Optimization of cutting conditions in slotting of multidirectional CFRP laminate

被引:0
作者
Souhir Gara
Oleg Tsoumarev
机构
[1] ENIT—BP 37,Laboratoire de Recherche Mécanique Appliquée et Ingénierie (MAI)
来源
The International Journal of Advanced Manufacturing Technology | 2018年 / 95卷
关键词
CFRP; Graphical method; Knurled tool; Optimization; PSO; Slotting;
D O I
暂无
中图分类号
学科分类号
摘要
For metallic or composite materials, the judicious choice of cutting conditions depends on several factors that may be of such objectives (time, cost of production, material removal rate, etc.) or constraints (cutting force, temperature in the machining area, consumed power, etc.). The quality of the results depends on the optimization method and the efficiency of the algorithm involved. In this paper, graphical and particle swarm optimization (PSO) methods are proposed. They aim to determine the optimal cutting conditions (cutting speed and feed per tooth) in slotting of multidirectional carbon fiber reinforced plastic laminate (CFRP), referenced G803/914, with three knurled tools having different geometries. The experiences that led to the measures of roughness, temperature, cutting efforts, and consumed power are made in the same working conditions with cutting speed ranging from 80 to 200 m/min and feed per tooth from 0.008 to 0.060 mm/rev/tooth. The results illustrate that for the graphical method, the optimum cutting speed depends on the performance “maximum total removal rate” and is the same for all the studied knurled tools while optimum feed per tooth depends on the “roughness” performance: its value depends on the tool geometry. For the PSO technique, optimum cutting speed and feed per tooth values are variable and depend on the tool geometry.
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页码:3227 / 3242
页数:15
相关论文
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  • [1] Bhatnagar N(1995)On the machining of fiber reinforced plastic (FRP) composite laminates Int J Mach Tools Manuf 35 701-716
  • [2] Ramakrishnan N(2011)Optimization of multi-pass face milling using a fuzzy particle swarm optimization algorithm Int J Adv Manuf Technol 54 45-57
  • [3] Naik NK(2011)Optimization of multi-pass turning economies through a hybrid particle swarm optimization technique Int J Adv Manuf Technol 53 421-433
  • [4] Komanduri R(2008)Computer numerical control machining parameter optimization based on particle swarm optimization Tongji Daxue Xuebao/J Tongji Univ 36 803-806
  • [5] Yang W(2011)Optimization of machining parameters in turning process using genetic algorithm and particle swarm optimization with experimental verfification Int J Eng Sci Technol 3 1091-1102
  • [6] Guo Y(2010)Parameter optimization of a multi-pass milling process using non-traditional optimization algorithms Appl Soft Comput 10 445-456
  • [7] Liao W(2008)Parallel turning process parameter optimization based on a novel heuristic approach J Manuf Sci Eng 130 031002-1-031002-12
  • [8] Costa A(2010)Optimum surface roughness prediction in face milling X20Cr13 using particle swarm optimization algorithm Proc Inst Mech Eng B J Eng Manuf 224 1645-1653
  • [9] Celano G(2009)Optimal cutting condition determination for desired surface roughness in end milling Int J Adv Manuf Technol 41 440-451
  • [10] Fichera S(2008)Cutting parameters optimization for constant cutting force in milling Appl Mech Mater 10–12 483-487