Selection of CNC Tool Combinations Through The Approach of Genetic Algorithm Methods with The Criteria of Minimizing Machining Time and Considering The Minimum Machining Gap
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https://doi.org/10.37577/sainteks.v6i1.644Abstract
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References
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Dong, Z., Li, H., dan Vickers (1993): Optimal Rough Machining of Sculptured Parts on a CNC Milling Machine, Journal of Engineering for Industry Volume 115 issue 4, 424-431
Groover, M.P. (2010): Fundamentals of Modern Manufacturing, 4nd ed., Prenctice Hall.
Holland, J.H. (1992): Genetic Algorithms, Scientific American, Vol. 267, No. 1 (July 1992), pp. 66-73,
Jacso, A., Szalay, T., Jauregui, J.C., dan Resendiz, J. R., (2018): A discrete simulation-based algorithm for the technological investigation of 2.5D milling operations, Journal Mechanical Engineering Science 2019, Vol. 233(1) 78–90
Wang J., Luo M., Hafeez H.M., dan Zhang D. (2018): Image Skeleton and GA Based Tool Selection for 2 1/2-Axis Rough Milling, Laboratory of Contemporary Design and Integrated Manufacturing Technology, Ministry of Education, Northwestern Polytechnical University, Xi'an 710072, China
Wang Y., Ma H.J., Gao C.H., Xu H.G. dan Zhou X.H. (2005): A computer aided tool selection system for 3D die/mould-cavity NC machining using both a heuristic and analytical approachâ€, International Journal of Computer Integrated Manufacturing Volume 18 issue 8, 686 – 701
Buani, D. P. (2021). Penerapan Algoritma Naive Bayes dengan Seleksi Fitur Algoritma Genetika untuk Prediksi Gagal Jantung. Evolusi; Jurnal Sains dan Manajemen, 43-48.
Chen, Z. C. dan Fu, Q. (2011): An optimal approach to multiple tool selection and their numerical control path generation for aggressive rough machining of pockets with free-form boundarie, Computer-Aided Design Volume 43 issue 6, 651–663
Dong, Z., Li, H., dan Vickers (1993): Optimal Rough Machining of Sculptured Parts on a CNC Milling Machine, Journal of Engineering for Industry Volume 115 issue 4, 424-431
Groover, M.P. (2010): Fundamentals of Modern Manufacturing, 4nd ed., Prenctice Hall.
Holland, J.H. (1992): Genetic Algorithms, Scientific American, Vol. 267, No. 1 (July 1992), pp. 66-73,
Jacso, A., Szalay, T., Jauregui, J.C., dan Resendiz, J. R., (2018): A discrete simulation-based algorithm for the technological investigation of 2.5D milling operations, Journal Mechanical Engineering Science 2019, Vol. 233(1) 78–90
Wang J., Luo M., Hafeez H.M., dan Zhang D. (2018): Image Skeleton and GA Based Tool Selection for 2 1/2-Axis Rough Milling, Laboratory of Contemporary Design and Integrated Manufacturing Technology, Ministry of Education, Northwestern Polytechnical University, Xi'an 710072, China
Wang Y., Ma H.J., Gao C.H., Xu H.G. dan Zhou X.H. (2005): A computer aided tool selection system for 3D die/mould-cavity NC machining using both a heuristic and analytical approachâ€, International Journal of Computer Integrated Manufacturing Volume 18 issue 8, 686 – 701
