Abstract
Optimal cutting parameters can lead to considerable savings in manufacturing fields. In this paper, to deal with the optimization problem of cutting parameters which aims to minimize the unit production cost (UC) in parallel turnings, we propose a novel optimization approach which divides this complicated problem into several sub-problems. Then a genetic algorithm (GA) is developed to search the optimal results for each sub-problem. Simulations show that the corresponding approach can find better results than previous approach to significantly reduce the production cost.
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Acknowledgments
This work was supported by the Natural Science Foundation of Fujian Province of China (No. 2016J01735, JK2015025), and the Foundation for Young Professors of Jimei University, China (No. 2011C002).
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Pan, L., Xie, S., Liu, K., Liao, J. (2016). Selection of Optimal Cutting Parameters in Parallel Turnings Using Genetic Heuristics. In: Huang, DS., Bevilacqua, V., Premaratne, P. (eds) Intelligent Computing Theories and Application. ICIC 2016. Lecture Notes in Computer Science(), vol 9771. Springer, Cham. https://doi.org/10.1007/978-3-319-42291-6_17
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DOI: https://doi.org/10.1007/978-3-319-42291-6_17
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