Analysis of Experiments, John Wiley and Sons, New York, (1991).

Google Scholar