Optimization of bone drilling using Taguchi methodology coupled with fuzzy based desirability function approach
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Bone drilling is frequently done during Orthopaedic surgery to produce hole for screw insertion to fix and immobilize the fractured bones. Minimally invasive drilling of bone has a great demand as it helps in better fixation and quick healing of the broken bones. In the present investigation, Taguchi methodology coupled with the fuzzy logic based on desirability function is used for the optimization of bone drilling process to minimize the drilling induced damage of bone. Experiments have been performed with different conditions of feed rate and spindle speed using full factorial design. The responses considered are temperature, force and surface roughness. The multiple responses are aggregated into a single multi-performance index using fuzzy based desirability function which is then optimized using the Taguchi method. The optimal setting and the influence of the bone drilling process parameters on the multi-performance index is determined using response table, response graph and analysis of variance. The confirmation experiment carried out to validate the results reveals that the present approach can effectively minimize the bone tissue damage during drilling.
KeywordsBone drilling Taguchi method Fuzzy logic Desirability function Analysis of variance (ANOVA)
- Adnan, M. R. H. M., Sarkheyli, A., Zain, A. M., & Haron, H. (2013). Fuzzy logic for modeling machining process: A review. Artificial Intelligence Review. doi: 10.1007/s10462-012-9381-8.
- Al-Refaie, A., Rawabdeh, I., Jalham, I., Bata, N., & Abu-Alhaj, R. (2013). Optimization of multiple responses in the Taguchi method using desirability function and fuzzy regression. In Proceedings of the international multiConference of engineers and computer scientists, vol. II, IMECS, March 13–15, 2013, Hong Kong.Google Scholar
- Bagawade, A. D., Ramdasi, P. G., Pawade, R. S., & Bramhankar, P. K. (2012). Machining optimization models for hard turning: A review. International Journal of Mechanical Engineering and Research, 1(1), 55–60.Google Scholar
- Cardoso, P., & Davim, J. P. (2012). A brief review on micromachining of materials. Review of Advanced Materials Science, 30, 98–102.Google Scholar
- Derringer, G., & Suich, R. (1980). Simultaneous optimization of several response variables. Journal of Quality Technology, 12(4), 214–219.Google Scholar
- Köklü, U. (2013). Optimisation of machining parameters in interrupted cylindrical grinding using the Grey-based Taguchi method. International Journal of Computer Integrated Manufacturing. doi: 10.1080/0951192X.2012.749537.
- Pandey, R. K., & Panda, S. S. (2013). Drilling of bone: A comprehensive review. Journal of Clinical Orthopaedics and Trauma. doi: 10.1016/j.jcot.2013.01.002.
- Pandey, R. K., & Panda, S. S. (2013a). Modeling of temperature in orthopaedic drilling using fuzzy logic. Applied Mechanics and Materials, 249–250, 1313.Google Scholar
- Roy, R. (2001). Design of experiments using the Taguchi approach: 16 steps to product and process improvement. New York: Wiley. ISBN 0471361011.Google Scholar
- Yager, R. R., & Filev, D. P. (1999). Essential of fuzzy modeling and control. New York: Willey.Google Scholar