Multi Objective Optimization in Machining Operations
Process Planning activities are significantly based on experience and technical skill. In spite of the great efforts made for planning automation, this activity continues being made in manual form. Process Planning activities are significantly based on experience and technical skills. The advent of the CAM systems (Computer Aided Manufacturing) has partially close the gap left between the Automated Design and Manufacture. Meanwhile, a great dose of manual work still exists and investigation in this area is still necessary. This paper presents the application of a multi objective genetic algorithm for the definition of the optimal cutting parameters. The objective functions consider the production rate and production cost in turning operations. The obtained Pareto front is compared to high efficiency cutting range. This paper also describes one application of the developed mechanism using an example.
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- 4.Taylor, F.W.: On the art of cutting metals. ASME Journal of Engineering for Industry 28, 310–350 (1906)Google Scholar
- 6.Taha, H.: A policy for determining the optimal cycle length for a cutting tool. Journal of Industrial Engineering 17(3), 157–162 (1966)Google Scholar
- 14.Deb, K., et al.: Fast Elitist Non-Dominated Sorting Genetic Algorithm for Multi-Objective Optimization: NSGA-II. In: Deb, K., et al. (eds.) Parallel Problem Solving from Nature-PPSN VI. LNCS, vol. 1917, Springer, Heidelberg (2000)Google Scholar
- 15.Consalter, L.: Arquivo de dados tecnológicos de usinagem para a determinação automática das condições automática das condições de corte em tornos com comando numérico. Msc Thesis, Universidade Federal de Santa Catarina, Florianópolis, Brasil (1985)Google Scholar