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http://dx.doi.org/10.5762/KAIS.2018.19.11.338

Optimization of the Tool Life Prediction Using Genetic Algorithm  

Kong, Jung-Shik (Department of Mechanical Convergence Engineering, Induk University)
Publication Information
Journal of the Korea Academia-Industrial cooperation Society / v.19, no.11, 2018 , pp. 338-343 More about this Journal
Abstract
Recently, a computer numerical control (CNC) machine is used widely for mold making in various industries. In the operation of a CNC machine, the production quality and safety of workers are becoming increasingly important as the product process increases. A variety of tool life prediction studies has been conducted to standardize the quality of production and improve reproducibility. When the tool life is predicted using the conventional tool life equation, there is a large error between the experimental result and result by the conventional tool life equation. In this paper, an algorithm that can predict the precise tool life was implemented using a genetic algorithm.
Keywords
Tool life; Genetic algorithm; CNC machine; Taylor tool life equation; Prediction Optimization;
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1 B. S. Kim, T. H. Kang, S. H. Lee, J. H. Kang, J.Y. Song, "Development of a Tool Life Prediction Program for Increasing Reliability of Cutting Tools", Transactions of the Korean Society of Machine Tool Engineers, Vol.14, No.3, pp.1-7, 2005.
2 M. J. Maeng, J. K. Chung, "A Study on the Cutting Resistance and Acoustic Emission Signal due to Increasing Tool Wear in Turning", Journal of the Korean Society of Machine Tool Engineers, Vol.4, No.2, pp.18-24, 1995.
3 N. H. Cook, "Tool Wear and Tool Life", Journal of Engineering for Industry, Vol.95, No.4, pp.931-938, 1973. DOI: https://dx.doi.org/10.1115/1.3438271   DOI
4 J. J. Park, "Adaptive Observer and Computer Vision for On-Line Flank Wear Estimation", Ph. D. Dissertation, Univ. of Michigan, 1990.
5 S. H. Lee, B. S. Kim, T. H. Kang, J. Y. Song, J. H. Kang, C. S. Seo, "Development of Reliability Prediction Program for Tool Life", Proceedings of the KSMTE Spring Conference 2004, pp.317-322, 2004.
6 P. Lim, S. Y. Park, G. E. Yang, "A Study on tool life in the high speed machining of small-size end mill by factorial design of experiments and regression model", Journal of the Korean Society for Precision Engineering, Vol.23, No.2, pp.73-80, 2006.
7 S. Y. Lee, Y. M. Im, "Prediction and Experiments of Cutting Forces in End Milling", Journal of the Korean Society of Manufacturing Technology Engineers, Vol.13, No.4, pp.9-15, 2004.
8 G. D. Kim, J. N. Ju, "Prediction of the Amount of Tool Fracture in Face Milling using Cutting Force Signal", Trans. Korean Soc. Mech. Eng. A, Vol.25, No.6, pp.972-979, 2001. DOI: https://dx.doi.org/10.22634/KSME-A.2001.25.6.972   DOI
9 J. E. Beasley, P. C Chu, "A genetic algorithm for the set covering problem", European Journal of Operational Research, Vol.94, No.2, pp.392-404, 1996. DOI: https://dx.doi.org/10.1016/0377-2217(95)00159-X   DOI
10 Nageswaran Tamil Alagan, "Textured insert for improved heat extraction in combination with high-pressure colling in turning of superalloys", Trollhattan, Sweden 2017.
11 F. W. Taylor, "On the Art of Cutting Metals", Trans. ASME, Vol.28, pp.310-350, 1906.
12 W. Choi, "Study on the Tool Life Constant in Tool Life Equation", Annual report of the KIT, Vol.8, pp.37-40, 1987.